Last updated: 2019-09-27
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Knit directory: Comparative_APA/analysis/
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File | Version | Author | Date | Message |
---|---|---|---|---|
Rmd | 6d96d73 | brimittleman | 2019-09-27 | add alt mapping method |
In this analysis I will look at mapping across lines.
library(tidyverse)
── Attaching packages ─────────────────────────────────────────────────────────────────────────────────────── tidyverse 1.2.1 ──
✔ ggplot2 3.1.1 ✔ purrr 0.3.2
✔ tibble 2.1.1 ✔ dplyr 0.8.0.1
✔ tidyr 0.8.3 ✔ stringr 1.3.1
✔ readr 1.3.1 ✔ forcats 0.3.0
── Conflicts ────────────────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
library(reshape2)
Attaching package: 'reshape2'
The following object is masked from 'package:tidyr':
smiths
metadata=read.table("../data/metadata_HCpanel.txt", stringsAsFactors = F, header = T)
ggplot(metadata, aes(x=Line, y=PerMap, fill=Species,by=Species)) + geom_bar(position = "dodge", stat="identity") + facet_grid(~Fraction) +theme(axis.text.x = element_text(angle = 90)) + labs(y= "Map percent", title="Pre cleaning")
ggplot(metadata, aes(x=Line, y=PerMapClean, fill=Species,by=Species)) + geom_bar(position = "dodge", stat="identity") + facet_grid(~Fraction) +theme(axis.text.x = element_text(angle = 90)) + labs(y= "Map percent", title="Post cleaning")
These are really low. I will try mapping some of the human lines to hg19 to compare to the apaQTL project.
mkdir ../Human/data/bam_hg19
mkdir ../Human/data/sort_hg19
sbatch maphg19.sh
Try with subread. (is it a star problem as well)
mkdir ../Human/data/bam_hg19_sub
mkdir ../Human/data/sort_hg19_sub
sbatch maphg19_subjunc.sh
I ended up doing this with hg38
hg19Res=read.table("../Human/data/Comphg19_hg38.txt", header = T, stringsAsFactors = F)%>% select(Line, Fraction, PerMap, HG19_mapper, subread_perc)
hg19Res$Line=as.factor(hg19Res$Line)
hg19Res_m= melt(hg19Res, id.vars = c("Line", "Fraction"))
ggplot(hg19Res_m, aes(x=Line, y=value, fill=variable)) + geom_bar(position = "dodge", stat="identity") +facet_grid(~Fraction)
Seems like the 38 genomes isnt as good in either.
sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)
Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.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] reshape2_1.4.3 forcats_0.3.0 stringr_1.3.1 dplyr_0.8.0.1
[5] purrr_0.3.2 readr_1.3.1 tidyr_0.8.3 tibble_2.1.1
[9] ggplot2_3.1.1 tidyverse_1.2.1
loaded via a namespace (and not attached):
[1] Rcpp_1.0.2 cellranger_1.1.0 pillar_1.3.1 compiler_3.5.1
[5] git2r_0.25.2 plyr_1.8.4 workflowr_1.4.0 tools_3.5.1
[9] digest_0.6.18 lubridate_1.7.4 jsonlite_1.6 evaluate_0.12
[13] nlme_3.1-137 gtable_0.2.0 lattice_0.20-38 pkgconfig_2.0.2
[17] rlang_0.4.0 cli_1.1.0 rstudioapi_0.10 yaml_2.2.0
[21] haven_1.1.2 withr_2.1.2 xml2_1.2.0 httr_1.3.1
[25] knitr_1.20 hms_0.4.2 generics_0.0.2 fs_1.3.1
[29] rprojroot_1.3-2 grid_3.5.1 tidyselect_0.2.5 glue_1.3.0
[33] R6_2.3.0 readxl_1.1.0 rmarkdown_1.10 modelr_0.1.2
[37] magrittr_1.5 whisker_0.3-2 backports_1.1.2 scales_1.0.0
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[49] broom_0.5.1 crayon_1.3.4