SNP_finemapping_results
Last updated: 2022-03-24
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Knit directory: funcFinemapping/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | 5ea9a98 | Jing Gu | 2022-03-24 | update spliceAI results |
Assess the impact of different priors on fine mapping
library(data.table)
library(dplyr)
library(susieR)
library(bigsnpr)
library(ggplot2)
source("code/make_plots.R")
source("code/run_susie.R")SpliceAI-predicted variant effects on splicing
Annotations * spliceAI predictions are not tissue-specific. * The predicted delta score of a variant can be interpreted as the probrability of the variant being splice-altering.
Procedure * Build binary annotation by denoting delta score>=0.01 as 1 and detal score < 0.01 as 0. * Run TORUS jointly over spliceAI-predictions, iPSC-derived neuronal accessibility, CADD top5% and protein coding regions. * Use the derived prior probability for each SNP to further perform fine mapping with Susie.
Torus enrichment estimates
est<-read.table("output/splicing/torus_enrichment_joint_scz_spliceAI.est", header = F, skip = 2)
colnames(est)<-c("term", "estimate", "low", "high")
snp_enrichment_plot(est, y.label = c("top5% CADD", "CDS", "iPSC-derived", "spliceAI_0.01"))
Results Summary
Plot p-values against susie PIPs 
* For an initial QC, we did not observe SNPs with high PIPs but show no significant associations for both scenarios under the assumption of one causal variant per locus. However, at L=10 we did see a substantial fractions of SNPs with high PIPs and non-sigiciant p-values for the run with functional priors.
NOTE: The following analyses were based on L=1.
Compare PIPs between uniform and functional priors 
* We observed most variants have similar low PIPs with or without functional priors. However some variants show higher PIPs with functional prior while some show higher PIPs without functional priors.
Compare the sizes of credible sets
- Uniform priors
plot_cs_size(uniform_L1) 
* Functional priors
plot_cs_size(annot_L1)
* The numbers the stacked barplot represent the numbers of independent LD blocks within each range of credible sizes. * Overall, the credible sizes are similar between the runs with or without priors
Examine the snps within credible set of size less than 20 variants
Examine a few loci
snp beta se pval zscore locus
85212 2:200715388:G:T:rs2949006 0.100117 0.0118920 3.69e-17 -8.418853 251
46595 2:57987593:T:C:rs11682175 -0.066332 0.0095085 3.05e-12 -6.976074 171
240783 8:143316970:G:A:rs13262595 0.081672 0.0096177 1.99e-17 -8.491843 935
6764 1:8423510:G:A:rs10779702 0.057891 0.0101120 1.03e-08 -5.724980 6
97703 3:2547786:G:T:rs17194490 -0.092006 0.0131910 3.06e-12 -6.974907 279
6842 1:8484228:C:T:rs159961 -0.058975 0.0102170 7.83e-09 -5.772242 6
240768 8:143312933:C:A:rs4129585 0.082041 0.0095633 9.26e-18 -8.578733 935
97650 3:2519703:G:T:rs17014863 -0.085798 0.0123130 3.21e-12 -6.968083 279
6755 1:8418644:A:C:rs11121172 0.055245 0.0102990 8.25e-08 -5.364113 6
6802 1:8452725:C:T:rs2661863 0.056569 0.0101850 2.81e-08 -5.554148 6
X_NUM_ID_ torus_pip cs cs_purity cs_size susie_pip iPSC_derived_d
85212 2883 0.00482880 1 0.9912495 2 0.93320400 1
46595 2743 0.00023381 1 0.7441588 8 0.91643760 1
240783 1392 0.00127850 1 0.8849128 3 0.77486460 1
6764 4052 0.00482880 1 0.9317116 19 0.39688087 1
97703 6588 0.00058581 1 0.7786948 17 0.30755800 0
6842 4166 0.00127850 1 0.9317116 19 0.13671204 1
240768 1373 0.00010706 1 0.8849128 3 0.13482170 0
97650 6513 0.00023381 1 0.7786948 17 0.11716620 1
6755 4043 0.00816960 1 0.9317116 19 0.09668983 0
6802 4114 0.00221670 1 0.9317116 19 0.07165940 0
CADD_d CDS_d spliceAI0.01_d_d all_d
85212 0 0 1 2
46595 0 0 0 1
240783 1 0 0 2
6764 0 0 1 2
97703 1 0 0 1
6842 1 0 0 2
240768 0 0 0 0
97650 0 0 0 1
6755 1 1 1 3
6802 0 0 1 1- Locus 251:
- top snp(2:200715388:G:T:rs2949006|zscore=8.42|spliceAI=0.01|iPSC_derived=1|pip=0.93|cs_size=2)
- Compared with the other SNP in credible set, rs2949006 has a PIP higher than 0.9 due to being annotated with having splice-altering effects.
