This updates the script to produce a more tearsheet-like output for sample set statistics. Formatting will be updated for aesthetic improvements. There are also several database options that currently pull out misleading information because of changes in sequencing methodology that will be updated to show correct information. Eventually, plot formatting will be updated as well and additional informative plots will be added.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@4988 348d0f76-0448-11de-a6fe-93d51630548a
This commit is contained in:
corin
parent
ffae7bf537
commit
6b5474a00a
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@ -1,11 +1,27 @@
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##put titles/rownames left
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##make titles blue
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##decrease margins below titles
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## put row names in black
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##put background rows in.
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##change layouts so that it looks better
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##get sample numbers in correctly
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.libPaths('~/Sting/R/') #but make sure this is universal
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#put use scripts here
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suppressMessages(library(gplots));
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suppressMessages(library(ReadImages));
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suppressMessages(library(gsalib));
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suppressMessages(library(ROracle));
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cmdargs = getargs(
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cmdargs = gsa.getargs(
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list(
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bamlist = list(value=NA, doc="list of BAM files"),
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evalroot = list(value=NA, doc="VariantEval root"),
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statsout = list(value=NA, doc="Output path for stats"),
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tearxsout = list(value=NA, doc="Output path for tearsheet PDF"),
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plotout = list(value=NA, doc="Output path for PDF")
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),
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doc="Creates a tearsheet"
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@ -54,156 +70,187 @@ dproj = d[which(squid_fclanes %in% fclanes),];
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d2proj = d2[which(d2$"Project" %in% unique(dproj$"Project") & d2$"Sample" %in% dproj$"External ID"),];
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#}
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## Tear sheet components
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tearsheetdrop <- "tearsheetdrop.jpg" #put the path to the tearsheet backdrop here
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# Project summary
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projects = paste(unique(dproj$"Project"), collapse=", ");
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cat(sprintf("Project Summary (%s)\n", projects), file=cmdargs$statsout, append=FALSE);
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tearsheet<-function(){
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pdf(file= cmdargs$statsout, width=22, height=15, pagecentre=TRUE, pointsize=24)
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#define layout
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layout(matrix(c(1,1,2,4,3,5), ncol=2, nrow=3, byrow=TRUE), heights=c(1, 2.5,2.5), respect=FALSE)
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#prep for title bar
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full<-strsplit(cmdargs$evalroot, "/")
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name<-strsplit(full[[1]][length(full[[1]])], ".",fixed=TRUE)[[1]][1]
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title=paste(name, ": TEAR SHEET", sep="")
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drop<-read.jpeg(system.file(tearsheetdrop, package="gsalib"))
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#plot title bar
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par(mar=c(0,0,0,0))
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plot(drop)
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text(110, 45, title, family="serif", adj=c(0,0), cex=3, col=gray(.25))
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used_samples = length(unique(dproj$"External ID"));
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cat(sprintf("\tUsed samples: %s\n", used_samples), file=cmdargs$statsout, append=TRUE);
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# Project summary
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projects = paste(unique(dproj$"Project"), collapse=", ");
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unused_samples = 0;
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cat(sprintf("\tUnused samples: %s\n", unused_samples), file=cmdargs$statsout, append=TRUE);
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used_samples = length(unique(dproj$"External ID"));
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sequencing_protocol = "Hybrid selection";
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cat(sprintf("\tSequencing protocol: %s\n", sequencing_protocol), file=cmdargs$statsout, append=TRUE);
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unused_samples = 0;
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bait_design = paste(unique(dproj$"Bait Set"), collapse=", ");
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cat(sprintf("\tBait design: %s\n", bait_design), file=cmdargs$statsout, append=TRUE);
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sequencing_protocol = "Hybrid selection"; #can this be extracted?
