sashaphanes

#read MAOA and MAOB human RNAseq data and use t.test by regions
setwd("/home/mydirectory/work.dir/allen.brain/human")
maoa = read.csv("combinedA.csv")
maob = read.csv("combinedB.csv")
test.result = mapply(t.test, maoa, maob)

#store p-values by brain region:
#p.values = mapply(function(x, y) t.test(x,y)$p.value, maoa, maob)

#store p-values in a column with regions in a separate column:

sashaphanes

zcat human.Hela.ALDH.ethanol.RNAseq/features.stat/human.Hela.ALDH.ethanol.RNAseq.RPKM.limma.stat.txt.gz | head -n +4
ChrGene	D.C1	D.C3	D.E1	D.E2	D.E3	S.C1	S.C3	S.E1	S.E2	S.E3	D.C1.qNorm	D.C3.qNorm	D.E1.qNorm	D.E2.qNorm	D.E3.qNorm	S.C1.qNorm	S.C3.qNorm	S.E1.qNorm	S.E2.qNorm	S.E3.qNorm	DEvsSE.logFC	DEvsSE.AveExpr	DEvsSE.t	DEvsSE.P.Value	DEvsSE.adj.P.Val	DEvsSE.B	DEvsSE.qvalue	SEvsSC.logFCSEvsSC.AveExpr	SEvsSC.t	SEvsSC.P.Value	SEvsSC.adj.P.Val	SEvsSC.B	SEvsSC.qvalue	DEvsDC.logFC	DEvsDC.AveExpr	DEvsDC.t	DEvsDC.P.Value	DEvsDC.adj.P.Val	DEvsDC.B	DEvsDC.qvalue	DCvsSC.logFC	DCvsSC.AveExpr	DCvsSC.t	DCvsSC.P.Value	DCvsSC.adj.P.Val	DCvsSC.B	DCvsSC.qvalue
chr12.ALDH2	406.3	358.9	455.3	443	481	9.1	3.3	4.3	2.8	4.8	8.5	8.448	8.862	8.74	8.862	3.041	2.892	2.691	2.218	2.41	6.38172000660375	5.66652337604155	35.9972945401694	2.12746190437488e-12	2.34297379528806e-08	16.3325155031259	1.49547550388356e-08	-0.527099724237586	5.66652337604155	-2.65931570380224	0.0229117862569256	0.999962251464947	-4.35286289202634	0.999962251464947	

sashaphanes

>dataFile = "fileOfInterest.txt.gz"
>rawdata = read.delim(gzfile(dataFile), sep="\t", header=T)
>rownames(rawdata) = paste(rawdata[,"Chr"],  rawdata[,"GeneSym"], sep = ".")
>data.RPKM = rawdata[, grep("RPKM", colnames(rawdata))]
>rowMax = do.call("pmax", c(data.RPKM[,1:ncol(data.RPKM)],na.rm=TRUE))
>data.RPKM.rowMax.gt1 = data.RPKM[rowMax >1,]
>data.RPKM.rowMax.gt1[is.na(data.RPKM.rowMax.gt1)] = 0
>data.RPKM.log2 = log2(data.RPKM.rowMax.gt1 + 1)
>RNAseq.RPKM.log.m = as.matrix(data.RPKM.log2)
>library(limma)

sashaphanes

source("http://bioconductor.org/biocLite.R")
biocLite("preprocessCore")
library(preprocessCore)
data <- read.delim(gzfile("fileOfInterest.txt.gz"), sep="\t")
data <- data[,grep("RPKM", colnames(data))]
filtered <- data[!apply(data, 1, function(x){ all(x <2) }),]
qn <- normalize.quantiles(as.matrix(filtered), copy = TRUE)]
qn <- as.data.frame(qn)
colnames(qn) <- colnames(filtered)
rownames(qn) <- rownames(filtered)

sashaphanes

#!/usr/bin/perl -sw

while (<>) {
    foreach 
    $_ =~ s/,/\t/; 
    print "$_\n" if (eof);
}

user@localhost:~/work.dir/PerlScripts>cat ~/work.dir/Sasha/Expression\ Data/Homo_sapiens/aba_maoa/Columns.csv | perl replacer.pl
syntax error at replacer.pl line 5, near "$_ =~"

sashaphanes

#!/usr/bin/perl -s

#Q19. Write a simple perl statement to add leading 0s for the integers which is less than 10000. 
#Assume the integers are in the range of 1 to 9999.


while (<>) {
    $_ =~ s/([0-9]+)/sprintf('%05d',$1)/ge;
}

sashaphanes

#!/usr/bin/perl -sw

while (<>) {
    if(!(/^[ACGT0123NX\.]+$/)){
        print;
        next;
    }
    while(/[ACGT][0123]/){
        s/A0/AA/;s/C0/CC/;s/G0/GG/;s/T0/TT/;
        s/A1/AC/;s/C1/CA/;s/G1/GT/;s/T1/TG/;

sashaphanes

#!/usr/bin/perl -sw

# sample inputs:
#ILLUMINA-A93428   66    1     1     7848  1267  CGATGT      1      ATGTTGGCTGGCGGTGAAATAAATCTCAAACGTACCTGTTACAAAATTGTGTTAATCCTTTCAGATTCGCAG      ggggggggggggggcfdffdgggfefffffcfcffcccacBeddddded_cffefgggggBBBBBBBBBBBB      chrX.fa           122287709   R     40C21GAC7   269                                 Y

# output for sample input:
#@ILLUMINA-A93428:66:1:1:7848:1267:#CGATGT/1
#ATGTTGGCTGGCGGTGAAATAAATCTCAAACGTACCTGTTACAAAATTGTGTTAATCCTTTCAGATTCGCAG
#+ILLUMINA-A93428:66:1:1:7848:1267:#CGATGT/1
#ggggggggggggggcfdffdgggfefffffcfcffcccacBeddddded_cffefgggggBBBBBBBBBBBB

sashaphanes

#!/usr/bin/perl -s

require "getopts.pl";
   
use vars qw ($opt_f $opt_d $opt_h $opt_H);

&Getopts('f:d:hH:');
my $executable = "printUniqueStrings.pl";
$| = 1;
my $usage = qq{

sashaphanes

#This is a shellscript intended to streamline the process of checking an initial array of genes against
#1) a file storing relevant column numbers for a particular neural tissue,
#2) a file storing expression data regarding that tissue and those genes

#!/usr/bin/perl

use strict;
#use warnings;

require "getopts.pl";