Plot for 6c
ERM
2025-01-21
Last updated: 2025-01-21
Checks: 7 0
Knit directory: ATAC_learning/
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Unstaged changes:
Modified: ATAC_learning.Rproj
Modified: analysis/Correlation_of_SNPnPEAK.Rmd
Modified: analysis/Enhancer_files_ff.Rmd
Modified: analysis/TE_analysis_ff.Rmd
Modified: analysis/final_four_analysis.Rmd
Modified: analysis/final_plot_attempt.Rmd
Modified: analysis/index.Rmd
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | 3eb76dd | E. Renee Matthews | 2025-01-21 | adding in CELSR2 |
| html | a505a0a | E. Renee Matthews | 2025-01-17 | Build site. |
| Rmd | 4a1d2bf | E. Renee Matthews | 2025-01-17 | updates to plots |
| html | ae1542c | E. Renee Matthews | 2025-01-17 | Build site. |
| Rmd | e179f61 | E. Renee Matthews | 2025-01-17 | updates with comments |
| html | d09c7db | E. Renee Matthews | 2025-01-17 | Build site. |
| Rmd | 20ed2fe | E. Renee Matthews | 2025-01-17 | additional analysis |
library(tidyverse)
library(kableExtra)
library(broom)
library(RColorBrewer)
library("TxDb.Hsapiens.UCSC.hg38.knownGene")
library("org.Hs.eg.db")
library(rtracklayer)
library(ggfortify)
library(readr)
library(BiocGenerics)
library(gridExtra)
library(VennDiagram)
library(scales)
library(ggVennDiagram)
library(BiocParallel)
library(ggpubr)
library(edgeR)
library(genomation)
library(ggsignif)
library(plyranges)
library(ggrepel)
library(ComplexHeatmap)
library(cowplot)
library(smplot2)
library(readxl)Notes to self(and anyone else who is reading this!):
This is me applying the same code from my correlation_of_SNPnPeak.rmd
document.
Summary of what I am doing: 1: create a list of peaks within +/-20 kb,
+/-10 kb, and +/- 5 kb of an RNA expressed gene TSS. (3 separate
lists)
2: making a dataframe that has all ATAC 3 hour and 24 hr LFC by peak for
later ease of use. 3: creating lists of gwas SNPs (HF and ARR lists
only) that are either 1bp, 10kb, 20kb, or 50kb in length to determine
impact of the SNP on surrounding peaks.
Collapsed_new_peaks <- read_delim("data/Final_four_data/collapsed_new_peaks.txt", delim = "\t", col_names = TRUE)
Collapsed_new_peaks_gr <- Collapsed_new_peaks %>% dplyr::select(chr:Peakid) %>% GRanges()
peak_10kb_neargenes <-
Collapsed_new_peaks %>%
dplyr::filter(dist_to_NG<5000&dist_to_NG>-5000) %>%
distinct(Peakid, .keep_all = TRUE) %>%
dplyr::select(Peakid,NCBI_gene,SYMBOL)
peak_20kb_neargenes <-
Collapsed_new_peaks %>%
dplyr::filter(dist_to_NG<10000&dist_to_NG>-10000) %>%
distinct(Peakid, .keep_all = TRUE) %>%
dplyr::select(Peakid,NCBI_gene,SYMBOL)
peak_40kb_neargenes <-
Collapsed_new_peaks %>%
dplyr::filter(dist_to_NG<20000&dist_to_NG>-20000) %>%
distinct(Peakid, .keep_all = TRUE) %>%
dplyr::select(Peakid,NCBI_gene,SYMBOL)
RNA_median_3_lfc <- readRDS("data/other_papers/RNA_median_3_lfc.RDS")
RNA_median_24_lfc <- readRDS("data/other_papers/RNA_median_24_lfc.RDS")
ATAC_24_lfc <- read_csv("data/Final_four_data/median_24_lfc.csv")
ATAC_3_lfc <- read_csv("data/Final_four_data/median_3_lfc.csv")
gwas_HF <- readRDS("data/gwas_5_dataframe.RDS")
gwas_ARR <- readRDS("data/gwas_2_dataframe.RDS")
Short_gwas_gr <-
gwas_ARR %>%
distinct(SNPS,.keep_all = TRUE) %>%
dplyr::select(CHR_ID, CHR_POS,SNPS) %>%
mutate(gwas="ARR") %>%
rbind(gwas_HF %>%
distinct(SNPS,.keep_all = TRUE) %>%
dplyr::select(CHR_ID, CHR_POS,SNPS) %>%
mutate(gwas="HF")) %>%
na.omit() %>%
mutate(seqnames=paste0("chr",CHR_ID), CHR_POS=as.numeric(CHR_POS)) %>%
na.omit() %>%
mutate(start=CHR_POS, end=CHR_POS, width=1) %>%
GRanges()
Short_gwas_5k_gr <-
gwas_ARR %>%
distinct(SNPS,.keep_all = TRUE) %>%
dplyr::select(CHR_ID, CHR_POS,SNPS) %>%
mutate(gwas="ARR") %>%
rbind(gwas_HF %>%
distinct(SNPS,.keep_all = TRUE) %>%
dplyr::select(CHR_ID, CHR_POS,SNPS) %>%
mutate(gwas="HF")) %>%
na.omit() %>%
mutate(seqnames=paste0("chr",CHR_ID), CHR_POS=as.numeric(CHR_POS)) %>%
na.omit() %>%
mutate(start=CHR_POS-5000, end=CHR_POS+4999) %>%
GRanges()
Short_gwas_20k_gr <-
gwas_ARR %>%
distinct(SNPS,.keep_all = TRUE) %>%
dplyr::select(CHR_ID, CHR_POS,SNPS) %>%
mutate(gwas="ARR") %>%
rbind(gwas_HF %>%
distinct(SNPS,.keep_all = TRUE) %>%
dplyr::select(CHR_ID, CHR_POS,SNPS) %>%
mutate(gwas="HF")) %>%
na.omit() %>%
mutate(seqnames=paste0("chr",CHR_ID), CHR_POS=as.numeric(CHR_POS)) %>%
na.omit() %>%
mutate(start=(CHR_POS-10000),end=(CHR_POS+9999), width=20000) %>%
distinct() %>%
GRanges()
Short_gwas_50k_gr <-
gwas_ARR %>%
distinct(SNPS,.keep_all = TRUE) %>%
dplyr::select(CHR_ID, CHR_POS,SNPS) %>%
mutate(gwas="ARR") %>%
rbind(gwas_HF %>%
distinct(SNPS,.keep_all = TRUE) %>%
dplyr::select(CHR_ID, CHR_POS,SNPS) %>%
mutate(gwas="HF")) %>%
na.omit() %>%
mutate(seqnames=paste0("chr",CHR_ID), CHR_POS=as.numeric(CHR_POS)) %>%
na.omit() %>%
mutate(start=(CHR_POS-25000),end=(CHR_POS+24999), width=50000) %>%
distinct() %>%
GRanges()
gwas_peak_check <- join_overlap_intersect(Collapsed_new_peaks_gr,Short_gwas_gr) %>%
as.data.frame()
#
gwas_peak_check_10k <- join_overlap_intersect(Collapsed_new_peaks_gr,Short_gwas_5k_gr) %>%
as.data.frame()
gwas_peak_check_20k <- join_overlap_intersect(Collapsed_new_peaks_gr,Short_gwas_20k_gr) %>%
as.data.frame()
gwas_peak_check_50k <- join_overlap_intersect(Collapsed_new_peaks_gr,Short_gwas_50k_gr) %>%
as.data.frame()
ATAC_LFC <- Collapsed_new_peaks %>%
dplyr::select(Peakid) %>%
left_join(.,(ATAC_3_lfc %>% dplyr::select(peak, med_3h_lfc)), by=c("Peakid"="peak")) %>%
left_join(.,(ATAC_24_lfc %>% dplyr::select(peak, med_24h_lfc)), by=c("Peakid"="peak"))
Short_gwas_gr %>% as.data.frame(
) seqnames start end width strand CHR_ID CHR_POS SNPS
1 chr1 50875994 50875994 1 * 1 50875994 rs7545860
2 chr18 30783657 30783657 1 * 18 30783657 rs8086068
3 chr6 51020055 51020055 1 * 6 51020055 rs190759
4 chr12 127308069 127308069 1 * 12 127308069 rs1823172
5 chr15 78633676 78633676 1 * 15 78633676 rs950776
6 chr17 62701571 62701571 1 * 17 62701571 rs2251393
7 chr20 61668355 61668355 1 * 20 61668355 rs944260
8 chr12 92496744 92496744 1 * 12 92496744 rs10219495
9 chr12 91586597 91586597 1 * 12 91586597 rs10777317
10 chr14 100159565 100159565 1 * 14 100159565 rs7157599
11 chr8 48899642 48899642 1 * 8 48899642 rs12155623
12 chr3 140456518 140456518 1 * 3 140456518 rs11708189
13 chr12 97295990 97295990 1 * 12 97295990 rs10777845
14 chr2 157923692 157923692 1 * 2 157923692 rs10183640
15 chr1 171292054 171292054 1 * 1 171292054 rs6660565
16 chr22 39291479 39291479 1 * 22 39291479 rs54211
17 chr8 104945312 104945312 1 * 8 104945312 rs16872085
18 chr3 270666 270666 1 * 3 270666 rs6764363
19 chr12 75826838 75826838 1 * 12 75826838 rs7307780
20 chr11 96133536 96133536 1 * 11 96133536 rs10765792
21 chr18 6939948 6939948 1 * 18 6939948 rs597503
22 chr15 94622351 94622351 1 * 15 94622351 rs1014922
23 chr17 70648048 70648048 1 * 17 70648048 rs17718586
24 chr6 151964552 151964552 1 * 6 151964552 rs2982694
25 chr17 2868218 2868218 1 * 17 2868218 rs12603284
26 chr16 9650238 9650238 1 * 16 9650238 rs17550532
27 chr15 75426328 75426328 1 * 15 75426328 rs8028182
28 chr14 23563861 23563861 1 * 14 23563861 rs2281680
29 chr13 24508492 24508492 1 * 13 24508492 rs9581094
30 chr12 50819650 50819650 1 * 12 50819650 rs17291650
31 chr11 23023046 23023046 1 * 11 23023046 rs10833905
32 chr10 94276223 94276223 1 * 10 94276223 rs11187837
33 chr13 74168185 74168185 1 * 13 74168185 rs12429889
34 chr5 153677988 153677988 1 * 5 153677988 rs12189362
35 chr10 18661626 18661626 1 * 10 18661626 rs10829156
36 chr14 87039904 87039904 1 * 14 87039904 rs11624056
37 chr22 27694209 27694209 1 * 22 27694209 rs5762311
38 chr8 77768114 77768114 1 * 8 77768114 rs3864663
39 chr7 97991379 97991379 1 * 7 97991379 rs13438327
40 chr7 12892424 12892424 1 * 7 12892424 rs732577
41 chr2 192090779 192090779 1 * 2 192090779 rs13007495
42 chr2 159213245 159213245 1 * 2 159213245 rs13022357
43 chr2 154370165 154370165 1 * 2 154370165 rs707040
44 chr19 45804148 45804148 1 * 19 45804148 rs8111071
45 chr2 11370822 11370822 1 * 2 11370822 rs6716724
46 chr2 54120613 54120613 1 * 2 54120613 rs1559040
47 chr2 179701951 179701951 1 * 2 179701951 rs16866933
48 chr4 116333133 116333133 1 * 4 116333133 rs2389202
49 chr5 113694467 113694467 1 * 5 113694467 rs4621553
50 chr18 26576461 26576461 1 * 18 26576461 rs16942421
51 chr7 46202985 46202985 1 * 7 46202985 rs6964415
52 chr18 35977503 35977503 1 * 18 35977503 rs2276314
53 chr3 38582762 38582762 1 * 3 38582762 rs3922844
54 chr6 39340966 39340966 1 * 6 39340966 rs9471077
55 chr3 38803890 38803890 1 * 3 38803890 rs9827945
56 chr2 13488323 13488323 1 * 2 13488323 rs12692501
57 chr6 41163990 41163990 1 * 6 41163990 rs2234247
58 chr21 29151972 29151972 1 * 21 29151972 rs3787662
59 chr3 73108137 73108137 1 * 3 73108137 rs6766673
60 chr2 16726625 16726625 1 * 2 16726625 rs1722426
61 chr15 29439240 29439240 1 * 15 29439240 rs11856574
62 chr1 234680808 234680808 1 * 1 234680808 rs482329
63 chr14 23397504 23397504 1 * 14 23397504 rs412768
64 chr2 135149518 135149518 1 * 2 135149518 rs6730157
65 chr10 62465689 62465689 1 * 10 62465689 rs2077316
66 chr4 110485663 110485663 1 * 4 110485663 rs192667187
67 chr4 110491909 110491909 1 * 4 110491909 rs192833524
68 chr2 159333698 159333698 1 * 2 159333698 rs4665058
69 chr2 232894174 232894174 1 * 2 232894174 rs1554218
70 chr1 111836404 111836404 1 * 1 111836404 rs12129789
71 chr1 170653968 170653968 1 * 1 170653968 rs588837
72 chr1 203070474 203070474 1 * 1 203070474 rs871298
73 chr10 103575604 103575604 1 * 10 103575604 rs373205748
74 chr10 20868692 20868692 1 * 10 20868692 rs2296610
75 chr10 76176911 76176911 1 * 10 76176911 rs10458661
76 chr12 111171923 111171923 1 * 12 111171923 rs3809297
77 chr12 114355435 114355435 1 * 12 114355435 rs883079
78 chr12 24656044 24656044 1 * 12 24656044 rs34109091
79 chr12 56718164 56718164 1 * 12 56718164 rs58668145
80 chr14 32454619 32454619 1 * 14 32454619 rs145451266
81 chr16 73019123 73019123 1 * 16 73019123 rs2359171
82 chr17 45942346 45942346 1 * 17 45942346 rs242557
83 chr2 65039704 65039704 1 * 2 65039704 rs34443138
84 chr4 110795357 110795357 1 * 4 110795357 rs12644625
85 chr4 173530418 173530418 1 * 4 173530418 rs3822127
86 chr6 133122523 133122523 1 * 6 133122523 rs6941949
87 chr7 116554851 116554851 1 * 7 116554851 rs729949
88 chr9 94880600 94880600 1 * 9 94880600 rs141301535
89 chrX 23381384 23381384 1 * X 23381384 rs73205368
90 chr4 110840331 110840331 1 * 4 110840331 rs3853445
91 chr10 103571190 103571190 1 * 10 103571190 rs12253987
92 chr16 72843259 72843259 1 * 16 72843259 rs9921081
93 chr4 173678308 173678308 1 * 4 173678308 rs4615152
94 chr4 110809256 110809256 1 * 4 110809256 rs12506083
95 chr1 203065778 203065778 1 * 1 203065778 rs3737883