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callable_target = paste(unique(dproj$"Target Territory"), collapse=", ");
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cat(sprintf("\tCallable target: %s\n", callable_target), file=cmdargs$statsout, append=TRUE);
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bait_design = paste(unique(dproj$"Bait Set"), collapse=", ");
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# Bases summary per lane
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cat("\nBases summary (excluding unused lanes/samples)\n", file=cmdargs$statsout, append=TRUE);
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callable_target = paste(unique(dproj$"Target Territory"), collapse=", ");
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cat("\tBases summary per lane\n", file=cmdargs$statsout, append=TRUE);
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table1<-rbind(paste(used_samples," used samples/", unused_samples + used_samples," total samples", sep=""), sequencing_protocol, bait_design, callable_target)
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print(nrow(table1))
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rownames(table1)<-c("Samples","Sequencing Protocol", "Bait Design","Callable Target")
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par(mar=c(4,4,4,4))
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textplot(table1, col.rownames="darkblue", show.colnames=FALSE, cex=1.25)
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title(main=sprintf("Project Summary (%s)\n", projects), family="sans", cex.main=1.75)
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reads_per_lane_mean = mean(dproj$"PF Reads (HS)");
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reads_per_lane_sd = sd(dproj$"PF Reads (HS)");
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cat(sprintf("\t\tReads: %s +/- %s\n", reads_per_lane_mean, reads_per_lane_sd), file=cmdargs$statsout, append=TRUE);
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# Bases summary
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used_bases_per_lane_mean = mean(dproj$"PF HQ Aligned Q20 Bases");
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used_bases_per_lane_sd = sd(dproj$"PF HQ Aligned Q20 Bases");
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cat(sprintf("\t\tUsed bases: %s +/- %s\n", used_bases_per_lane_mean, used_bases_per_lane_sd), file=cmdargs$statsout, append=TRUE);
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reads_per_lane_mean = signif(mean(dproj$"PF Reads (HS)"), 3);
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reads_per_lane_sd = signif(sd(dproj$"PF Reads (HS)"), 3);
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lanes<-sprintf("%s +/- %s\n", reads_per_lane_mean, reads_per_lane_sd)
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target_coverage_mean = mean(na.omit(dproj$"Mean Target Coverage"));
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target_coverage_sd = sd(na.omit(dproj$"Mean Target Coverage"));
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cat(sprintf("\t\tTarget coverage: %0.2fx +/- %0.2fx\n", target_coverage_mean, target_coverage_sd), file=cmdargs$statsout, append=TRUE);
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used_bases_per_lane_mean = signif(mean(dproj$"PF HQ Aligned Q20 Bases"), 3);
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used_bases_per_lane_sd = signif(sd(dproj$"PF HQ Aligned Q20 Bases"), 3);
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lanes<-c(lanes, sprintf("%s +/- %s\n", used_bases_per_lane_mean, used_bases_per_lane_sd));
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pct_loci_gt_10x_mean = mean(na.omit(dproj$"Target Bases 10x %"));
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pct_loci_gt_10x_sd = sd(na.omit(dproj$"Target Bases 10x %"));
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cat(sprintf("\t\t%% loci > 10x covered: %0.2f%% +/- %0.2f%%\n", pct_loci_gt_10x_mean, pct_loci_gt_10x_sd), file=cmdargs$statsout, append=TRUE);
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target_coverage_mean = mean(na.omit(dproj$"Mean Target Coverage"));
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target_coverage_sd = sd(na.omit(dproj$"Mean Target Coverage"));
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lanes<-c(lanes, sprintf("%0.2fx +/- %0.2fx\n", target_coverage_mean, target_coverage_sd));
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pct_loci_gt_20x_mean = mean(na.omit(dproj$"Target Bases 20x %"));
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pct_loci_gt_20x_sd = sd(na.omit(dproj$"Target Bases 20x %"));
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cat(sprintf("\t\t%% loci > 20x covered: %0.2f%% +/- %0.2f%%\n", pct_loci_gt_20x_mean, pct_loci_gt_20x_sd), file=cmdargs$statsout, append=TRUE);
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pct_loci_gt_10x_mean = mean(na.omit(dproj$"Target Bases 10x %"));
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pct_loci_gt_10x_sd = sd(na.omit(dproj$"Target Bases 10x %"));
