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Fixing the way that lanes are pulled into from the database so that multiplexed lanes are handled and older sequence data ids are properly handled. 

git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@5123 348d0f76-0448-11de-a6fe-93d51630548a
This commit is contained in:
corin 2011-01-29 02:40:10 +00:00
parent 4ee4fd47e9
commit 4f2882c546
1 changed files with 25 additions and 20 deletions
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45
R/DataProcessingReport/GetTearsheetStats.R
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@ -25,19 +25,22 @@ cmdargs = gsa.getargs(
);
bamlist = read.table(cmdargs$bamlist);
bamlist = scan(cmdargs$bamlist, "character");
squids <- c()
fclanes = c();
for (bam in bamlist$V1) {
for (bam in bamlist) {
bamheader = system(paste("samtools view -H", bam), intern=TRUE);
squids<-c(squids, strsplit(bam, "/")[[1]][4])
if (length(bamheader) > 0) {
rgs = bamheader[grep("^@RG", bamheader)];
for (rg in rgs) {
id = grep("ID:", unlist(strsplit(rg, "\t")), value=TRUE);
id = sub("ID:", "", id);
id = grep("PU:", unlist(strsplit(rg, "\t")), value=TRUE);
id = sub("PU:", "", id);
id = gsub("A.XX......", "", id)
##change this so that it pulls out the flowcell and lane properly from old samples
##change this so that it pulls out only samples which are in the right project for new samples
fclanes = c(fclanes, id);
}
} else {
@ -63,8 +66,10 @@ oraCloseDriver(drv);
squid_fclanes = sprintf("%s.%s", d$"Flowcell", d$"Lane");
squid_fclanes = gsub("A.XX", "", squid_fclanes);
dproj = d[which(squid_fclanes %in% fclanes),];
d2proj = d2[which(d2$"Project" %in% unique(dproj$"Project") & d2$"Sample" %in% dproj$"External ID"),];
dproj = dproj[which(dproj$"Project" %in% unique(squids)),]
d2proj = d2[which(d2$"Project" %in% unique(squids) & d2$"Sample" %in% dproj$"External ID"),];
tearsheet<-function(){
@ -91,7 +96,7 @@ tearsheet<-function(){
# Project summary
projects = paste(unique(dproj$"Project"), collapse=", ");
used_samples = length(bamlist$V1);
used_samples = length(bamlist);
unused_samples = 0;
@ -107,7 +112,7 @@ tearsheet<-function(){
bait_design<-strsplit(bait_design, ".Homo")[[1]][1]
}
callable_target = paste(unique(dproj$"Target Territory"), collapse=", ");
callable_target = paste(na.omit(unique(dproj$"Target Territory")), collapse=", ");
table1<-rbind(paste(used_samples," used samples/", unused_samples + used_samples," total samples", sep=""), sequencing_protocol, bait_design, callable_target)
print(nrow(table1))
@ -117,12 +122,12 @@ tearsheet<-function(){
title(main=sprintf("Project Summary (%s)\n", projects), family="sans", cex.main=1.25, line=-1)
# Bases summary
reads_per_lane_mean = format(mean(dproj$"PF Reads (HS)"), 8, 3,1, scientific=TRUE);
reads_per_lane_sd = format(sd(dproj$"PF Reads (HS)"), 8, 3,1, scientific=TRUE);
reads_per_lane_mean = format(mean(dproj$"PF Reads (HS)", na.rm=TRUE), 8, 3,1, scientific=TRUE);
reads_per_lane_sd = format(sd(dproj$"PF Reads (HS)", na.rm=TRUE), 8, 3,1, scientific=TRUE);
lanes<-sprintf("%s +/- %s\n", reads_per_lane_mean, reads_per_lane_sd)
used_bases_per_lane_mean = format(mean(dproj$"PF HQ Aligned Q20 Bases"),8, 3,1, scientific=TRUE);
used_bases_per_lane_sd = format(sd(dproj$"PF HQ Aligned Q20 Bases"), 8, 3,1, scientific=TRUE);
used_bases_per_lane_mean = format(mean(dproj$"PF HQ Aligned Q20 Bases", na.rm=TRUE),8, 3,1, scientific=TRUE);
used_bases_per_lane_sd = format(sd(dproj$"PF HQ Aligned Q20 Bases", na.rm=TRUE), 8, 3,1, scientific=TRUE);
lanes<-c(lanes, sprintf("%s +/- %s\n", used_bases_per_lane_mean, used_bases_per_lane_sd));
target_coverage_mean = mean(na.omit(dproj$"Mean Target Coverage"));
@ -142,12 +147,12 @@ tearsheet<-function(){
lanes<-c(lanes,sprintf("%0.2f%% +/- %0.2f%%\n", pct_loci_gt_30x_mean, pct_loci_gt_30x_sd));
reads_per_sample_mean = format(mean(d2proj$"PF Reads"), 8, 3,1, scientific=TRUE);
reads_per_sample_sd = format(sd(d2proj$"PF Reads"), 8, 3,1, scientific=TRUE);
reads_per_sample_mean = format(mean(d2proj$"PF Reads", na.rm=TRUE), 8, 3,1, scientific=TRUE);
reads_per_sample_sd = format(sd(d2proj$"PF Reads",na.rm=TRUE), 8, 3,1, scientific=TRUE);
samps<-sprintf("%s +/- %s\n", reads_per_sample_mean, reads_per_sample_sd);
used_bases_per_sample_mean = format(mean(d2proj$"PF HQ Aligned Q20 Bases"),8, 3,1, scientific=TRUE);
used_bases_per_sample_sd = format(sd(d2proj$"PF HQ Aligned Q20 Bases"), 8, 3,1, scientific=TRUE);
used_bases_per_sample_mean = format(mean(d2proj$"PF HQ Aligned Q20 Bases", na.rm=TRUE),8, 3,1, scientific=TRUE);
used_bases_per_sample_sd = format(sd(d2proj$"PF HQ Aligned Q20 Bases", na.rm=TRUE), 8, 3,1, scientific=TRUE);
samps<-c(samps, sprintf("%s +/- %s\n", used_bases_per_sample_mean, used_bases_per_sample_sd));
target_coverage_mean = mean(na.omit(d2proj$"Mean Target Coverage"));
@ -195,8 +200,8 @@ tearsheet<-function(){
unused_lanes_by_analysis = 0;
lanes_per_sample_mean = mean(table(dproj$"External ID"));
lanes_per_sample_sd = sd(table(dproj$"External ID"));
lanes_per_sample_mean = mean(table(dproj$"External ID"), na.rm=TRUE);
lanes_per_sample_sd = sd(table(dproj$"External ID"), na.rm=TRUE);
lanes_per_sample_median = median(table(dproj$"External ID"));
lanes_paired = nrow(subset(dproj, dproj$"Lane Type" == "Paired"));
lanes_widowed = nrow(subset(dproj, dproj$"Lane Type" == "Widowed"));
@ -249,7 +254,7 @@ tearsheet<-function(){
table4 = matrix(c(eval.counts.called.all, eval.counts.called.known, eval.counts.called.novel, eval.titv.called.all, eval.titv.called.known, eval.titv.called.novel, "3.0 - 3.2", "3.2 - 3.4", "2.7 - 3.0"), nrow=3);
print(nrow(table4))
print(paste("columns should be three, actually are:", ncol(table4)))
rownames(table4) = c("All", "Known", "Novel");
colnames(table4) = c("Found", "Ti/Tv ratio", "Expected Ti/Tv ratio");