96 chr1 170600176 170600176 1 * 1 170600176 rs3903239
97 chr4 110784612 110784612 1 * 4 110784612 rs6817105
98 chr10 103539854 103539854 1 * 10 103539854 rs6584555
99 chr16 73017721 73017721 1 * 16 73017721 rs2106261
100 chr15 69714534 69714534 1 * 15 69714534 rs4776472
101 chr13 46259582 46259582 1 * 13 46259582 rs958546
102 chr11 99622442 99622442 1 * 11 99622442 rs10501920
103 chr6 32039119 32039119 1 * 6 32039119 rs6455
104 chr8 74007478 74007478 1 * 8 74007478 rs10504554
105 chr10 18705654 18705654 1 * 10 18705654 rs11015781
106 chr5 135024741 135024741 1 * 5 135024741 rs31209
107 chr12 25905670 25905670 1 * 12 25905670 rs117640426
108 chr1 111849738 111849738 1 * 1 111849738 rs12044963
109 chr1 170368215 170368215 1 * 1 170368215 rs4656762
110 chr2 65049602 65049602 1 * 2 65049602 rs2540951
111 chr4 110707883 110707883 1 * 4 110707883 rs16997168
112 chr4 173526992 173526992 1 * 4 173526992 rs10024737
113 chr5 114413763 114413763 1 * 5 114413763 rs1013168
114 chr7 116551643 116551643 1 * 7 116551643 rs9886216
115 chr10 76190062 76190062 1 * 10 76190062 rs16932995
116 chr10 103713072 103713072 1 * 10 103713072 rs10509768
117 chr12 114351421 114351421 1 * 12 114351421 rs2384407
118 chr16 72877507 72877507 1 * 16 72877507 rs7197197
119 chr2 25937505 25937505 1 * 2 25937505 rs7604968
120 chr10 63561387 63561387 1 * 10 63561387 rs12245149
121 chr10 67826634 67826634 1 * 10 67826634 rs138645114
122 chr1 164093291 164093291 1 * 1 164093291 rs528903211
123 chr1 164354848 164354848 1 * 1 164354848 rs750729995
124 chr1 165247437 165247437 1 * 1 165247437 rs747358876
125 chr1 165362063 165362063 1 * 1 165362063 rs745582874
126 chr2 20576675 20576675 1 * 2 20576675 rs182836018
127 chr4 102192657 102192657 1 * 4 102192657 rs77616117
128 chr8 9026103 9026103 1 * 8 9026103 rs189051215
129 chr13 100490655 100490655 1 * 13 100490655 rs768476991
130 chr13 100743542 100743542 1 * 13 100743542 rs535535747
131 chr17 17199699 17199699 1 * 17 17199699 rs12939857
132 chr4 173523751 173523751 1 * 4 173523751 rs17059534
133 chr4 110796911 110796911 1 * 4 110796911 rs6843082
134 chr1 203057463 203057463 1 * 1 203057463 rs17461925
135 chr2 65045228 65045228 1 * 2 65045228 rs2540953
136 chr4 173682953 173682953 1 * 4 173682953 rs7698692
137 chr10 103717405 103717405 1 * 10 103717405 rs2047036
138 chr5 140333293 140333293 1 * 5 140333293 rs13385
139 chr9 90890978 90890978 1 * 9 90890978 rs1675334
140 chr4 110793733 110793733 1 * 4 110793733 rs2220427
141 chr7 116560326 116560326 1 * 7 116560326 rs1049334
142 chr11 80889048 80889048 1 * 11 80889048 rs60572254
143 chr6 122093011 122093011 1 * 6 122093011 rs13219206
144 chr1 170643732 170643732 1 * 1 170643732 rs639652
145 chr12 111269073 111269073 1 * 12 111269073 rs4766566
146 chr19 47639489 47639489 1 * 19 47639489 rs11881441
147 chr20 38213512 38213512 1 * 20 38213512 rs3746471
148 chr22 21644940 21644940 1 * 22 21644940 rs5754508
149 chr22 41793403 41793403 1 * 22 41793403 rs139557
150 chr1 10736809 10736809 1 * 1 10736809 rs880315
151 chr1 21956126 21956126 1 * 1 21956126 rs7529220
152 chr1 41078607 41078607 1 * 1 41078607 rs2885697
153 chr1 51539068 51539068 1 * 1 51539068 rs12022114
154 chr1 111840049 111840049 1 * 1 111840049 rs11102343
155 chr1 115755137 115755137 1 * 1 115755137 rs4073778
156 chr1 147756741 147756741 1 * 1 147756741 rs11240121
157 chr1 154890476 154890476 1 * 1 154890476 rs11264280
158 chr1 170659114 170659114 1 * 1 170659114 rs680084
159 chr1 203063025 203063025 1 * 1 203063025 rs4950913
160 chr1 205722188 205722188 1 * 1 205722188 rs4951258
161 chr2 25937071 25937071 1 * 2 25937071 rs6546620
162 chr2 61449805 61449805 1 * 2 61449805 rs2694635
163 chr2 65057097 65057097 1 * 2 65057097 rs2540949
164 chr2 69879700 69879700 1 * 2 69879700 rs6747542
165 chr2 86356069 86356069 1 * 2 86356069 rs13387570
166 chr2 144924368 144924368 1 * 2 144924368 rs11679718
167 chr2 148042141 148042141 1 * 2 148042141 rs12992231
168 chr2 174648092 174648092 1 * 2 174648092 rs7574892
169 chr2 178548383 178548383 1 * 2 178548383 rs3731748
170 chr2 200315300 200315300 1 * 2 200315300 rs3820888
171 chr1 983237 983237 1 * 1 983237 rs4970418
172 chr1 15872556 15872556 1 * 1 15872556 rs9782984
173 chr1 38920042 38920042 1 * 1 38920042 rs75414548
174 chr1 99683752 99683752 1 * 1 99683752 rs1933723
175 chr4 70911218 70911218 1 * 4 70911218 rs12512502
176 chr4 82989559 82989559 1 * 4 82989559 rs6841049
177 chr5 140323701 140323701 1 * 5 140323701 rs17118812
178 chr6 22598030 22598030 1 * 6 22598030 rs7766436
179 chr6 75454873 75454873 1 * 6 75454873 rs12209223
180 chr6 134797951 134797951 1 * 6 134797951 rs4896104
181 chr7 105972290 105972290 1 * 7 105972290 rs2727757
182 chr8 117851173 117851173 1 * 8 117851173 rs17430357
183 chr9 116419515 116419515 1 * 9 116419515 rs17303101
184 chr10 32483806 32483806 1 * 10 32483806 rs11527634
185 chr10 49277389 49277389 1 * 10 49277389 rs76460895
186 chr10 79139212 79139212 1 * 10 79139212 rs1769758
187 chr11 3868829 3868829 1 * 11 3868829 rs7126870
188 chr11 14014642 14014642 1 * 11 14014642 rs10500790
189 chr11 95356718 95356718 1 * 11 95356718 rs517938
190 chr12 12733093 12733093 1 * 12 12733093 rs10845620
191 chr12 104098225 104098225 1 * 12 104098225 rs2629755
192 chr13 21537382 21537382 1 * 13 21537382 rs11841562
193 chr13 73946049 73946049 1 * 13 73946049 rs1886512
194 chr16 15808858 15808858 1 * 16 15808858 rs9284324
195 chr18 79396537 79396537 1 * 18 79396537 rs8096658
196 chr2 212386779 212386779 1 * 2 212386779 rs13019524
197 chr3 12800305 12800305 1 * 3 12800305 rs7650482
198 chr3 24431375 24431375 1 * 3 24431375 rs73032363
199 chr3 38725824 38725824 1 * 3 38725824 rs6801957
200 chr3 66403767 66403767 1 * 3 66403767 rs34080181
201 chr3 69357030 69357030 1 * 3 69357030 rs17005647
202 chr3 89440379 89440379 1 * 3 89440379 rs6771054
203 chr3 111835579 111835579 1 * 3 111835579 rs10804493
204 chr3 136095167 136095167 1 * 3 136095167 rs1278493
205 chr3 179455191 179455191 1 * 3 179455191 rs7612445
206 chr3 195080124 195080124 1 * 3 195080124 rs60902112
207 chr4 10102854 10102854 1 * 4 10102854 rs12640611
208 chr4 80248758 80248758 1 * 4 80248758 rs11099098
209 chr4 102791180 102791180 1 * 4 102791180 rs223449
210 chr4 110789811 110789811 1 * 4 110789811 rs17042175
211 chr4 113507558 113507558 1 * 4 113507558 rs55754224
212 chr4 148016386 148016386 1 * 4 148016386 rs10213171
213 chr4 173551270 173551270 1 * 4 173551270 rs4282143
214 chr5 107091908 107091908 1 * 5 107091908 rs6596717
215 chr5 114410483 114410483 1 * 5 114410483 rs337708
216 chr5 128854670 128854670 1 * 5 128854670 rs2012809
217 chr5 138107797 138107797 1 * 5 138107797 rs529526
218 chr5 143438558 143438558 1 * 5 143438558 rs6580277
219 chr5 168966222 168966222 1 * 5 168966222 rs77328981
220 chr5 173243742 173243742 1 * 5 173243742 rs6891790
221 chr6 16418331 16418331 1 * 6 16418331 rs9370893
222 chr6 18209878 18209878 1 * 6 18209878 rs34969716
223 chr6 34221089 34221089 1 * 6 34221089 rs12214804
224 chr6 36679512 36679512 1 * 6 36679512 rs3176326
225 chr6 87176617 87176617 1 * 6 87176617 rs7757330
226 chr6 118653635 118653635 1 * 6 118653635 rs9481842
227 chr6 122077095 122077095 1 * 6 122077095 rs72966339
228 chr6 133111184 133111184 1 * 6 133111184 rs6902225
229 chr6 149092383 149092383 1 * 6 149092383 rs78811127
230 chr7 855648 855648 1 * 7 855648 rs6461461
231 chr7 14334089 14334089 1 * 7 14334089 rs12154315
232 chr7 28377595 28377595 1 * 7 28377595 rs9639575
233 chr7 92620826 92620826 1 * 7 92620826 rs42044
234 chr7 116558567 116558567 1 * 7 116558567 rs1997571
235 chr7 150972888 150972888 1 * 7 150972888 rs3778872
236 chr8 11927032 11927032 1 * 8 11927032 rs6996342
237 chr8 18055243 18055243 1 * 8 18055243 rs399485
238 chr8 21947754 21947754 1 * 8 21947754 rs6998692
239 chr8 123597926 123597926 1 * 8 123597926 rs58847541
240 chr8 140730769 140730769 1 * 8 140730769 rs6994744
241 chr9 20235006 20235006 1 * 9 20235006 rs4977397
242 chr9 94951177 94951177 1 * 9 94951177 rs10821415
243 chr9 136202927 136202927 1 * 9 136202927 rs2274115
244 chr10 20953453 20953453 1 * 10 20953453 rs7910227
245 chr14 72888423 72888423 1 * 14 72888423 rs2110552
246 chr14 76960182 76960182 1 * 14 76960182 rs10873298
247 chr15 70171653 70171653 1 * 15 70171653 rs2415081
248 chr15 73374914 73374914 1 * 15 73374914 rs7172038
249 chr15 80384583 80384583 1 * 15 80384583 rs12908004
250 chr15 98725621 98725621 1 * 15 98725621 rs4965430
251 chr16 714753 714753 1 * 16 714753 rs3809666
252 chr16 1954717 1954717 1 * 16 1954717 rs2815301
253 chr16 73014468 73014468 1 * 16 73014468 rs67329386
254 chr17 1408752 1408752 1 * 17 1408752 rs61248729
255 chr17 7511639 7511639 1 * 17 7511639 rs2071502
256 chr17 12715363 12715363 1 * 17 12715363 rs72811294
257 chr17 39893336 39893336 1 * 17 39893336 rs7359623
258 chr17 47060667 47060667 1 * 17 47060667 rs145153053
259 chr17 70425662 70425662 1 * 17 70425662 rs1396517
260 chr18 48947822 48947822 1 * 18 48947822 rs9953366
261 chr20 62557186 62557186 1 * 20 62557186 rs6089752
262 chr21 34746814 34746814 1 * 21 34746814 rs2834618
263 chr22 18114735 18114735 1 * 22 18114735 rs464901
264 chr22 25768112 25768112 1 * 22 25768112 rs133902
265 chr1 170662622 170662622 1 * 1 170662622 rs629234
266 chr1 203062910 203062910 1 * 1 203062910 rs11579558
267 chr10 67854979 67854979 1 * 10 67854979 rs12360521
268 chr10 73654586 73654586 1 * 10 73654586 rs60212594
269 chr10 76176912 76176912 1 * 10 76176912 rs10458662
270 chr10 103556539 103556539 1 * 10 103556539 rs74154539
271 chr10 110816937 110816937 1 * 10 110816937 rs10749053
272 chr11 19988745 19988745 1 * 11 19988745 rs4757877
273 chr11 121783619 121783619 1 * 11 121783619 rs7946552
274 chr11 128894675 128894675 1 * 11 128894675 rs76097649
275 chr12 24619033 24619033 1 * 12 24619033 rs10842383
276 chr12 26195496 26195496 1 * 12 26195496 rs113819537
277 chr12 32825503 32825503 1 * 12 32825503 rs12809354
278 chr12 56712154 56712154 1 * 12 56712154 rs2860482
279 chr12 69619635 69619635 1 * 12 69619635 rs71454237
280 chr12 75845075 75845075 1 * 12 75845075 rs1565765
281 chr12 111193961 111193961 1 * 12 111193961 rs4766552
282 chr12 122827504 122827504 1 * 12 122827504 rs897393
283 chr12 124328132 124328132 1 * 12 124328132 rs3741508
284 chr12 132515028 132515028 1 * 12 132515028 rs4883571
285 chr13 22794695 22794695 1 * 13 22794695 rs3904323
286 chr13 113210523 113210523 1 * 13 113210523 rs2316443
287 chr14 23395595 23395595 1 * 14 23395595 rs422068
288 chr14 32521231 32521231 1 * 14 32521231 rs11156751
289 chr14 34704569 34704569 1 * 14 34704569 rs73241997
290 chr14 64213242 64213242 1 * 14 64213242 rs2738413