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lanes<-c(lanes, sprintf("%0.2f%% +/- %0.2f%%\n", pct_loci_gt_10x_mean, pct_loci_gt_10x_sd));
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pct_loci_gt_30x_mean = mean(na.omit(dproj$"Target Bases 30x %"));
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pct_loci_gt_30x_sd = sd(na.omit(dproj$"Target Bases 30x %"));
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cat(sprintf("\t\t%% loci > 30x covered: %0.2f%% +/- %0.2f%%\n", pct_loci_gt_30x_mean, pct_loci_gt_30x_sd), file=cmdargs$statsout, append=TRUE);
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pct_loci_gt_20x_mean = mean(na.omit(dproj$"Target Bases 20x %"));
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pct_loci_gt_20x_sd = sd(na.omit(dproj$"Target Bases 20x %"));
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lanes<-c(lanes,sprintf("%0.2f%% +/- %0.2f%%\n", pct_loci_gt_20x_mean, pct_loci_gt_20x_sd));
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pct_loci_gt_30x_mean = mean(na.omit(dproj$"Target Bases 30x %"));
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pct_loci_gt_30x_sd = sd(na.omit(dproj$"Target Bases 30x %"));
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lanes<-c(lanes,sprintf("%0.2f%% +/- %0.2f%%\n", pct_loci_gt_30x_mean, pct_loci_gt_30x_sd));
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cat("\tBases summary per sample\n", file=cmdargs$statsout, append=TRUE);
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reads_per_sample_mean = signif(mean(d2proj$"PF Reads"), 3);
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reads_per_sample_sd = signif(sd(d2proj$"PF Reads"), 3);
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samps<-sprintf("%s +/- %s\n", reads_per_sample_mean, reads_per_sample_sd);
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reads_per_sample_mean = mean(d2proj$"PF Reads");
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reads_per_sample_sd = sd(d2proj$"PF Reads");
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cat(sprintf("\t\tReads: %s +/- %s\n", reads_per_sample_mean, reads_per_sample_sd), file=cmdargs$statsout, append=TRUE);
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used_bases_per_sample_mean = signif(mean(d2proj$"PF HQ Aligned Q20 Bases"), 3);
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used_bases_per_sample_sd = signif(sd(d2proj$"PF HQ Aligned Q20 Bases"), 3);
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samps<-c(samps, sprintf("%s +/- %s\n", used_bases_per_sample_mean, used_bases_per_sample_sd));
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used_bases_per_sample_mean = mean(d2proj$"PF HQ Aligned Q20 Bases");
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used_bases_per_sample_sd = sd(d2proj$"PF HQ Aligned Q20 Bases");
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cat(sprintf("\t\tUsed bases: %s +/- %s\n", used_bases_per_sample_mean, used_bases_per_sample_sd), file=cmdargs$statsout, append=TRUE);
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target_coverage_mean = mean(na.omit(d2proj$"Mean Target Coverage"));
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target_coverage_sd = sd(na.omit(d2proj$"Mean Target Coverage"));
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samps<-c(samps, sprintf("%0.2fx +/- %0.2fx\n", target_coverage_mean, target_coverage_sd));
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target_coverage_mean = mean(na.omit(d2proj$"Mean Target Coverage"));
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target_coverage_sd = sd(na.omit(d2proj$"Mean Target Coverage"));
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cat(sprintf("\t\tTarget coverage: %0.2fx +/- %0.2fx\n", target_coverage_mean, target_coverage_sd), file=cmdargs$statsout, append=TRUE);
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pct_loci_gt_10x_mean = mean(na.omit(d2proj$"Target Bases 10x %"));
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pct_loci_gt_10x_sd = sd(na.omit(d2proj$"Target Bases 10x %"));
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samps<-c(samps, sprintf("%0.2f%% +/- %0.2f%%\n", pct_loci_gt_10x_mean, pct_loci_gt_10x_sd));
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pct_loci_gt_10x_mean = mean(na.omit(d2proj$"Target Bases 10x %"));
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pct_loci_gt_10x_sd = sd(na.omit(d2proj$"Target Bases 10x %"));
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cat(sprintf("\t\t%% loci > 10x covered: %0.2f%% +/- %0.2f%%\n", pct_loci_gt_10x_mean, pct_loci_gt_10x_sd), file=cmdargs$statsout, append=TRUE);
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pct_loci_gt_20x_mean = mean(na.omit(d2proj$"Target Bases 20x %"));
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pct_loci_gt_20x_sd = sd(na.omit(d2proj$"Target Bases 20x %"));
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samps<-c(samps, sprintf("%0.2f%% +/- %0.2f%%\n", pct_loci_gt_20x_mean, pct_loci_gt_20x_sd));
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pct_loci_gt_20x_mean = mean(na.omit(d2proj$"Target Bases 20x %"));