- found in GWAS catalog
- not a GTEx splicing QTL
snp beta se pval zscore locus
85212 2:200715388:G:T:rs2949006 0.100117 0.011892 3.69e-17 -8.418853 251
85213 2:200716119:A:C:rs796364 0.099031 0.011912 9.41e-17 -8.313549 251
X_NUM_ID_ torus_pip cs cs_purity cs_size susie_pip iPSC_derived_d
85212 2883 0.00482880 1 0.9912495 2 0.93320400 1
85213 2884 0.00023381 1 0.9912495 2 0.01895903 1
CADD_d CDS_d spliceAI0.01_d_d all_d
85212 0 0 1 2
85213 0 0 0 1- Locus 6:
- top snp(1:8423510:G:A:rs10779702|zscore=5.7|spliceAI=0.02|iPSC_derived=1|pip=0.4|cs_size=19)
- not found in GWAS catalog
- annotated as a GTEx eQTL from combined analysis
snp beta se pval zscore locus
85212 2:200715388:G:T:rs2949006 0.100117 0.011892 3.69e-17 -8.418853 251
85213 2:200716119:A:C:rs796364 0.099031 0.011912 9.41e-17 -8.313549 251
X_NUM_ID_ torus_pip cs cs_purity cs_size susie_pip iPSC_derived_d
85212 2883 0.00482880 1 0.9912495 2 0.93320400 1
85213 2884 0.00023381 1 0.9912495 2 0.01895903 1
CADD_d CDS_d spliceAI0.01_d_d all_d
85212 0 0 1 2
85213 0 0 0 1Annotate fine-mapped results
Troubleshoot Torus's inflation esimation
sessionInfo()R version 4.0.4 (2021-02-15)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)
Matrix products: default
BLAS/LAPACK: /software/openblas-0.3.13-el7-x86_64/lib/libopenblas_haswellp-r0.3.13.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] RColorBrewer_1.1-2 ggplot2_3.3.3 bigsnpr_1.9.11 bigstatsr_1.5.6
[5] susieR_0.11.92 dplyr_1.0.4 data.table_1.14.2
loaded via a namespace (and not attached):
[1] Rcpp_1.0.8 lattice_0.20-41 assertthat_0.2.1 rprojroot_2.0.2
[5] digest_0.6.27 foreach_1.5.1 utf8_1.2.2 R6_2.5.1
[9] bigsparser_0.6.0 plyr_1.8.6 evaluate_0.14 highr_0.8
[13] pillar_1.5.0 flock_0.7 rlang_1.0.1 rstudioapi_0.13
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[25] munsell_0.5.0 mixsqp_0.3-43 compiler_4.0.4 httpuv_1.5.5
[29] xfun_0.21 pkgconfig_2.0.3 htmltools_0.5.1.1 tidyselect_1.1.1
[33] tibble_3.0.6 workflowr_1.6.2 codetools_0.2-18 matrixStats_0.58.0
[37] reshape_0.8.8 fansi_1.0.2 crayon_1.4.1 withr_2.4.3
[41] later_1.1.0.1 grid_4.0.4 jsonlite_1.7.2 gtable_0.3.0
[45] lifecycle_1.0.0 DBI_1.1.1 git2r_0.28.0 magrittr_2.0.1
[49] scales_1.1.1 cli_3.2.0 stringi_1.5.3 farver_2.1.0
[53] fs_1.5.0 promises_1.2.0.1 doParallel_1.0.16 bslib_0.2.4
[57] ellipsis_0.3.2 generics_0.1.0 vctrs_0.3.8 cowplot_1.1.1
[61] iterators_1.0.13 tools_4.0.4 glue_1.6.1 purrr_0.3.4
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