291 chr2 65128252 65128252 1 * 2 65128252 rs75251643
292 chr2 200298731 200298731 1 * 2 200298731 rs4673904
293 chr3 12831496 12831496 1 * 3 12831496 rs75387493
294 chr4 148015263 148015263 1 * 4 148015263 rs10213376
295 chr4 173542765 173542765 1 * 4 173542765 rs187693118
296 chr8 123622957 123622957 1 * 8 123622957 rs4871397
297 chr9 95129587 95129587 1 * 9 95129587 rs149672087
298 chr10 103574950 103574950 1 * 10 103574950 rs185158502
299 chr12 24648922 24648922 1 * 12 24648922 rs7973464
300 chr12 26443292 26443292 1 * 12 26443292 rs74763618
301 chr14 32442886 32442886 1 * 14 32442886 rs10138310
302 chr16 30608424 30608424 1 * 16 30608424 rs1055894680
303 chrX 138708418 138708418 1 * X 138708418 rs778479352
304 chr2 65155127 65155127 1 * 2 65155127 rs9989843
305 chr4 173530848 173530848 1 * 4 173530848 rs2276940
306 chr6 133244597 133244597 1 * 6 133244597 rs1582725060
307 chr9 95006476 95006476 1 * 9 95006476 rs147288039
308 chr12 24650915 24650915 1 * 12 24650915 rs60634518
309 chr14 32505638 32505638 1 * 14 32505638 rs8010040
310 chr4 110776497 110776497 1 * 4 110776497 rs78229461
311 chr10 20913431 20913431 1 * 10 20913431 rs3802729
312 chr4 110742777 110742777 1 * 4 110742777 rs78073007
313 chr4 110799605 110799605 1 * 4 110799605 rs10033464
314 chr4 110789013 110789013 1 * 4 110789013 rs2200733
315 chr16 72995261 72995261 1 * 16 72995261 rs7193343
316 chr10 73661450 73661450 1 * 10 73661450 rs10824026
317 chr2 178546938 178546938 1 * 2 178546938 rs2288327
318 chr10 103720629 103720629 1 * 10 103720629 rs35176054
319 chr1 50525780 50525780 1 * 1 50525780 rs56202902
320 chr2 178624999 178624999 1 * 2 178624999 rs12614435
321 chr1 154858667 154858667 1 * 1 154858667 rs34245846
322 chr1 170224684 170224684 1 * 1 170224684 rs72700114
323 chr5 136209152 136209152 1 * 5 136209152 rs77831929
324 chr16 72998133 72998133 1 * 16 72998133 rs4404097
325 chr10 76176818 76176818 1 * 10 76176818 rs10458660
326 chr10 103582915 103582915 1 * 10 103582915 rs11598047
327 chr11 19989899 19989899 1 * 11 19989899 rs10741807
328 chr11 121790799 121790799 1 * 11 121790799 rs4935786
329 chr12 24626557 24626557 1 * 12 24626557 rs4963776
330 chr12 26192593 26192593 1 * 12 26192593 rs17380837
331 chr12 75844207 75844207 1 * 12 75844207 rs12426679
332 chr12 122843353 122843353 1 * 12 122843353 rs10773657
333 chr12 132573624 132573624 1 * 12 132573624 rs6560886
334 chr13 22794804 22794804 1 * 13 22794804 rs9506925
335 chr13 113218398 113218398 1 * 13 113218398 rs35569628
336 chr14 72782711 72782711 1 * 14 72782711 rs74884082
337 chr15 57632516 57632516 1 * 15 57632516 rs147301839
338 chr16 2215270 2215270 1 * 16 2215270 rs77316573
339 chr16 73033862 73033862 1 * 16 73033862 rs876727
340 chr18 51153152 51153152 1 * 18 51153152 rs9963878
341 chr1 170225682 170225682 1 * 1 170225682 rs72700118
342 chr1 10730740 10730740 1 * 1 10730740 rs284277
343 chr4 111004500 111004500 1 * 4 111004500 rs79399769
344 chr1 51069367 51069367 1 * 1 51069367 rs146518726
345 chr4 111533139 111533139 1 * 4 111533139 rs138311480
346 chr4 112408189 112408189 1 * 4 112408189 rs7687819
347 chr5 173966108 173966108 1 * 5 173966108 rs28439930
348 chr1 203057086 203057086 1 * 1 203057086 rs10753933
349 chr2 25942659 25942659 1 * 2 25942659 rs7578393
350 chr12 24562114 24562114 1 * 12 24562114 rs2291437
351 chr12 69677733 69677733 1 * 12 69677733 rs775498
352 chr2 86367364 86367364 1 * 2 86367364 rs72926475
353 chr15 80701947 80701947 1 * 15 80701947 rs2759301
354 chr2 145002786 145002786 1 * 2 145002786 rs67969609
355 chr5 168959084 168959084 1 * 5 168959084 rs12188351
356 chr6 16415520 16415520 1 * 6 16415520 rs73366713
357 chr6 87111783 87111783 1 * 6 87111783 rs2031522
358 chr6 118238495 118238495 1 * 6 118238495 rs3951016
359 chr6 122082413 122082413 1 * 6 122082413 rs13195459
360 chr6 149077964 149077964 1 * 6 149077964 rs117984853
361 chr7 14332384 14332384 1 * 7 14332384 rs55734480
362 chr7 28376208 28376208 1 * 7 28376208 rs6462079
363 chr7 74720592 74720592 1 * 7 74720592 rs35005436
364 chr7 92648802 92648802 1 * 7 92648802 rs56201652
365 chr7 116551247 116551247 1 * 7 116551247 rs11773845
366 chr7 128776990 128776990 1 * 7 128776990 rs55985730
367 chr7 150964321 150964321 1 * 7 150964321 rs7789146
368 chr8 11642399 11642399 1 * 8 11642399 rs35620480
369 chr8 18056461 18056461 1 * 8 18056461 rs7508
370 chr8 21964267 21964267 1 * 8 21964267 rs7834729
371 chr8 123539735 123539735 1 * 8 123539735 rs62521286
372 chr10 67905124 67905124 1 * 10 67905124 rs7096385
373 chr1 147760632 147760632 1 * 1 147760632 rs10465885
374 chr1 154423470 154423470 1 * 1 154423470 rs6689306
375 chr1 154741530 154741530 1 * 1 154741530 rs4999127
376 chr1 170618199 170618199 1 * 1 170618199 rs577676
377 chr3 38592651 38592651 1 * 3 38592651 rs7374540
378 chr3 38668824 38668824 1 * 3 38668824 rs7373065
379 chr4 110334761 110334761 1 * 4 110334761 rs244017
380 chr4 110603473 110603473 1 * 4 110603473 rs61501369
381 chr4 110675204 110675204 1 * 4 110675204 rs6850025
382 chr1 48844092 48844092 1 * 1 48844092 rs11590635
383 chr4 111244056 111244056 1 * 4 111244056 rs1532170
384 chr1 111921382 111921382 1 * 1 111921382 rs1545300
385 chr4 111683665 111683665 1 * 4 111683665 rs114904067
386 chr1 147783720 147783720 1 * 1 147783720 rs79187193
387 chr4 173526198 173526198 1 * 4 173526198 rs10520260
388 chr6 121778006 121778006 1 * 6 121778006 rs9401451
389 chr10 103517717 103517717 1 * 10 103517717 rs55693294
390 chr2 61242991 61242991 1 * 2 61242991 rs11125871
391 chr12 55662031 55662031 1 * 12 55662031 rs11614818
392 chr14 32455299 32455299 1 * 14 32455299 rs1957021
393 chr2 126675889 126675889 1 * 2 126675889 rs28387148
394 chr16 1626803 1626803 1 * 16 1626803 rs118159104
395 chr2 174690986 174690986 1 * 2 174690986 rs56181519
396 chr2 212401279 212401279 1 * 2 212401279 rs35544454
397 chr3 24421744 24421744 1 * 3 24421744 rs73041705
398 chr3 38730434 38730434 1 * 3 38730434 rs6790396
399 chr4 80243569 80243569 1 * 4 80243569 rs1458038
400 chr4 102969823 102969823 1 * 4 102969823 rs10006327
401 chr4 110778529 110778529 1 * 4 110778529 rs67249485
402 chr4 113527500 113527500 1 * 4 113527500 rs6829664
403 chr4 173720033 173720033 1 * 4 173720033 rs12648245
404 chr5 114401365 114401365 1 * 5 114401365 rs337705
405 chr5 138084300 138084300 1 * 5 138084300 rs2040862
406 chr15 63811578 63811578 1 * 15 63811578 rs7170477
407 chr15 73384923 73384923 1 * 15 73384923 rs74022964
408 chr16 1953015 1953015 1 * 16 1953015 rs140185678
409 chr17 1406556 1406556 1 * 17 1406556 rs7225165
410 chr17 7549660 7549660 1 * 17 7549660 rs9899183
411 chr17 39874911 39874911 1 * 17 39874911 rs11658278
412 chr17 46797087 46797087 1 * 17 46797087 rs1563304
413 chr17 78777556 78777556 1 * 17 78777556 rs12604076
414 chr18 51182178 51182178 1 * 18 51182178 rs8088085
415 chr10 101306718 101306718 1 * 10 101306718 rs144361223
416 chr12 111803962 111803962 1 * 12 111803962 rs671
417 chr1 203059583 203059583 1 * 1 203059583 rs4590732
418 chr4 110789946 110789946 1 * 4 110789946 rs4540107
419 chr1 10329982 10329982 1 * 1 10329982 rs551033057
420 chr1 111908825 111908825 1 * 1 111908825 rs2120436
421 chr1 115768197 115768197 1 * 1 115768197 rs4484922
422 chr1 154873058 154873058 1 * 1 154873058 rs11264278
423 chr2 178549906 178549906 1 * 2 178549906 rs890578
424 chr2 200306468 200306468 1 * 2 200306468 rs10931898
425 chr2 61138961 61138961 1 * 2 61138961 rs148785604
426 chr2 65056838 65056838 1 * 2 65056838 rs74181299
427 chr2 69918585 69918585 1 * 2 69918585 rs6546558
428 chr14 72894562 72894562 1 * 14 72894562 rs3814864
429 chr15 73375705 73375705 1 * 15 73375705 rs7178084
430 chr17 39910014 39910014 1 * 17 39910014 rs1008723
431 chr19 50399948 50399948 1 * 19 50399948 rs181513970
432 chr22 18114652 18114652 1 * 22 18114652 rs362021
433 chrX 119698761 119698761 1 * X 119698761 rs77806999
434 chrX 138333934 138333934 1 * X 138333934 rs2129742
435 chr8 21946224 21946224 1 * 8 21946224 rs7846485
436 chr8 76948760 76948760 1 * 8 76948760 rs113304312
437 chr10 63229171 63229171 1 * 10 63229171 rs7916868
438 chr10 67504839 67504839 1 * 10 67504839 rs10823051
439 chr11 128898062 128898062 1 * 11 128898062 rs78907918
440 chr11 14014033 14014033 1 * 11 14014033 rs7116230
441 chr12 111730205 111730205 1 * 12 111730205 rs11066015
442 chr12 124016178 124016178 1 * 12 124016178 rs556992087
443 chr12 24609567 24609567 1 * 12 24609567 rs11047527
444 chr12 32837485 32837485 1 * 12 32837485 rs34791177
445 chr12 56709370 56709370 1 * 12 56709370 rs7978685
446 chr12 69675839 69675839 1 * 12 69675839 rs710719
447 chr13 22792608 22792608 1 * 13 22792608 rs9510344
448 chr14 23392602 23392602 1 * 14 23392602 rs365990
449 chr14 32453874 32453874 1 * 14 32453874 rs8011444
450 chr3 179452706 179452706 1 * 3 179452706 rs4855075
451 chr3 69350572 69350572 1 * 3 69350572 rs9310148
452 chr5 114423288 114423288 1 * 5 114423288 rs337684
453 chr5 123120403 123120403 1 * 5 123120403 rs17149944
454 chr5 138070140 138070140 1 * 5 138070140 rs141654122
455 chr5 173247874 173247874 1 * 5 173247874 rs6874428
456 chr6 117208687 117208687 1 * 6 117208687 rs11153653
457 chr6 118370282 118370282 1 * 6 118370282 rs77710920
458 chr6 122068760 122068760 1 * 6 122068760 rs868155
459 chr6 16413394 16413394 1 * 6 16413394 rs7770062
460 chr6 36678191 36678191 1 * 6 36678191 rs730506
461 chr6 87258847 87258847 1 * 6 87258847 rs9362415
462 chr8 123533862 123533862 1 * 8 123533862 rs78332318
463 chr8 140677101 140677101 1 * 8 140677101 rs13268718
464 chr8 17939376 17939376 1 * 8 17939376 rs139743358
465 chr3 38736063 38736063 1 * 3 38736063 rs10428132
466 chr3 179441371 179441371 1 * 3 179441371 rs75880040
467 chr4 102994461 102994461 1 * 4 102994461 rs3960788
468 chr4 148031831 148031831 1 * 4 148031831 rs6839459
469 chr4 173721638 173721638 1 * 4 173721638 rs74500426
470 chr6 87112623 87112623 1 * 6 87112623 rs13210074
471 chr6 118244502 118244502 1 * 6 118244502 rs4946333
472 chr7 28368690 28368690 1 * 7 28368690 rs6948592
473 chr17 78776206 78776206 1 * 17 78776206 rs7224711
474 chr10 63320967 63320967 1 * 10 63320967 rs10822156
475 chr11 121774297 121774297 1 * 11 121774297 rs2156664
476 chr14 23418974 23418974 1 * 14 23418974 rs28631169
477 chr14 32514611 32514611 1 * 14 32514611 rs7140396
478 chr17 12709614 12709614 1 * 17 12709614 rs55941572
479 chr2 144977379 144977379 1 * 2 144977379 rs12621647
480 chr4 110743002 110743002 1 * 4 110743002 rs17042098
481 chr5 138029106 138029106 1 * 5 138029106 rs17171711
482 chr5 173237160 173237160 1 * 5 173237160 rs6882776
483 chr6 75478614 75478614 1 * 6 75478614 rs12211255