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pct_loci_gt_20x_sd = sd(na.omit(d2proj$"Target Bases 20x %"));
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cat(sprintf("\t\t%% loci > 20x covered: %0.2f%% +/- %0.2f%%\n", pct_loci_gt_20x_mean, pct_loci_gt_20x_sd), file=cmdargs$statsout, append=TRUE);
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pct_loci_gt_30x_mean = mean(na.omit(d2proj$"Target Bases 30x %"));
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pct_loci_gt_30x_sd = sd(na.omit(d2proj$"Target Bases 30x %"));
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samps<-c(samps, sprintf("%0.2f%% +/- %0.2f%%\n", pct_loci_gt_30x_mean, pct_loci_gt_30x_sd));
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pct_loci_gt_30x_mean = mean(na.omit(d2proj$"Target Bases 30x %"));
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pct_loci_gt_30x_sd = sd(na.omit(d2proj$"Target Bases 30x %"));
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cat(sprintf("\t\t%% loci > 30x covered: %0.2f%% +/- %0.2f%%\n", pct_loci_gt_30x_mean, pct_loci_gt_30x_sd), file=cmdargs$statsout, append=TRUE);
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table2<-cbind(lanes, samps)
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colnames(table2)<-c("Per lane", "Per sample")
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print(nrow(table2))
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# Sequencing summary
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rownames(table2)<-c("Reads", "Used bases", "Average target coverage", "% loci covered to 10x", "% loci covered to 20x","% loci covered to 30x")
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par(mar=c(4,4,4,4))
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textplot(table2, rmar=1, col.rownames="dark blue", cex=1.25)
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title(main="Bases Summary", family="sans", cex.main=1.75)
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cat("\nSequencing summary\n", file=cmdargs$statsout, append=TRUE);
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instrument = "Illumina GA2";
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cat(sprintf("\tSequencer: %s\n", instrument), file=cmdargs$statsout, append=TRUE);
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used_lanes = nrow(dproj);
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cat(sprintf("\tUsed lanes: %s\n", used_lanes), file=cmdargs$statsout, append=TRUE);
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# Sequencing summary
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unused_lanes_by_sequencing = 0;
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unused_lanes_by_analysis = 0;
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cat(sprintf("\tUnused lanes: %s rejected by sequencing, %s by analysis\n", unused_lanes_by_sequencing, unused_lanes_by_analysis), file=cmdargs$statsout, append=TRUE);
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instrument = "Illumina GA2";#Can we get this?
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used_lanes = nrow(dproj);
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unused_lanes_by_sequencing = 0; #can we get this?
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unused_lanes_by_analysis = 0;
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lanes_per_sample_mean = mean(table(dproj$"External ID"));
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lanes_per_sample_sd = sd(table(dproj$"External ID"));
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lanes_per_sample_median = median(table(dproj$"External ID"));
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cat(sprintf("\tLanes/sample: %0.1f +/- %0.1f lanes (median=%0.1f)\n", lanes_per_sample_mean, lanes_per_sample_sd, lanes_per_sample_median), file=cmdargs$statsout, append=TRUE);
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lanes_paired = nrow(subset(dproj, dproj$"Lane Type" == "Paired"));
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lanes_widowed = nrow(subset(dproj, dproj$"Lane Type" == "Widowed"));
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lanes_single = nrow(subset(dproj, dproj$"Lane Type" == "Single"));
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cat(sprintf("\tLane parities: %s paired, %s widowed, %s single\n", lanes_paired, lanes_widowed, lanes_single), file=cmdargs$statsout, append=TRUE);
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lanes_per_sample_mean = mean(table(dproj$"External ID"));
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lanes_per_sample_sd = sd(table(dproj$"External ID"));
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lanes_per_sample_median = median(table(dproj$"External ID"));
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lanes_paired = nrow(subset(dproj, dproj$"Lane Type" == "Paired"));
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lanes_widowed = nrow(subset(dproj, dproj$"Lane Type" == "Widowed"));
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lanes_single = nrow(subset(dproj, dproj$"Lane Type" == "Single"));