484 chr7 150954728 150954728 1 * 7 150954728 rs2269001
485 chr10 73660422 73660422 1 * 10 73660422 rs7915134
486 chr10 76175587 76175587 1 * 10 76175587 rs11001667
487 chr15 98727906 98727906 1 * 15 98727906 rs6598541
488 chr17 46789236 46789236 1 * 17 46789236 rs199497
489 chr2 65052671 65052671 1 * 2 65052671 rs2723064
490 chr2 126679788 126679788 1 * 2 126679788 rs113949548
491 chr2 200304035 200304035 1 * 2 200304035 rs56326533
492 chr2 212395133 212395133 1 * 2 212395133 rs6738011
493 chr3 12800724 12800724 1 * 3 12800724 rs4642101
494 chr1 11792459 11792459 1 * 1 11792459 rs17375901
495 chr4 110787131 110787131 1 * 4 110787131 rs17042171
496 chr1 154841877 154841877 1 * 1 154841877 rs13376333
497 chr20 47796832 47796832 1 * 20 47796832 rs13038095
498 chr11 123009573 123009573 1 * 11 123009573 rs12420422
499 chr12 3060327 3060327 1 * 12 3060327 rs12310617
500 chr2 9956965 9956965 1 * 2 9956965 rs16867253
501 chr2 146120964 146120964 1 * 2 146120964 rs222826
502 chr14 92945686 92945686 1 * 14 92945686 rs4905014
503 chr3 123019460 123019460 1 * 3 123019460 rs7632505
504 chr16 72963084 72963084 1 * 16 72963084 rs7190256
505 chr17 7718146 7718146 1 * 17 7718146 rs3803802
506 chr7 19177581 19177581 1 * 7 19177581 rs17140821
507 chr18 8522684 8522684 1 * 18 8522684 rs8082812
508 chr9 22125348 22125348 1 * 9 22125348 rs1333048
509 chr21 41463567 41463567 1 * 21 41463567 rs460976
510 chr10 26969741 26969741 1 * 10 26969741 rs7081476
511 chr10 112996282 112996282 1 * 10 112996282 rs4506565
512 chr1 154841792 154841792 1 * 1 154841792 rs6666258
513 chr7 116546187 116546187 1 * 7 116546187 rs3807989
514 chr14 64214130 64214130 1 * 14 64214130 rs1152591
515 chr15 73359833 73359833 1 * 15 73359833 rs7164883
516 chr19 19296909 19296909 1 * 19 19296909 rs10401969
517 chr19 44919689 44919689 1 * 19 44919689 rs4420638
518 chr19 44744370 44744370 1 * 19 44744370 rs4803750
519 chr1 109275684 109275684 1 * 1 109275684 rs629301
520 chr2 21065449 21065449 1 * 2 21065449 rs562338
521 chr2 21176344 21176344 1 * 2 21176344 rs478442
522 chr2 27263727 27263727 1 * 2 27263727 rs6759518
523 chr2 27412596 27412596 1 * 2 27412596 rs1728918
524 chr2 27518370 27518370 1 * 2 27518370 rs780094
525 chr2 215086907 215086907 1 * 2 215086907 rs940274
526 chr4 102363708 102363708 1 * 4 102363708 rs13114738
527 chr4 110810780 110810780 1 * 4 110810780 rs6533530
528 chr4 139829967 139829967 1 * 4 139829967 rs1869717
529 chr5 75329662 75329662 1 * 5 75329662 rs7703051
530 chr5 75463358 75463358 1 * 5 75463358 rs4704221
531 chr5 75584065 75584065 1 * 5 75584065 rs5744680
532 chr5 75701931 75701931 1 * 5 75701931 rs10057967
533 chr7 73462836 73462836 1 * 7 73462836 rs2074755
534 chr7 73637727 73637727 1 * 7 73637727 rs799165
535 chr11 61803311 61803311 1 * 11 61803311 rs174547
536 chr11 116778201 116778201 1 * 11 116778201 rs964184
537 chr11 117037567 117037567 1 * 11 117037567 rs7115242
538 chr12 89656726 89656726 1 * 12 89656726 rs12579302
539 chr12 122479003 122479003 1 * 12 122479003 rs12369179
540 chr15 58435126 58435126 1 * 15 58435126 rs261332
541 chr16 53786615 53786615 1 * 16 53786615 rs9939609
542 chr16 56956804 56956804 1 * 16 56956804 rs247617
543 chr8 20008763 20008763 1 * 8 20008763 rs765547
544 chr8 125466108 125466108 1 * 8 125466108 rs2980853
545 chr9 22125504 22125504 1 * 9 22125504 rs1333049
546 chr20 41147406 41147406 1 * 20 41147406 rs760762
547 chr20 41322165 41322165 1 * 20 41322165 rs2866611
548 chr4 110789386 110789386 1 * 4 110789386 rs61303432
549 chr7 116519907 116519907 1 * 7 116519907 rs2109514
550 chr11 128894676 128894676 1 * 11 128894676 rs75190942
551 chr15 57351688 57351688 1 * 15 57351688 rs2921421
552 chr1 170622169 170622169 1 * 1 170622169 rs651386
553 chr4 110791276 110791276 1 * 4 110791276 rs2129977
554 chr6 122142045 122142045 1 * 6 122142045 rs12664873
555 chr9 94730238 94730238 1 * 9 94730238 rs7026071
556 chr15 73376665 73376665 1 * 15 73376665 rs7183206
557 chr4 110767596 110767596 1 * 4 110767596 rs2723334
558 chr10 73661890 73661890 1 * 10 73661890 rs7394190
559 chr10 103562124 103562124 1 * 10 103562124 rs60848348
560 chr16 73025260 73025260 1 * 16 73025260 rs4499262
561 chr2 69811100 69811100 1 * 2 69811100 rs6546550
562 chr12 32820006 32820006 1 * 12 32820006 rs1454934
563 chr1 154845927 154845927 1 * 1 154845927 rs36004974
564 chr5 114412874 114412874 1 * 5 114412874 rs337711
565 chr1 170669192 170669192 1 * 1 170669192 rs520525
566 chr7 116558774 116558774 1 * 7 116558774 rs1997572
567 chr1 170216500 170216500 1 * 1 170216500 rs10800507
568 chr2 69749252 69749252 1 * 2 69749252 rs62133983
569 chr5 137912251 137912251 1 * 5 137912251 rs6864727
570 chr6 118252898 118252898 1 * 6 118252898 rs281868
571 chr17 46969002 46969002 1 * 17 46969002 rs76774446
572 chr10 63556040 63556040 1 * 10 63556040 rs7919685
573 chr13 22797335 22797335 1 * 13 22797335 rs7987944
574 chr17 7531723 7531723 1 * 17 7531723 rs8073937
575 chr14 76961126 76961126 1 * 14 76961126 rs8181996
576 chr11 121758299 121758299 1 * 11 121758299 rs949078
577 chr1 205716224 205716224 1 * 1 205716224 rs951366
578 chr13 22799267 22799267 1 * 13 22799267 rs9580438
579 chr17 7516977 7516977 1 * 17 7516977 rs9675122
580 chr6 34272799 34272799 1 * 6 34272799 rs1307274
581 chr4 110796991 110796991 1 * 4 110796991 rs13105878
582 chr6 122070990 122070990 1 * 6 122070990 rs13191450
583 chr4 110733185 110733185 1 * 4 110733185 rs143269342
584 chr1 111919280 111919280 1 * 1 111919280 rs1443926
585 chr15 63512308 63512308 1 * 15 63512308 rs146311723
586 chr4 110859850 110859850 1 * 4 110859850 rs149829837
587 chr6 118245024 118245024 1 * 6 118245024 rs17079881
588 chr5 143270839 143270839 1 * 5 143270839 rs174048
589 chr3 111869032 111869032 1 * 3 111869032 rs17490701
590 chr7 116514132 116514132 1 * 7 116514132 rs17516287
591 chr4 110815726 110815726 1 * 4 110815726 rs17570669
592 chr11 19988967 19988967 1 * 11 19988967 rs1822273
593 chr1 10107367 10107367 1 * 1 10107367 rs187585530
594 chr6 117559179 117559179 1 * 6 117559179 rs210632
595 chr2 200330879 200330879 1 * 2 200330879 rs295114
596 chr16 1955981 1955981 1 * 16 1955981 rs30252
597 chr3 66361431 66361431 1 * 3 66361431 rs332388
598 chr1 154839924 154839924 1 * 1 154839924 rs34292822
599 chr5 138098483 138098483 1 * 5 138098483 rs34750263
600 chr8 124847575 124847575 1 * 8 124847575 rs35006907
601 chr12 69703684 69703684 1 * 12 69703684 rs35349325
602 chr2 178556567 178556567 1 * 2 178556567 rs35504893
603 chr12 123962792 123962792 1 * 12 123962792 rs3789967
604 chr4 10117121 10117121 1 * 4 10117121 rs3822259
605 chr17 70351197 70351197 1 * 17 70351197 rs3844438
606 chr8 140736225 140736225 1 * 8 140736225 rs4355822
607 chr9 94886305 94886305 1 * 9 94886305 rs4385527
608 chr7 28373568 28373568 1 * 7 28373568 rs6462078
609 chr10 73660356 73660356 1 * 10 73660356 rs6480708
610 chr2 69884579 69884579 1 * 2 69884579 rs6546553
611 chr2 61541610 61541610 1 * 2 61541610 rs6742276
612 chr3 12799435 12799435 1 * 3 12799435 rs6810325
613 chr4 110775495 110775495 1 * 4 110775495 rs6847935
614 chr6 87146285 87146285 1 * 6 87146285 rs6907805
615 chr8 140752560 140752560 1 * 8 140752560 rs6993266
616 chr5 114400719 114400719 1 * 5 114400719 rs716845
617 chr17 70341044 70341044 1 * 17 70341044 rs7219869
618 chr20 62560732 62560732 1 * 20 62560732 rs7269123
619 chr22 18117816 18117816 1 * 22 18117816 rs465276
620 chr9 106870072 106870072 1 * 9 106870072 rs4743034
621 chr3 179450674 179450674 1 * 3 179450674 rs4855074
622 chr1 205748695 205748695 1 * 1 205748695 rs4951261
623 chr1 170665943 170665943 1 * 1 170665943 rs503706
624 chr1 170648165 170648165 1 * 1 170648165 rs608930
625 chr15 63507814 63507814 1 * 15 63507814 rs62011291
626 chr7 107215557 107215557 1 * 7 107215557 rs62483627
627 chr3 111873991 111873991 1 * 3 111873991 rs73228543
628 chr8 134800173 134800173 1 * 8 134800173 rs7460121
629 chr7 74696373 74696373 1 * 7 74696373 rs74910854
630 chr4 110737238 110737238 1 * 4 110737238 rs75021220
631 chr6 36677811 36677811 1 * 6 36677811 rs762624
632 chr3 89485227 89485227 1 * 3 89485227 rs7632427
633 chr3 196767831 196767831 1 * 3 196767831 rs9872035
634 chr2 69889883 69889883 1 * 2 69889883 rs10165883
635 chr10 101845957 101845957 1 * 10 101845957 rs1044258
636 chr7 92655809 92655809 1 * 7 92655809 rs11773884
637 chr9 124415987 124415987 1 * 9 124415987 rs10760361
638 chr1 154451288 154451288 1 * 1 154451288 rs12129500
639 chr10 102230055 102230055 1 * 10 102230055 rs10786662
640 chr14 76960368 76960368 1 * 14 76960368 rs10873299
641 chr12 75830037 75830037 1 * 12 75830037 rs11180703
642 chr4 110735436 110735436 1 * 4 110735436 rs112599895
643 chr20 6591367 6591367 1 * 20 6591367 rs2145274
644 chr14 32512278 32512278 1 * 14 32512278 rs2145587
645 chr16 1964282 1964282 1 * 16 1964282 rs2286466
646 chr3 66384219 66384219 1 * 3 66384219 rs2306272
647 chr2 61548229 61548229 1 * 2 61548229 rs2441380
648 chr4 110631977 110631977 1 * 4 110631977 rs2595104
649 chr11 19988805 19988805 1 * 11 19988805 rs2625322
650 chr4 148025539 148025539 1 * 4 148025539 rs10027347
651 chr7 836590 836590 1 * 7 836590 rs11768850
652 chr5 138052751 138052751 1 * 5 138052751 rs10479177
653 chr14 34717488 34717488 1 * 14 34717488 rs11846704
654 chr1 170224718 170224718 1 * 1 170224718 rs12122060
655 chr1 170724397 170724397 1 * 1 170724397 rs12142379
656 chr6 133153164 133153164 1 * 6 133153164 rs12208899
657 chr12 123934127 123934127 1 * 12 123934127 rs12298484
658 chr15 70161800 70161800 1 * 15 70161800 rs12591736
659 chr12 114653212 114653212 1 * 12 114653212 rs12810346
660 chr15 98744146 98744146 1 * 15 98744146 rs12908437
661 chr2 148035096 148035096 1 * 2 148035096 rs12992412
662 chr4 110783043 110783043 1 * 4 110783043 rs2129981
663 chr10 116816095 116816095 1 * 10 116816095 rs740363
664 chr6 160589086 160589086 1 * 6 160589086 rs10455872
665 chr4 45180510 45180510 1 * 4 45180510 rs10938397
666 chr18 23567545 23567545 1 * 18 23567545 rs1652348
667 chr18 60067625 60067625 1 * 18 60067625 rs7234864
668 chr16 53765595 53765595 1 * 16 53765595 rs9937053
669 chr12 42859612 42859612 1 * 12 42859612 rs1520832
670 chr2 126905321 126905321 1 * 2 126905321 rs13418717
671 chr9 18109237 18109237 1 * 9 18109237 rs2210327
672 chr12 29951209 29951209 1 * 12 29951209 rs2046383
673 chr12 91911494 91911494 1 * 12 91911494 rs17019682
674 chr15 63445726 63445726 1 * 15 63445726 rs10519210
675 chr7 27290437 27290437 1 * 7 27290437 rs13225783
676 chr9 27533986 27533986 1 * 9 27533986 rs10812610
677 chr13 75202132 75202132 1 * 13 75202132 rs548097
678 chr19 3159771 3159771 1 * 19 3159771 rs11880198
679 chr12 58865846 58865846 1 * 12 58865846 rs11172782