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read_length_mean = mean(dproj$"Mean Read Length (P)");
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read_length_sd = sd(dproj$"Mean Read Length (P)");
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read_length_median = median(dproj$"Mean Read Length (P)");
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cat(sprintf("\tRead length: %0.1f +/- %0.1f bases (median=%0.1f)\n", read_length_mean, read_length_sd, read_length_median), file=cmdargs$statsout, append=TRUE);
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read_length_mean = mean(dproj$"Mean Read Length (P)");
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read_length_sd = sd(dproj$"Mean Read Length (P)");
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read_length_median = median(dproj$"Mean Read Length (P)");
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date = dproj$"Run Date";
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date = sub("JAN", "01", date);
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date = sub("FEB", "02", date);
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date = sub("MAR", "03", date);
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date = sub("APR", "04", date);
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date = sub("MAY", "05", date);
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date = sub("JUN", "06", date);
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date = sub("JUL", "07", date);
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date = sub("AUG", "08", date);
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date = sub("SEP", "09", date);
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date = sub("OCT", "10", date);
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date = sub("NOV", "11", date);
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date = sub("DEC", "12", date);
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date = date[order(as.Date(date, format="%d-%m-%Y"))];
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date = dproj$"Run Date";
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date = sub("JAN", "01", date);
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date = sub("FEB", "02", date);
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date = sub("MAR", "03", date);
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date = sub("APR", "04", date);
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date = sub("MAY", "05", date);
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date = sub("JUN", "06", date);
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date = sub("JUL", "07", date);
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date = sub("AUG", "08", date);
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date = sub("SEP", "09", date);
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date = sub("OCT", "10", date);
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date = sub("NOV", "11", date);
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date = sub("DEC", "12", date);
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date = date[order(as.Date(date, format="%d-%m-%Y"))];
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start_date = date[1];
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end_date = date[length(date)];
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cat(sprintf("\tSequencing dates: %s to %s\n", start_date, end_date), file=cmdargs$statsout, append=TRUE);
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start_date = date[1];
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end_date = date[length(date)];
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table3<-rbind(instrument, used_lanes, sprintf("%s rejected by sequencing, %s by analysis\n", unused_lanes_by_sequencing, unused_lanes_by_analysis), sprintf("%0.1f +/- %0.1f lanes (median=%0.1f)\n", lanes_per_sample_mean, lanes_per_sample_sd, lanes_per_sample_median), sprintf("%s paired, %s widowed, %s single\n", lanes_paired, lanes_widowed, lanes_single), sprintf("%0.1f +/- %0.1f bases (median=%0.1f)\n", read_length_mean, read_length_sd, read_length_median), sprintf("\tSequencing dates: %s to %s\n", start_date, end_date))
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print(nrow(table3))
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rownames(table3)<-c("Sequencer", "Used lanes", "Unused lanes","Used lanes/sample", "Lane pariteies", "Read legnths", "Sequencing dates")
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par(mar=c(4,4,4,4))
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textplot(table3, rmar=1, col.rownames="dark blue", show.colnames=FALSE, cex=1.25)
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title(main="Sequencing Summary", family="sans", cex.main=1.75)
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# Variant summary
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cat("\nVariant summary\n", file=cmdargs$statsout, append=TRUE);
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eval.counts = read.csv(paste(cmdargs$evalroot, ".Count_Variants.csv", sep=""), header=TRUE, comment.char="#");