680 chr8 82756885 82756885 1 * 8 82756885 rs6473383
681 chr10 89204857 89204857 1 * 10 89204857 rs11203032
682 chr11 126158822 126158822 1 * 11 126158822 rs563519
683 chr1 220855166 220855166 1 * 1 220855166 rs11118620
684 chr3 165562421 165562421 1 * 3 165562421 rs1523288
685 chr9 95085566 95085566 1 * 9 95085566 rs137908951
686 chr12 115118502 115118502 1 * 12 115118502 rs35427
687 chr4 110776497 110776497 1 * 4 110776497 rs78229461
688 chr6 22569405 22569405 1 * 6 22569405 rs2073030
689 chr6 36665292 36665292 1 * 6 36665292 rs4713999
690 chr9 133276354 133276354 1 * 9 133276354 rs600038
691 chr9 22122061 22122061 1 * 9 22122061 rs35831924
692 chr15 33904646 33904646 1 * 15 33904646 rs187108425
693 chr16 73014468 73014468 1 * 16 73014468 rs67329386
694 chr18 58252666 58252666 1 * 18 58252666 rs11660748
695 chr1 6219310 6219310 1 * 1 6219310 rs846111
696 chr2 178898903 178898903 1 * 2 178898903 rs7564756
697 chr12 111446804 111446804 1 * 12 111446804 rs3184504
698 chr17 66311864 66311864 1 * 17 66311864 rs4328478
699 chr7 128846309 128846309 1 * 7 128846309 rs34373805
700 chr12 26195496 26195496 1 * 12 26195496 rs113819537
701 chr20 33701957 33701957 1 * 20 33701957 rs57668191
702 chr14 89416793 89416793 1 * 14 89416793 rs71415423
703 chr10 119532469 119532469 1 * 10 119532469 rs148802390
704 chr18 58289633 58289633 1 * 18 58289633 rs10871753
705 chr1 15804829 15804829 1 * 1 15804829 rs113151268
706 chr2 178882341 178882341 1 * 2 178882341 rs142556838
707 chr2 178846649 178846649 1 * 2 178846649 rs2220127
708 chr3 134736952 134736952 1 * 3 134736952 rs13092177
709 chr2 71451390 71451390 1 * 2 71451390 rs4852257
710 chr10 119696417 119696417 1 * 10 119696417 rs11199073
711 chr3 14376944 14376944 1 * 3 14376944 rs34234056
712 chr1 6188122 6188122 1 * 1 6188122 rs114300540
713 chr6 32668263 32668263 1 * 6 32668263 rs9274626
714 chr3 49173299 49173299 1 * 3 49173299 rs7617480
715 chr17 45949373 45949373 1 * 17 45949373 rs242562
716 chr12 115117725 115117725 1 * 12 115117725 rs35432
717 chr17 46969002 46969002 1 * 17 46969002 rs76774446
718 chr6 118346359 118346359 1 * 6 118346359 rs11153730
719 chr3 158569666 158569666 1 * 3 158569666 rs2276773
720 chr17 1466275 1466275 1 * 17 1466275 rs8069650
721 chr10 119667597 119667597 1 * 10 119667597 rs196321
722 chr16 2103932 2103932 1 * 16 2103932 rs9938566
723 chr8 140625230 140625230 1 * 8 140625230 rs1962104
724 chr19 41439932 41439932 1 * 19 41439932 rs13346603
725 chr1 45555123 45555123 1 * 1 45555123 rs666720
726 chr2 36922355 36922355 1 * 2 36922355 rs11124554
727 chr5 139426616 139426616 1 * 5 139426616 rs11242465
728 chr7 128825592 128825592 1 * 7 128825592 rs57573379
729 chr4 16027243 16027243 1 * 4 16027243 rs1850507
730 chr15 84145450 84145450 1 * 15 84145450 rs4842937
731 chr16 940791 940791 1 * 16 940791 rs12598405
732 chr17 55297249 55297249 1 * 17 55297249 rs12452367
733 chr6 54163271 54163271 1 * 6 54163271 rs6915002
734 chr19 45812551 45812551 1 * 19 45812551 rs10421891
735 chr1 236688982 236688982 1 * 1 236688982 rs12724121
736 chr2 200315300 200315300 1 * 2 200315300 rs3820888
737 chr15 84806000 84806000 1 * 15 84806000 rs35630683
738 chr8 124847608 124847608 1 * 8 124847608 rs34866937
739 chr22 23836092 23836092 1 * 22 23836092 rs5760061
740 chr16 53794154 53794154 1 * 16 53794154 rs17817964
741 chr6 36677811 36677811 1 * 6 36677811 rs762624
742 chr17 1370588 1370588 1 * 17 1370588 rs117510670
743 chr2 178975161 178975161 1 * 2 178975161 rs10497529
744 chr2 178888822 178888822 1 * 2 178888822 rs1873164
745 chr10 119611816 119611816 1 * 10 119611816 rs11594596
746 chr3 14250179 14250179 1 * 3 14250179 rs11710541
747 chr10 73657491 73657491 1 * 10 73657491 rs4746140
748 chr3 14232793 14232793 1 * 3 14232793 rs56281979
749 chr1 16021917 16021917 1 * 1 16021917 rs945425
750 chr2 178649706 178649706 1 * 2 178649706 rs2562845
751 chr4 110787848 110787848 1 * 4 110787848 rs1906592
752 chr10 119656173 119656173 1 * 10 119656173 rs72840788
753 chr11 43607199 43607199 1 * 11 43607199 rs4755720
754 chr6 22598030 22598030 1 * 6 22598030 rs7766436
755 chr2 632592 632592 1 * 2 632592 rs12992672
756 chr12 124824136 124824136 1 * 12 124824136 rs10846742
757 chr4 113463172 113463172 1 * 4 113463172 rs17620390
758 chr1 50281325 50281325 1 * 1 50281325 rs72688573
759 chr4 45184122 45184122 1 * 4 45184122 rs10938398
760 chr7 75470858 75470858 1 * 7 75470858 rs6945340
761 chr2 144500878 144500878 1 * 2 144500878 rs7564469
762 chr12 106865692 106865692 1 * 12 106865692 rs7977247
763 chr2 59078490 59078490 1 * 2 59078490 rs1016287
764 chr14 29700781 29700781 1 * 14 29700781 rs959388
765 chr4 102291689 102291689 1 * 4 102291689 rs233806
766 chr2 37006122 37006122 1 * 2 37006122 rs17038861
767 chr6 79075890 79075890 1 * 6 79075890 rs9352691
768 chr19 45824573 45824573 1 * 19 45824573 rs10520390
769 chr1 66524036 66524036 1 * 1 66524036 rs79682748
770 chr9 22102166 22102166 1 * 9 22102166 rs7859727
771 chr4 110748064 110748064 1 * 4 110748064 rs2634071
772 chr16 53768582 53768582 1 * 16 53768582 rs11642015
773 chr6 36679512 36679512 1 * 6 36679512 rs3176326
774 chr1 109278889 109278889 1 * 1 109278889 rs602633
775 chr1 16004613 16004613 1 * 1 16004613 rs1739833
776 chr10 119667372 119667372 1 * 10 119667372 rs17617337
777 chr10 73647154 73647154 1 * 10 73647154 rs34163229
778 chr17 67840105 67840105 1 * 17 67840105 rs113437066
779 chr5 137671073 137671073 1 * 5 137671073 rs11746435
780 chr21 29230673 29230673 1 * 21 29230673 rs2832275
781 chr7 74708526 74708526 1 * 7 74708526 rs7795282
782 chr16 69532406 69532406 1 * 16 69532406 rs12933292
783 chr17 2297577 2297577 1 * 17 2297577 rs216199
784 chr12 111762346 111762346 1 * 12 111762346 rs2013002
785 chr1 222632876 222632876 1 * 1 222632876 rs17163345
786 chr17 39668086 39668086 1 * 17 39668086 rs3764351
787 chr6 12903725 12903725 1 * 6 12903725 rs9349379
788 chr18 38953012 38953012 1 * 18 38953012 rs4327120
789 chr11 123009573 123009573 1 * 11 123009573 rs12420422
790 chr12 3060327 3060327 1 * 12 3060327 rs12310617
791 chr2 9956965 9956965 1 * 2 9956965 rs16867253
792 chr2 146120964 146120964 1 * 2 146120964 rs222826
793 chr14 92945686 92945686 1 * 14 92945686 rs4905014
794 chr3 123019460 123019460 1 * 3 123019460 rs7632505
795 chr16 72963084 72963084 1 * 16 72963084 rs7190256
796 chr17 7718146 7718146 1 * 17 7718146 rs3803802
797 chr7 19177581 19177581 1 * 7 19177581 rs17140821
798 chr18 8522684 8522684 1 * 18 8522684 rs8082812
799 chr9 22125348 22125348 1 * 9 22125348 rs1333048
800 chr21 41463567 41463567 1 * 21 41463567 rs460976
801 chr10 26969741 26969741 1 * 10 26969741 rs7081476
802 chr10 112996282 112996282 1 * 10 112996282 rs4506565
803 chr12 111395984 111395984 1 * 12 111395984 rs10774624
804 chr12 112172910 112172910 1 * 12 112172910 rs11066188
805 chr14 23167830 23167830 1 * 14 23167830 rs114352564
806 chr1 50509555 50509555 1 * 1 50509555 rs116626164
807 chr5 137676482 137676482 1 * 5 137676482 rs11745324
808 chr7 144116260 144116260 1 * 7 144116260 rs117540300
809 chr16 72972675 72972675 1 * 16 72972675 rs12325072
810 chr18 60099280 60099280 1 * 18 60099280 rs1539952
811 chr7 75432493 75432493 1 * 7 75432493 rs6944634
812 chr10 18226070 18226070 1 * 10 18226070 rs1757223
813 chr18 23574060 23574060 1 * 18 23574060 rs1788826
814 chr4 110665822 110665822 1 * 4 110665822 rs1823290
815 chr16 53814649 53814649 1 * 16 53814649 rs1861867
816 chr1 61420374 61420374 1 * 1 61420374 rs1997997
817 chr17 2300159 2300159 1 * 17 2300159 rs216193
818 chr7 92635679 92635679 1 * 7 92635679 rs2282979
819 chr1 16021039 16021039 1 * 1 16021039 rs28579893
820 chr7 74720592 74720592 1 * 7 74720592 rs35005436
821 chr9 22025494 22025494 1 * 9 22025494 rs10738604
822 chr22 22522600 22522600 1 * 22 22522600 rs361894
823 chr22 22521228 22521228 1 * 22 22521228 rs362079
824 chr6 22571185 22571185 1 * 6 22571185 rs3734214
825 chr2 86536881 86536881 1 * 2 86536881 rs4832298
826 chr6 160584578 160584578 1 * 6 160584578 rs55730499
827 chr16 53772541 53772541 1 * 16 53772541 rs56094641
828 chr14 34878306 34878306 1 * 14 34878306 rs1712355
829 chr4 110927114 110927114 1 * 4 110927114 rs17513625
830 chr2 630075 630075 1 * 2 630075 rs73139123
831 chr2 36920832 36920832 1 * 2 36920832 rs7605601
832 chr4 110843816 110843816 1 * 4 110843816 rs7680240
833 chr11 43612095 43612095 1 * 11 43612095 rs7936836
834 chr1 51332122 51332122 1 * 1 51332122 rs80061532
835 chr6 78635532 78635532 1 * 6 78635532 rs9361413
836 chr4 110707472 110707472 1 * 4 110707472 rs981150
837 chr17 78802073 78802073 1 * 17 78802073 rs2306527
838 chr18 33675954 33675954 1 * 18 33675954 rs34728432
839 chr12 104992867 104992867 1 * 12 104992867 rs4331189
840 chr12 104959466 104959466 1 * 12 104959466 rs4075503
841 chr5 2655665 2655665 1 * 5 2655665 rs16870234
842 chr5 103642776 103642776 1 * 5 103642776 rs75087282
843 chr12 107654295 107654295 1 * 12 107654295 rs28548659
844 chr4 11262289 11262289 1 * 4 11262289 rs782760
845 chr3 32484661 32484661 1 * 3 32484661 rs367841
846 chr20 52069476 52069476 1 * 20 52069476 rs6013374
847 chr19 57376380 57376380 1 * 19 57376380 rs189508091
848 chr12 29535269 29535269 1 * 12 29535269 rs299453
849 chr12 104806310 104806310 1 * 12 104806310 rs9737956
850 chr3 175704057 175704057 1 * 3 175704057 rs6773175
851 chr6 36799290 36799290 1 * 6 36799290 rs9470398
852 chr18 7165714 7165714 1 * 18 7165714 rs75262741
853 chr18 7165736 7165736 1 * 18 7165736 rs147545594
854 chr2 225227882 225227882 1 * 2 225227882 rs189536067
855 chr7 6501383 6501383 1 * 7 6501383 rs73059342
856 chr7 6508129 6508129 1 * 7 6508129 rs556723179
857 chr15 75879549 75879549 1 * 15 75879549 rs76806081
858 chr12 75895517 75895517 1 * 12 75895517 rs114782882
859 chr16 50121093 50121093 1 * 16 50121093 rs552214848
860 chr16 87929642 87929642 1 * 16 87929642 rs139731147
861 chr12 89965597 89965597 1 * 12 89965597 rs113983785
862 chr6 15880941 15880941 1 * 6 15880941 rs116116894
863 chr22 46417046 46417046 1 * 22 46417046 rs190258023
864 chr10 77152423 77152423 1 * 10 77152423 rs79087352
865 chr8 63615955 63615955 1 * 8 63615955 rs187251765
866 chr5 170374105 170374105 1 * 5 170374105 rs144322502
867 chr12 119704045 119704045 1 * 12 119704045 rs371848093
868 chr5 166124695 166124695 1 * 5 166124695 rs114101629
869 chr1 226505234 226505234 1 * 1 226505234 rs143554223
870 chr16 13710372 13710372 1 * 16 13710372 rs28523422
871 chr1 18784033 18784033 1 * 1 18784033 rs74056620
872 chr1 18784068 18784068 1 * 1 18784068 rs74056621
873 chr1 18783514 18783514 1 * 1 18783514 rs113459855
874 chr12 75899702 75899702 1 * 12 75899702 rs115146744