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eval.counts.called = subset(eval.counts, evaluation_name == "eval" & comparison_name == "dbsnp" & jexl_expression == "none" & filter_name == "called");
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eval.counts.called.all = subset(eval.counts.called, novelty_name == "all")$nVariantLoci;
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eval.counts.called.known = subset(eval.counts.called, novelty_name == "known")$nVariantLoci;
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eval.counts.called.novel = subset(eval.counts.called, novelty_name == "novel")$nVariantLoci;
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eval.counts = read.csv(paste(cmdargs$evalroot, ".Count_Variants.csv", sep=""), header=TRUE, comment.char="#");
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eval.counts.called = subset(eval.counts, evaluation_name == "eval" & comparison_name == "dbsnp" & jexl_expression == "none" & filter_name == "called");
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eval.counts.called.all = subset(eval.counts.called, novelty_name == "all")$nVariantLoci;
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eval.counts.called.known = subset(eval.counts.called, novelty_name == "known")$nVariantLoci;
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eval.counts.called.novel = subset(eval.counts.called, novelty_name == "novel")$nVariantLoci;
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eval.titv = read.csv(paste(cmdargs$evalroot, ".Ti_slash_Tv_Variant_Evaluator.csv", sep=""), header=TRUE, comment.char="#");
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eval.titv.called = subset(eval.titv, evaluation_name == "eval" & comparison_name == "dbsnp" & jexl_expression == "none" & filter_name == "called");
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eval.titv.called.all = subset(eval.titv.called, novelty_name == "all")$ti.tv_ratio;
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eval.titv.called.known = subset(eval.titv.called, novelty_name == "known")$ti.tv_ratio;
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eval.titv.called.novel = subset(eval.titv.called, novelty_name == "novel")$ti.tv_ratio;
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|
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eval.titv = read.csv(paste(cmdargs$evalroot, ".Ti_slash_Tv_Variant_Evaluator.csv", sep=""), header=TRUE, comment.char="#");
|
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eval.titv.called = subset(eval.titv, evaluation_name == "eval" & comparison_name == "dbsnp" & jexl_expression == "none" & filter_name == "called");
|
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eval.titv.called.all = subset(eval.titv.called, novelty_name == "all")$ti.tv_ratio;
|
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eval.titv.called.known = subset(eval.titv.called, novelty_name == "known")$ti.tv_ratio;
|
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eval.titv.called.novel = subset(eval.titv.called, novelty_name == "novel")$ti.tv_ratio;
|
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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))
|
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|
||||
vars = 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);
|
||||
rownames(vars) = c("All", "Known", "Novel");
|
||||
colnames(vars) = c("Found", "Ti/Tv ratio", "Expected Ti/Tv ratio");
|
||||
rownames(table4) = c("All", "Known", "Novel");
|
||||
colnames(table4) = c("Found", "Ti/Tv ratio", "Expected Ti/Tv ratio");
|
||||
|
||||
cat(sprintf("\t\tFound\tTi/Tv ratio\tExpected Ti/Tv ratio\n"), file=cmdargs$statsout, append=TRUE);
|
||||
cat(sprintf("\tAll\t%s\t%s\t\t%s\n", eval.counts.called.all, eval.titv.called.all, "3.0 - 3.2"), file=cmdargs$statsout, append=TRUE);
|
||||
cat(sprintf("\tKnown\t%s\t%s\t\t%s\n", eval.counts.called.known, eval.titv.called.known, "3.2 - 3.4"), file=cmdargs$statsout, append=TRUE);
|
||||
cat(sprintf("\tNovel\t%s\t%s\t\t%s\n", eval.counts.called.novel, eval.titv.called.novel, "2.7 - 3.0"), file=cmdargs$statsout, append=TRUE);
|
||||
|
||||
|
||||
textplot(table4, rmar=1, col.rownames="dark blue", cex=1.25)
|
||||
title(main="Variant Summary", family="sans", cex.main=1.75)
|
||||
|
||||
dev.off()
|
||||
}
|
||||
|
||||
tearsheet()
|
||||
|
||||
# Plots
|
||||
|
||||
plots<-function(){
|
||||
eval.bysample = read.csv(paste(cmdargs$evalroot, ".SimpleMetricsBySample.csv", sep=""), header=TRUE, comment.char="#");
|
||||
eval.bysample.called = subset(eval.bysample, evaluation_name == "eval" & comparison_name == "dbsnp" & jexl_expression == "none" & filter_name == "called");
|
||||
eval.bysample.called.all = subset(eval.bysample.called, novelty_name == "all");
|
||||
|
|
@ -243,3 +290,6 @@ points(eval.func.called.novel$Synonymous[ind] / (eval.func.called.novel$Missense
|
|||
legend("topright", c("All", "Known", "Novel"), col=c("black", "blue", "red"), pt.cex=1.3, pch=21);
|
||||
|
||||
dev.off();
|
||||
}
|
||||
|
||||
plots()
|
||||
|
|
|
|||
Loading…
Reference in New Issue