875 chr1 226518546 226518546 1 * 1 226518546 rs148467525
876 chr1 18783980 18783980 1 * 1 18783980 rs74056619
877 chr1 18784160 18784160 1 * 1 18784160 rs74056622
878 chr4 114106683 114106683 1 * 4 114106683 rs115982993
879 chr11 118548722 118548722 1 * 11 118548722 rs111657631
880 chr3 189563329 189563329 1 * 3 189563329 rs189566544
881 chr11 121940094 121940094 1 * 11 121940094 rs143694932
882 chr5 166138903 166138903 1 * 5 166138903 rs75729550
883 chr20 59333413 59333413 1 * 20 59333413 rs138005219
884 chr3 189573162 189573162 1 * 3 189573162 rs144563425
885 chr12 84365999 84365999 1 * 12 84365999 rs146219909
886 chr18 7162907 7162907 1 * 18 7162907 rs74972015
887 chr2 225229677 225229677 1 * 2 225229677 rs111641830
888 chr2 225229816 225229816 1 * 2 225229816 rs112372754
889 chr7 6499355 6499355 1 * 7 6499355 rs142659860
890 chr11 824293 824293 1 * 11 824293 rs114512805
891 chr16 24501229 24501229 1 * 16 24501229 rs116598880
892 chr19 32170310 32170310 1 * 19 32170310 rs76302892
893 chr12 89962714 89962714 1 * 12 89962714 rs113516553
894 chr12 89966409 89966409 1 * 12 89966409 rs111371067
895 chr12 89967845 89967845 1 * 12 89967845 rs138517179
896 chr13 73906571 73906571 1 * 13 73906571 rs146264611
897 chr6 16264087 16264087 1 * 6 16264087 rs149649230
898 chr2 4101751 4101751 1 * 2 4101751 rs112901026
899 chr22 46417215 46417215 1 * 22 46417215 rs148416395
900 chr18 7165316 7165316 1 * 18 7165316 rs76345468
901 chr14 24328255 24328255 1 * 14 24328255 rs2092866
902 chr12 75900959 75900959 1 * 12 75900959 rs149765481
903 chr6 22177692 22177692 1 * 6 22177692 rs182178320
904 chr7 47398239 47398239 1 * 7 47398239 rs192154334
905 chr19 32137461 32137461 1 * 19 32137461 rs115709306
906 chr19 32143298 32143298 1 * 19 32143298 rs78705027
907 chr19 32152628 32152628 1 * 19 32152628 rs116175387
908 chr2 172769257 172769257 1 * 2 172769257 rs115472750
909 chr16 87973047 87973047 1 * 16 87973047 rs116213227
910 chr22 46422493 46422493 1 * 22 46422493 rs535263906
911 chr6 14453908 14453908 1 * 6 14453908 rs149447933
912 chr16 87971983 87971983 1 * 16 87971983 rs114908471
913 chr5 141806037 141806037 1 * 5 141806037 rs17097649
914 chr5 141809067 141809067 1 * 5 141809067 rs17097676
915 chr5 101495996 101495996 1 * 5 101495996 rs113510721
916 chr5 101496433 101496433 1 * 5 101496433 rs28806579
917 chr5 166089843 166089843 1 * 5 166089843 rs114821210
918 chr1 165408879 165408879 1 * 1 165408879 rs78093250
919 chr16 24584678 24584678 1 * 16 24584678 rs148133894
920 chr3 134436825 134436825 1 * 3 134436825 rs189919070
921 chr1 18790006 18790006 1 * 1 18790006 rs74056624
922 chr13 113804983 113804983 1 * 13 113804983 rs56032548
923 chr1 18783262 18783262 1 * 1 18783262 rs188344082
924 chr22 46423108 46423108 1 * 22 46423108 rs150381023
925 chr22 46429532 46429532 1 * 22 46429532 rs150109621
926 chr6 14411553 14411553 1 * 6 14411553 rs139130723
927 chr6 14420151 14420151 1 * 6 14420151 rs142803096
928 chr18 48509413 48509413 1 * 18 48509413 rs144303414
929 chr22 49158345 49158345 1 * 22 49158345 rs6009185
930 chr5 31695670 31695670 1 * 5 31695670 rs372344
931 chr7 101886632 101886632 1 * 7 101886632 rs10234809
932 chr7 123038013 123038013 1 * 7 123038013 rs111681691
933 chr12 18903336 18903336 1 * 12 18903336 rs8181669
934 chr12 18903960 18903960 1 * 12 18903960 rs1490716
935 chr16 76851168 76851168 1 * 16 76851168 rs34141129
936 chr10 11818334 11818334 1 * 10 11818334 rs58829444
937 chr16 13889638 13889638 1 * 16 13889638 rs13338660
938 chr16 13894865 13894865 1 * 16 13894865 rs9924452
939 chr16 13894782 13894782 1 * 16 13894782 rs7184192
940 chr1 62981186 62981186 1 * 1 62981186 rs72671743
941 chr21 27242552 27242552 1 * 21 27242552 rs1477717
942 chr16 13892870 13892870 1 * 16 13892870 rs1364363
943 chr5 31694898 31694898 1 * 5 31694898 rs1678921
944 chr16 13891137 13891137 1 * 16 13891137 rs10163219
945 chr16 13892198 13892198 1 * 16 13892198 rs9927170
946 chr3 196256232 196256232 1 * 3 196256232 rs56107869
947 chr3 196256235 196256235 1 * 3 196256235 rs56297497
948 chr8 95439207 95439207 1 * 8 95439207 rs74864598
949 chr8 95439600 95439600 1 * 8 95439600 rs16917667
950 chr19 32103916 32103916 1 * 19 32103916 rs8105292
951 chr1 184396836 184396836 1 * 1 184396836 rs61823501
952 chr10 59510886 59510886 1 * 10 59510886 rs11006544
953 chr12 99694540 99694540 1 * 12 99694540 rs11110004
954 chr1 236396997 236396997 1 * 1 236396997 rs78133413
955 chr1 224153647 224153647 1 * 1 224153647 rs113737900
956 chr5 30869242 30869242 1 * 5 30869242 rs77506079
957 chr12 62675917 62675917 1 * 12 62675917 rs76392993
958 chr6 129963201 129963201 1 * 6 129963201 rs17757727
959 chr21 42637597 42637597 1 * 21 42637597 rs139489372
960 chr5 121264302 121264302 1 * 5 121264302 rs79031501
961 chr5 121265711 121265711 1 * 5 121265711 rs965460
962 chr5 121270537 121270537 1 * 5 121270537 rs114726259
963 chr7 104595243 104595243 1 * 7 104595243 rs143054558
964 chr8 108747025 108747025 1 * 8 108747025 rs62509389
965 chr8 108762441 108762441 1 * 8 108762441 rs62509394
966 chr7 104670969 104670969 1 * 7 104670969 rs190116644
967 chr7 4549001 4549001 1 * 7 4549001 rs11766034
968 chr16 13893862 13893862 1 * 16 13893862 rs6498482
969 chr16 50120769 50120769 1 * 16 50120769 rs79272715
970 chr8 95440624 95440624 1 * 8 95440624 rs1392797
971 chr8 95455121 95455121 1 * 8 95455121 rs78897914
972 chr8 95457559 95457559 1 * 8 95457559 rs16917715
973 chr8 95454820 95454820 1 * 8 95454820 rs116454494
974 chr16 13895264 13895264 1 * 16 13895264 rs7188980
975 chr16 78933297 78933297 1 * 16 78933297 rs7198756
976 chr1 121213648 121213648 1 * 1 121213648 rs587606498
977 chr22 27571691 27571691 1 * 22 27571691 rs5752592
978 chr22 27568401 27568401 1 * 22 27568401 rs28580426
979 chr4 38234363 38234363 1 * 4 38234363 rs78829380
980 chr21 14119015 14119015 1 * 21 14119015 rs57346421
981 chr21 14120037 14120037 1 * 21 14120037 rs55798126
982 chr21 14124936 14124936 1 * 21 14124936 rs56337324
983 chr21 14126271 14126271 1 * 21 14126271 rs78528733
984 chr21 14131214 14131214 1 * 21 14131214 rs73894141
985 chr21 14131694 14131694 1 * 21 14131694 rs73894142
986 chr18 79553190 79553190 1 * 18 79553190 rs188748322
987 chr16 87967762 87967762 1 * 16 87967762 rs114700275
988 chr5 30425422 30425422 1 * 5 30425422 rs541284506
989 chr5 33083283 33083283 1 * 5 33083283 rs112434206
990 chr1 165408366 165408366 1 * 1 165408366 rs116521297
991 chr1 18784584 18784584 1 * 1 18784584 rs74056623
992 chr16 87949887 87949887 1 * 16 87949887 rs138575291
993 chr5 166127270 166127270 1 * 5 166127270 rs74956835
994 chr13 113804866 113804866 1 * 13 113804866 rs77095672
995 chr16 87925065 87925065 1 * 16 87925065 rs149322277
996 chr16 720886 720886 1 * 16 720886 rs76064792
997 chr4 22625658 22625658 1 * 4 22625658 rs112577387
998 chr4 22630338 22630338 1 * 4 22630338 rs73123536
999 chr12 75962050 75962050 1 * 12 75962050 rs7965830
1000 chr13 27021678 27021678 1 * 13 27021678 rs61945053
1001 chr7 6163445 6163445 1 * 7 6163445 rs78314028
1002 chr11 98834502 98834502 1 * 11 98834502 rs12362161
1003 chr14 31849939 31849939 1 * 14 31849939 rs113235453
1004 chr2 23527771 23527771 1 * 2 23527771 rs1709294
1005 chr5 8543925 8543925 1 * 5 8543925 rs1700575
1006 chr6 42088268 42088268 1 * 6 42088268 rs79661299
1007 chr8 3620814 3620814 1 * 8 3620814 rs1600857
1008 chr8 21741725 21741725 1 * 8 21741725 rs112455636
1009 chr3 109782466 109782466 1 * 3 109782466 rs664669
1010 chr10 77684995 77684995 1 * 10 77684995 rs4979906
1011 chr3 32447042 32447042 1 * 3 32447042 rs12638540
1012 chr19 14240762 14240762 1 * 19 14240762 rs4528684
1013 chr4 175937875 175937875 1 * 4 175937875 rs7687921
1014 chr14 90213566 90213566 1 * 14 90213566 rs8017423
1015 chr12 131378358 131378358 1 * 12 131378358 rs7965445
1016 chr15 31537504 31537504 1 * 15 31537504 rs2125623
1017 chr11 12447850 12447850 1 * 11 12447850 rs7120489
1018 chr5 33636489 33636489 1 * 5 33636489 rs6868223
1019 chr1 221378197 221378197 1 * 1 221378197 rs12733856
1020 chr7 112446278 112446278 1 * 7 112446278 rs17159640
1021 chr19 19296909 19296909 1 * 19 19296909 rs10401969
1022 chr19 44919689 44919689 1 * 19 44919689 rs4420638
1023 chr19 44744370 44744370 1 * 19 44744370 rs4803750
1024 chr1 109275684 109275684 1 * 1 109275684 rs629301
1025 chr2 21065449 21065449 1 * 2 21065449 rs562338
1026 chr2 21176344 21176344 1 * 2 21176344 rs478442
1027 chr2 27263727 27263727 1 * 2 27263727 rs6759518
1028 chr2 27412596 27412596 1 * 2 27412596 rs1728918
1029 chr2 27518370 27518370 1 * 2 27518370 rs780094
1030 chr2 215086907 215086907 1 * 2 215086907 rs940274
1031 chr4 102363708 102363708 1 * 4 102363708 rs13114738
1032 chr4 110810780 110810780 1 * 4 110810780 rs6533530
1033 chr4 139829967 139829967 1 * 4 139829967 rs1869717
1034 chr5 75329662 75329662 1 * 5 75329662 rs7703051
1035 chr5 75463358 75463358 1 * 5 75463358 rs4704221
1036 chr5 75584065 75584065 1 * 5 75584065 rs5744680
1037 chr5 75701931 75701931 1 * 5 75701931 rs10057967
1038 chr7 73462836 73462836 1 * 7 73462836 rs2074755
1039 chr7 73637727 73637727 1 * 7 73637727 rs799165
1040 chr11 61803311 61803311 1 * 11 61803311 rs174547
1041 chr11 116778201 116778201 1 * 11 116778201 rs964184
1042 chr11 117037567 117037567 1 * 11 117037567 rs7115242
1043 chr12 89656726 89656726 1 * 12 89656726 rs12579302
1044 chr12 122479003 122479003 1 * 12 122479003 rs12369179
1045 chr15 58435126 58435126 1 * 15 58435126 rs261332
1046 chr16 53786615 53786615 1 * 16 53786615 rs9939609
1047 chr16 56956804 56956804 1 * 16 56956804 rs247617
1048 chr8 20008763 20008763 1 * 8 20008763 rs765547
1049 chr8 125466108 125466108 1 * 8 125466108 rs2980853
1050 chr9 22125504 22125504 1 * 9 22125504 rs1333049
1051 chr20 41147406 41147406 1 * 20 41147406 rs760762
1052 chr20 41322165 41322165 1 * 20 41322165 rs2866611
1053 chr1 109275216 109275216 1 * 1 109275216 rs660240
1054 chr4 110747470 110747470 1 * 4 110747470 rs17042102
1055 chr6 36679903 36679903 1 * 6 36679903 rs4135240
1056 chr6 160591981 160591981 1 * 6 160591981 rs140570886
1057 chr9 22100177 22100177 1 * 9 22100177 rs1556516
1058 chr12 111466567 111466567 1 * 12 111466567 rs4766578
1059 chr5 110840429 110840429 1 * 5 110840429 rs9885413
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1059 HF rtracklayer::export.bed(Short_gwas_gr,"data/Final_four_data/ARR_HF_SNP_local.bed", index=TRUE)Here I am doing the overlapping of the previous ranges of SNPs and the full ATAC peak set. I also later create the data frames from the reheat data, the reheat data using the p<0.005 top genes, the cluster names associated with each peak, and the list of TE/notTE associated with each peak.
ATAC_peaks_gr <- Collapsed_new_peaks %>% GRanges()
Peaks_cutoff <- read_delim("data/Final_four_data/LCPM_matrix_ff.txt",delim = "/") %>% dplyr::select(Peakid)
gwas_short_list <- gwas_peak_check %>% as.data.frame %>% dplyr::filter(Peakid %in%Peaks_cutoff$Peakid)
gwas_10k_list <- gwas_peak_check_10k %>% distinct(SNPS,Peakid)%>% dplyr::filter(Peakid %in%Peaks_cutoff$Peakid)
gwas_20k_list <- gwas_peak_check_20k %>% distinct(SNPS,Peakid)%>% dplyr::filter(Peakid %in%Peaks_cutoff$Peakid)
gwas_50k_list <- gwas_peak_check_50k %>% distinct(SNPS,Peakid)%>% dplyr::filter(Peakid %in%Peaks_cutoff$Peakid)
Reheat_data <- read_excel("data/other_papers/jah36123-sup-0002-tables2.xlsx")
top_reheat <- Reheat_data %>%
dplyr::filter(fisher_pvalue<0.005)
Nine_te_df <- readRDS("data/Final_four_data/Nine_group_TE_df.RDS")
###needed to change TE status to at least 1 bp overlap
match <- Nine_te_df %>%
mutate(TEstatus=if_else(!is.na(per_ol),"TE_peak","not_TE_peak")) %>%
distinct(Peakid,TEstatus,mrc,.keep_all = TRUE) Peaks within 5kb +/- RNA TSS, gwas range +/- 10 kb
To break down what I am doing here: I start with the list of peaks that overlap a gwas SNP that has been expanded by 20kb. I then only add the RNA expressed genes associated with the peaks that are within +/- 5 kb of its TSS. I join the median LFC data frames for ATAC and RNA at 3 and 24 hours, the TEstatus, the reheat status and exclude any SNP-Peak combinations that do not have RNA assigned. (This effectively is filtering out peaks outside of the 10kb TSS range That would make the list drop from 2019 to 298 rows)
gwas_df <-gwas_20k_list%>%
as.data.frame() %>%
left_join(., peak_10kb_neargenes, by=c("Peakid"="Peakid")) %>%
left_join(., (ATAC_3_lfc %>%
dplyr::select(peak,med_3h_lfc)),by=c("Peakid"="peak")) %>%
left_join(., (ATAC_24_lfc %>%
dplyr::select(peak,med_24h_lfc)),by=c("Peakid"="peak"))%>%
left_join(., RNA_median_3_lfc,by =c("NCBI_gene"="ENTREZID", "SYMBOL"="SYMBOL")) %>%
left_join(., RNA_median_24_lfc,by =c("NCBI_gene"="ENTREZID", "SYMBOL"="SYMBOL")) %>%
mutate(reheat=if_else(SYMBOL %in% Reheat_data$gene,"reheat_gene","not_reheat_gene")) %>%
distinct(SNPS,Peakid,.keep_all = TRUE) %>%
tidyr::unite(name,SNPS,SYMBOL,Peakid,sep ="_",remove=FALSE) %>%
left_join(.,(match %>%
group_by(Peakid) %>%
filter(!(TEstatus=="not_TE_peak" & any (TEstatus == "TE_peak"))) %>%
ungroup() %>%
distinct(TEstatus,Peakid,.keep_all = TRUE)),
by = c("Peakid"="Peakid")) %>%
mutate(dist_to_SNP=case_when(Peakid %in% gwas_short_list$Peakid &SNPS %in% gwas_short_list$SNPS~ 0,
Peakid %in% gwas_10k_list$Peakid &SNPS %in% gwas_10k_list$SNPS~ 10,
Peakid %in% gwas_20k_list$Peakid &SNPS %in% gwas_20k_list$SNPS~ 20,
Peakid %in% gwas_50k_list$Peakid &SNPS %in% gwas_50k_list$SNPS ~ 50)) %>%
group_by(SNPS,Peakid) %>%
summarize(name=unique(name),
med_3h_lfc=unique(med_3h_lfc),
med_24h_lfc=unique(med_24h_lfc),
RNA_3h_lfc=unique(RNA_3h_lfc),
RNA_24h_lfc=unique(RNA_24h_lfc),
repClass=paste(unique(repClass),collapse=":"),
TEstatus=paste(unique(TEstatus),collapse=";"),
SYMBOL=paste(unique(SYMBOL),collapse=";"),
reheat=paste(unique(reheat),collapse=";"),
mrc=unique(mrc),
dist_to_SNP=min(dist_to_SNP)) %>%
na.omit(RNA_3h_lfc)
gwas_mat <- gwas_df %>%
ungroup() %>%
dplyr::select(name,med_3h_lfc:RNA_24h_lfc) %>%
column_to_rownames("name") %>%
as.matrix()
gwas_name_mat <- gwas_df %>%
ungroup() %>%
dplyr::select(name,TEstatus,mrc,reheat,dist_to_SNP)
row_anno <- ComplexHeatmap::rowAnnotation(TE_status=gwas_name_mat$TEstatus,reheat_status=gwas_name_mat$reheat,MRC=gwas_name_mat$mrc,direct_overlap=gwas_name_mat$dist_to_SNP,col= list(TE_status=c("TE_peak"="goldenrod",
"TE_peak;not_TE_peak"="goldenrod",
"not_TE_peak;TE_peak"="goldenrod",
"not_TE_peak"="lightblue"), MRC = c("EAR_open" = "#F8766D", "EAR_close" = "#f6483c","ESR_open" = "#7CAE00",
"ESR_close" = "#587b00",
"ESR_opcl"="grey40",
"ESR_C"="grey40",
"ESR_clop"="tan",
"ESR_D"="tan",
"ESR_OC" = "#6a9500",
"LR_open" = "#00BFC4",
"LR_close" = "#008d91",
"NR" = "#C77CFF",
"not_mrc"="black"),
reheat_status=c("reheat_gene"="green","not_reheat_gene"="orange"),
direct_overlap=c("0"="red","10"="pink","20"="tan2","50"="grey8")))
mat2 <- gwas_mat
# rownames(mat2)[1] = paste(c(letters, LETTERS), collapse = "")
simply_map <- ComplexHeatmap::Heatmap(gwas_mat,
left_annotation = row_anno,
show_row_names = TRUE,
# row_names_side = "left",
row_names_max_width= max_text_width(rownames(gwas_mat), gp=gpar(fontsize=8)),
heatmap_legend_param = list(direction = "horizontal"),
show_column_names = TRUE,
cluster_rows = FALSE,
cluster_columns = FALSE)
draw(simply_map, merge_legend = TRUE, heatmap_legend_side = "bottom",
annotation_legend_side = "bottom")
| Version | Author | Date |
|---|---|---|
| d09c7db | E. Renee Matthews | 2025-01-17 |
Peaks within 5kb +/- RNA TSS, gwas range +/- 25 kb
For comparison, I went ahead and did the same this as above, but used the +/- 25 kb expanded SNP range. This left me with 660 ATAC-SNP_RNA sets.
gwas_df <-
gwas_50k_list%>%
as.data.frame() %>%
left_join(., peak_10kb_neargenes, by=c("Peakid"="Peakid")) %>%
left_join(., (ATAC_3_lfc %>%
dplyr::select(peak,med_3h_lfc)),by=c("Peakid"="peak")) %>%
left_join(., (ATAC_24_lfc %>%
dplyr::select(peak,med_24h_lfc)),by=c("Peakid"="peak"))%>%
left_join(., RNA_median_3_lfc,by =c("NCBI_gene"="ENTREZID", "SYMBOL"="SYMBOL")) %>%
left_join(., RNA_median_24_lfc,by =c("NCBI_gene"="ENTREZID", "SYMBOL"="SYMBOL")) %>%
mutate(reheat=if_else(SYMBOL %in% Reheat_data$gene,"reheat_gene","not_reheat_gene")) %>%
distinct(SNPS,Peakid,.keep_all = TRUE) %>%
tidyr::unite(name,SNPS,SYMBOL,Peakid,sep ="_",remove=FALSE) %>%
left_join(.,(match %>%
group_by(Peakid) %>%
filter(!(TEstatus=="not_TE_peak" & any (TEstatus == "TE_peak"))) %>%
ungroup() %>%
distinct(TEstatus,Peakid,.keep_all = TRUE)),
by = c("Peakid"="Peakid")) %>%
mutate(dist_to_SNP=case_when(Peakid %in% gwas_short_list$Peakid &SNPS %in% gwas_short_list$SNPS~ 0,
Peakid %in% gwas_10k_list$Peakid &SNPS %in% gwas_10k_list$SNPS~ 10,
Peakid %in% gwas_20k_list$Peakid &SNPS %in% gwas_20k_list$SNPS~ 20,
Peakid %in% gwas_50k_list$Peakid &SNPS %in% gwas_50k_list$SNPS ~ 50)) %>%
group_by(SNPS,Peakid) %>%
# mutate(Keep=case_when(SNPS))
# group_by(Peakid) %>%
summarize(name=unique(name),
# SNPS=unique(SNPS),
med_3h_lfc=unique(med_3h_lfc),
med_24h_lfc=unique(med_24h_lfc),
# AC_3h_lfc=unique(AC_3h_lfc),
# AC_24h_lfc=unique(AC_24h_lfc),
RNA_3h_lfc=unique(RNA_3h_lfc),
RNA_24h_lfc=unique(RNA_24h_lfc),
repClass=paste(unique(repClass),collapse=":"),
TEstatus=paste(unique(TEstatus),collapse=";"),
SYMBOL=paste(unique(SYMBOL),collapse=";"),
reheat=paste(unique(reheat),collapse=";"),
mrc=unique(mrc),
dist_to_SNP=min(dist_to_SNP)) %>%
na.omit(RNA_3h_lfc)
gwas_mat <- gwas_df %>%
ungroup() %>%
dplyr::select(name,med_3h_lfc:RNA_24h_lfc) %>%
column_to_rownames("name") %>%
as.matrix()
gwas_name_mat <- gwas_df %>%
ungroup() %>%
dplyr::select(name,TEstatus,mrc,reheat,dist_to_SNP)
row_anno <- ComplexHeatmap::rowAnnotation(TE_status=gwas_name_mat$TEstatus,reheat_status=gwas_name_mat$reheat,MRC=gwas_name_mat$mrc,direct_overlap=gwas_name_mat$dist_to_SNP,col= list(TE_status=c("TE_peak"="goldenrod",
"TE_peak;not_TE_peak"="goldenrod",
"not_TE_peak;TE_peak"="goldenrod",
"not_TE_peak"="lightblue"), MRC = c("EAR_open" = "#F8766D", "EAR_close" = "#f6483c","ESR_open" = "#7CAE00",
"ESR_close" = "#587b00",
"ESR_opcl"="grey40",
"ESR_C"="grey40",
"ESR_clop"="tan",
"ESR_D"="tan",
"ESR_OC" = "#6a9500",
"LR_open" = "#00BFC4",
"LR_close" = "#008d91",
"NR" = "#C77CFF",
"not_mrc"="black"),
reheat_status=c("reheat_gene"="green","not_reheat_gene"="orange"),
direct_overlap=c("0"="red","10"="pink","20"="tan2","50"="grey8")))
mat2 <- gwas_mat
# rownames(mat2)[1] = paste(c(letters, LETTERS), collapse = "")
simply_map <- ComplexHeatmap::Heatmap(gwas_mat,
left_annotation = row_anno,
show_row_names = TRUE,
# row_names_side = "left",
row_names_max_width= max_text_width(rownames(gwas_mat), gp=gpar(fontsize=8)),
heatmap_legend_param = list(direction = "horizontal"),
show_column_names = TRUE,
cluster_rows = FALSE,
cluster_columns = FALSE)
draw(simply_map, merge_legend = TRUE, heatmap_legend_side = "bottom",
annotation_legend_side = "bottom")
Peaks within +/-20 kb RNA TSS ,gwas range +/- 10 kb
warning, 702 rows below
gwas_df <-
gwas_20k_list%>%
as.data.frame() %>%
left_join(., peak_40kb_neargenes, by=c("Peakid"="Peakid")) %>%
left_join(., (ATAC_3_lfc %>%
dplyr::select(peak,med_3h_lfc)),by=c("Peakid"="peak")) %>%
left_join(., (ATAC_24_lfc %>%
dplyr::select(peak,med_24h_lfc)),by=c("Peakid"="peak"))%>%
left_join(., RNA_median_3_lfc,by =c("NCBI_gene"="ENTREZID", "SYMBOL"="SYMBOL")) %>%
left_join(., RNA_median_24_lfc,by =c("NCBI_gene"="ENTREZID", "SYMBOL"="SYMBOL")) %>%
mutate(reheat=if_else(SYMBOL %in% Reheat_data$gene,"reheat_gene","not_reheat_gene")) %>%
distinct(SNPS,Peakid,.keep_all = TRUE) %>%
tidyr::unite(name,SNPS,SYMBOL,Peakid,sep ="_",remove=FALSE) %>%
left_join(.,(match %>%
group_by(Peakid) %>%
filter(!(TEstatus=="not_TE_peak" & any (TEstatus == "TE_peak"))) %>%
ungroup() %>%
distinct(TEstatus,Peakid,.keep_all = TRUE)),
by = c("Peakid"="Peakid")) %>%
mutate(dist_to_SNP=case_when(Peakid %in% gwas_short_list$Peakid &SNPS %in% gwas_short_list$SNPS~ 0,
Peakid %in% gwas_10k_list$Peakid &SNPS %in% gwas_10k_list$SNPS~ 10,
Peakid %in% gwas_20k_list$Peakid &SNPS %in% gwas_20k_list$SNPS~ 20,
Peakid %in% gwas_50k_list$Peakid &SNPS %in% gwas_50k_list$SNPS ~ 50)) %>%
group_by(SNPS,Peakid) %>%
arrange(., Peakid) %>%
# mutate(Keep=case_when(SNPS))
# group_by(Peakid) %>%
summarize(name=unique(name),
# SNPS=unique(SNPS),
med_3h_lfc=unique(med_3h_lfc),
med_24h_lfc=unique(med_24h_lfc),
# AC_3h_lfc=unique(AC_3h_lfc),
# AC_24h_lfc=unique(AC_24h_lfc),
RNA_3h_lfc=unique(RNA_3h_lfc),
RNA_24h_lfc=unique(RNA_24h_lfc),
repClass=paste(unique(repClass),collapse=":"),
TEstatus=paste(unique(TEstatus),collapse=";"),
SYMBOL=paste(unique(SYMBOL),collapse=";"),
reheat=paste(unique(reheat),collapse=";"),
mrc=unique(mrc),
dist_to_SNP=min(dist_to_SNP)) %>%
na.omit(RNA_3h_lfc)
gwas_mat <- gwas_df %>%
ungroup() %>%
dplyr::select(name,med_3h_lfc:RNA_24h_lfc) %>%
column_to_rownames("name") %>%
as.matrix()
gwas_name_mat <- gwas_df %>%
ungroup() %>%
dplyr::select(name,TEstatus,mrc,reheat,dist_to_SNP)
row_anno <- ComplexHeatmap::rowAnnotation(TE_status=gwas_name_mat$TEstatus,reheat_status=gwas_name_mat$reheat,MRC=gwas_name_mat$mrc,direct_overlap=gwas_name_mat$dist_to_SNP,col= list(TE_status=c("TE_peak"="goldenrod",
"TE_peak;not_TE_peak"="goldenrod",
"not_TE_peak;TE_peak"="goldenrod",
"not_TE_peak"="lightblue"), MRC = c("EAR_open" = "#F8766D", "EAR_close" = "#f6483c","ESR_open" = "#7CAE00",
"ESR_close" = "#587b00",
"ESR_opcl"="grey40",
"ESR_C"="grey40",
"ESR_clop"="tan",
"ESR_D"="tan",
"ESR_OC" = "#6a9500",
"LR_open" = "#00BFC4",
"LR_close" = "#008d91",
"NR" = "#C77CFF",
"not_mrc"="black"),
reheat_status=c("reheat_gene"="green","not_reheat_gene"="orange"),
direct_overlap=c("0"="red","10"="pink","20"="tan2","50"="grey8")))
mat2 <- gwas_mat
# rownames(mat2)[1] = paste(c(letters, LETTERS), collapse = "")
simply_map <- ComplexHeatmap::Heatmap(gwas_mat,
left_annotation = row_anno,
show_row_names = TRUE,
# row_names_side = "left",
row_names_max_width= max_text_width(rownames(gwas_mat), gp=gpar(fontsize=8)),
heatmap_legend_param = list(direction = "horizontal"),
show_column_names = TRUE,
cluster_rows = FALSE,
cluster_columns = FALSE)
draw(simply_map, merge_legend = TRUE, heatmap_legend_side = "bottom",
annotation_legend_side = "bottom")
gwas short list only
To make life really easy, or the smallest set that was readable, I used only the peaks that were directly overlapping a SNP, but filtered out peaks that were more than +/- 5 kb from an expressed RNA TSS. This gave me 33 ATAC-SNP-RNA rows.
gwas_df_short <-gwas_short_list%>%
as.data.frame() %>%
left_join(., peak_10kb_neargenes, by=c("Peakid"="Peakid")) %>%
left_join(., (ATAC_3_lfc %>%
dplyr::select(peak,med_3h_lfc)),by=c("Peakid"="peak")) %>%
left_join(., (ATAC_24_lfc %>%
dplyr::select(peak,med_24h_lfc)),by=c("Peakid"="peak"))%>%
left_join(., RNA_median_3_lfc,by =c("NCBI_gene"="ENTREZID", "SYMBOL"="SYMBOL")) %>%
left_join(., RNA_median_24_lfc,by =c("NCBI_gene"="ENTREZID", "SYMBOL"="SYMBOL")) %>%
na.omit(RNA_median_24_lfc) %>%
mutate(reheat=if_else(SYMBOL %in% Reheat_data$gene,"reheat_gene","not_reheat_gene")) %>%
distinct(SNPS,Peakid,.keep_all = TRUE) %>%
tidyr::unite(name,SNPS,SYMBOL,Peakid,sep ="_",remove=FALSE) %>%
left_join(.,(match %>%
group_by(Peakid) %>%
filter(!(TEstatus=="not_TE_peak" & any (TEstatus == "TE_peak"))) %>%
ungroup() %>%
distinct(TEstatus,Peakid,.keep_all = TRUE)),
by = c("Peakid"="Peakid")) %>%
mutate(dist_to_SNP=case_when(Peakid %in% gwas_short_list$Peakid &SNPS %in% gwas_short_list$SNPS~ 0,
Peakid %in% gwas_10k_list$Peakid &SNPS %in% gwas_10k_list$SNPS~ 10,
Peakid %in% gwas_20k_list$Peakid &SNPS %in% gwas_20k_list$SNPS~ 20,
Peakid %in% gwas_50k_list$Peakid &SNPS %in% gwas_50k_list$SNPS ~ 50)) %>%
group_by(SNPS,Peakid) %>%
# mutate(Keep=case_when(SNPS))
# group_by(Peakid) %>%
summarize(name=unique(name),
# SNPS=unique(SNPS),
med_3h_lfc=unique(med_3h_lfc),
med_24h_lfc=unique(med_24h_lfc),
# AC_3h_lfc=unique(AC_3h_lfc),
# AC_24h_lfc=unique(AC_24h_lfc),
RNA_3h_lfc=unique(RNA_3h_lfc),
RNA_24h_lfc=unique(RNA_24h_lfc),
repClass=paste(unique(repClass),collapse=":"),
TEstatus=paste(unique(TEstatus),collapse=";"),
SYMBOL=paste(unique(SYMBOL),collapse=";"),
reheat=paste(unique(reheat),collapse=";"),
mrc=unique(mrc),
dist_to_SNP=min(dist_to_SNP)) %>%
arrange(., Peakid)
gwas_mat_short <- gwas_df_short %>%
ungroup() %>%
dplyr::select(name,med_3h_lfc:RNA_24h_lfc) %>%
column_to_rownames("name") %>%
as.matrix()
gwas_name_mat_short <- gwas_df_short %>%
ungroup() %>%
dplyr::select(name,TEstatus,mrc,reheat,dist_to_SNP)
row_anno_short <- ComplexHeatmap::rowAnnotation(TE_status=gwas_name_mat_short$TEstatus,reheat_status=gwas_name_mat_short$reheat,MRC=gwas_name_mat_short$mrc,direct_overlap=gwas_name_mat_short$dist_to_SNP,col= list(TE_status=c("TE_peak"="goldenrod",
"TE_peak;not_TE_peak"="goldenrod",
"not_TE_peak;TE_peak"="goldenrod",
"not_TE_peak"="lightblue"), MRC = c("EAR_open" = "#F8766D", "EAR_close" = "#f6483c","ESR_open" = "#7CAE00",
"ESR_close" = "#587b00",
"ESR_opcl"="grey40",
"ESR_C"="grey40",
"ESR_clop"="tan",
"ESR_D"="tan",
"ESR_OC" = "#6a9500",
"LR_open" = "#00BFC4",
"LR_close" = "#008d91",
"NR" = "#C77CFF",
"not_mrc"="black"),
reheat_status=c("reheat_gene"="green","not_reheat_gene"="orange"),
direct_overlap=c("0"="red","10"="pink","20"="tan2","50"="grey8")))
mat2_short <- gwas_mat_short
# rownames(mat2)[1] = paste(c(letters, LETTERS), collapse = "")
simply_map_short <- ComplexHeatmap::Heatmap(gwas_mat_short,
left_annotation = row_anno_short,
# show_row_names = TRUE,
# width = 10,
# row_names_side = "left",
row_names_max_width= max_text_width(rownames(gwas_mat_short), gp=gpar(fontsize=16)),
heatmap_legend_param = list(direction = "horizontal"),
show_column_names = TRUE,
cluster_rows = FALSE,
cluster_columns = FALSE)
draw(simply_map_short, merge_legend = TRUE, heatmap_legend_side = "bottom",
annotation_legend_side = "bottom")
mapping genes of interest:
drug_pal <- c("#8B006D","#DF707E","#F1B72B", "#3386DD","#707031","#41B333")
# K27_counts <- readRDS("data/Final_four_data/All_Raodahpeaks.RDS")
ATAC_counts <- readRDS("data/Final_four_data/x4_filtered.RDS")
RNA_counts <- readRDS("data/other_papers/Counts_RNA_ERMatthews.RDS")df_gene <- data.frame(SYMBOL=c("PSRC1","CDKN1A","CELSR2"))
df_gene <- df_gene %>%
left_join(., (RNA_median_24_lfc %>% dplyr::select(ENTREZID,SYMBOL)), by = c ("SYMBOL"="SYMBOL")) %>%
left_join(., (gwas_df_short %>% dplyr::select(SNPS,Peakid,mrc,SYMBOL)),by = c("SYMBOL"="SYMBOL"))
RNA_counts %>%
column_to_rownames("ENTREZID") %>%
cpm(., log = TRUE) %>%
as.data.frame() %>%
dplyr::filter(row.names(.) %in% df_gene$ENTREZID) %>%
mutate(ENTREZID = row.names(.)) %>%
pivot_longer(cols = !ENTREZID, names_to = "sample", values_to = "counts") %>%
left_join(., df_gene, by =c("ENTREZID"="ENTREZID")) %>%
separate("sample", into = c("trt","ind","time")) %>%
mutate(time=factor(time, levels = c("3h","24h"))) %>%
mutate(trt=factor(trt, levels= c("DOX","EPI","DNR","MTX","TRZ","VEH"))) %>%
ggplot(., aes (x = time, y=counts))+
geom_boxplot(aes(fill=trt))+
facet_wrap(~SYMBOL+Peakid, scales="free_y")+
ggtitle("RNA LFC of expressed gene")+
scale_fill_manual(values = drug_pal)+
theme_bw()+
ylab("log2 cpm RNA")
| Version | Author | Date |
|---|---|---|
| a505a0a | E. Renee Matthews | 2025-01-17 |
ATAC_counts %>%
cpm(., log = TRUE) %>%
as.data.frame() %>%
rename_with(.,~gsub(pattern = "Ind1_75", replacement = "1_",.)) %>%
rename_with(.,~gsub(pattern = "Ind2_87", replacement = "2_",.)) %>%
rename_with(.,~gsub(pattern = "Ind3_77", replacement = "3_",.)) %>%
rename_with(.,~gsub(pattern = "Ind6_71", replacement = "6_",.)) %>%
rename_with(.,~gsub( "DX" ,'DOX',.)) %>%
rename_with(.,~gsub( "DA" ,'DNR',.)) %>%
rename_with(.,~gsub( "E" ,'EPI',.)) %>%
rename_with(.,~gsub( "T" ,'TRZ',.)) %>%
rename_with(.,~gsub( "M" ,'MTX',.)) %>%
rename_with(.,~gsub( "V" ,'VEH',.)) %>%
rename_with(.,~gsub("24h","_24h",.)) %>%
rename_with(.,~gsub("3h","_3h",.)) %>%
dplyr::filter(row.names(.) %in% df_gene$Peakid) %>%
mutate(Peakid = row.names(.)) %>%
pivot_longer(cols = !Peakid, names_to = "sample", values_to = "counts") %>%
left_join(., df_gene, by =c("Peakid"="Peakid")) %>%
separate("sample", into = c("ind","trt","time")) %>%
mutate(time=factor(time, levels = c("3h","24h"))) %>%
mutate(trt=factor(trt, levels= c("DOX","EPI","DNR","MTX","TRZ","VEH"))) %>%
ggplot(., aes (x = time, y=counts))+
geom_boxplot(aes(fill=trt))+
facet_wrap(~Peakid+SYMBOL,scales="free_y")+
ggtitle(" ATAC accessibility")+
scale_fill_manual(values = drug_pal)+
theme_bw()+
ylab("log2 cpm ATAC")
| Version | Author | Date |
|---|---|---|
| a505a0a | E. Renee Matthews | 2025-01-17 |
sessionInfo()R version 4.4.2 (2024-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 26100)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.utf8
[2] LC_CTYPE=English_United States.utf8
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.utf8
time zone: America/Chicago
tzcode source: internal
attached base packages:
[1] grid stats4 stats graphics grDevices utils datasets
[8] methods base
other attached packages:
[1] readxl_1.4.3
[2] smplot2_0.2.4
[3] cowplot_1.1.3
[4] ComplexHeatmap_2.22.0
[5] ggrepel_0.9.6
[6] plyranges_1.26.0
[7] ggsignif_0.6.4
[8] genomation_1.38.0
[9] edgeR_4.4.1
[10] limma_3.62.1
[11] ggpubr_0.6.0
[12] BiocParallel_1.40.0
[13] ggVennDiagram_1.5.2
[14] scales_1.3.0
[15] VennDiagram_1.7.3
[16] futile.logger_1.4.3
[17] gridExtra_2.3
[18] ggfortify_0.4.17
[19] rtracklayer_1.66.0
[20] org.Hs.eg.db_3.20.0
[21] TxDb.Hsapiens.UCSC.hg38.knownGene_3.20.0
[22] GenomicFeatures_1.58.0
[23] AnnotationDbi_1.68.0
[24] Biobase_2.66.0
[25] GenomicRanges_1.58.0
[26] GenomeInfoDb_1.42.1
[27] IRanges_2.40.1
[28] S4Vectors_0.44.0
[29] BiocGenerics_0.52.0
[30] RColorBrewer_1.1-3
[31] broom_1.0.7
[32] kableExtra_1.4.0
[33] lubridate_1.9.4
[34] forcats_1.0.0
[35] stringr_1.5.1
[36] dplyr_1.1.4
[37] purrr_1.0.2
[38] readr_2.1.5
[39] tidyr_1.3.1
[40] tibble_3.2.1
[41] ggplot2_3.5.1
[42] tidyverse_2.0.0
[43] workflowr_1.7.1
loaded via a namespace (and not attached):
[1] later_1.4.1 BiocIO_1.16.0
[3] bitops_1.0-9 cellranger_1.1.0
[5] rpart_4.1.23 XML_3.99-0.17
[7] lifecycle_1.0.4 rstatix_0.7.2
[9] doParallel_1.0.17 rprojroot_2.0.4
[11] vroom_1.6.5 processx_3.8.4
[13] lattice_0.22-6 backports_1.5.0
[15] magrittr_2.0.3 Hmisc_5.2-1
[17] sass_0.4.9 rmarkdown_2.29
[19] jquerylib_0.1.4 yaml_2.3.10
[21] plotrix_3.8-4 httpuv_1.6.15
[23] DBI_1.2.3 abind_1.4-8
[25] zlibbioc_1.52.0 RCurl_1.98-1.16
[27] nnet_7.3-19 git2r_0.35.0
[29] circlize_0.4.16 GenomeInfoDbData_1.2.13
[31] svglite_2.1.3 codetools_0.2-20
[33] DelayedArray_0.32.0 xml2_1.3.6
[35] tidyselect_1.2.1 shape_1.4.6.1
[37] farver_2.1.2 UCSC.utils_1.2.0
[39] base64enc_0.1-3 matrixStats_1.4.1
[41] GenomicAlignments_1.42.0 jsonlite_1.8.9
[43] GetoptLong_1.0.5 Formula_1.2-5
[45] iterators_1.0.14 systemfonts_1.1.0
[47] foreach_1.5.2 tools_4.4.2
[49] Rcpp_1.0.13-1 glue_1.8.0
[51] SparseArray_1.6.0 xfun_0.49
[53] MatrixGenerics_1.18.0 withr_3.0.2
[55] formatR_1.14 fastmap_1.2.0
[57] callr_3.7.6 digest_0.6.37
[59] timechange_0.3.0 R6_2.5.1
[61] seqPattern_1.38.0 colorspace_2.1-1
[63] RSQLite_2.3.9 generics_0.1.3
[65] data.table_1.16.4 htmlwidgets_1.6.4
[67] httr_1.4.7 S4Arrays_1.6.0
[69] whisker_0.4.1 pkgconfig_2.0.3
[71] gtable_0.3.6 blob_1.2.4
[73] impute_1.80.0 XVector_0.46.0
[75] htmltools_0.5.8.1 carData_3.0-5
[77] pwr_1.3-0 clue_0.3-66
[79] png_0.1-8 knitr_1.49
[81] lambda.r_1.2.4 rstudioapi_0.17.1
[83] tzdb_0.4.0 reshape2_1.4.4
[85] rjson_0.2.23 checkmate_2.3.2
[87] curl_6.0.1 zoo_1.8-12
[89] cachem_1.1.0 GlobalOptions_0.1.2
[91] KernSmooth_2.23-24 parallel_4.4.2
[93] foreign_0.8-87 restfulr_0.0.15
[95] pillar_1.10.0 vctrs_0.6.5
[97] promises_1.3.2 car_3.1-3
[99] cluster_2.1.8 htmlTable_2.4.3
[101] evaluate_1.0.1 magick_2.8.5
[103] cli_3.6.3 locfit_1.5-9.10
[105] compiler_4.4.2 futile.options_1.0.1
[107] Rsamtools_2.22.0 rlang_1.1.4
[109] crayon_1.5.3 labeling_0.4.3
[111] ps_1.8.1 getPass_0.2-4
[113] plyr_1.8.9 fs_1.6.5
[115] stringi_1.8.4 viridisLite_0.4.2
[117] gridBase_0.4-7 munsell_0.5.1
[119] Biostrings_2.74.1 Matrix_1.7-1
[121] BSgenome_1.74.0 patchwork_1.3.0
[123] hms_1.1.3 bit64_4.5.2
[125] KEGGREST_1.46.0 statmod_1.5.0
[127] SummarizedExperiment_1.36.0 memoise_2.0.1
[129] bslib_0.8.0 bit_4.5.0.1