| Next changeset 1:ee4662eeb8c8 (2016-03-18) |
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hotspots/._.DS_Store hotspots/._Rplots.txt hotspots/._hotspots.py hotspots/._hotspots.xml hotspots/._readme.txt hotspots/._threshold_chisq.txt hotspots/Rplots.txt hotspots/hotspots.py hotspots/hotspots.xml hotspots/readme.txt hotspots/test-data/._.DS_Store hotspots/test-data/input/._.DS_Store hotspots/test-data/input/._all_classification_test.txt hotspots/test-data/input/._cis_classification_test.txt hotspots/test-data/input/._frequency.txt hotspots/test-data/input/._frequency_summary.txt hotspots/test-data/input/._sliding_frequency.txt hotspots/test-data/input/._sliding_lookup.txt hotspots/test-data/input/._trans_classification_test.txt hotspots/test-data/input/all_classification_test.txt hotspots/test-data/input/cis_classification_test.txt hotspots/test-data/input/frequency.txt hotspots/test-data/input/frequency_summary.txt hotspots/test-data/input/sliding_frequency.txt hotspots/test-data/input/sliding_lookup.txt hotspots/test-data/input/trans_classification_test.txt hotspots/test-data/output/._.DS_Store hotspots/test-data/output/._Rplots.zip hotspots/test-data/output/._all_eQTL_lists.txt hotspots/test-data/output/._all_hotspots_out.txt hotspots/test-data/output/._cis_eQTL_lists.txt hotspots/test-data/output/._cis_hotspots_out.txt hotspots/test-data/output/._full_summary.txt hotspots/test-data/output/._trans_eQTL_lists.txt hotspots/test-data/output/._trans_hotspots_out.txt hotspots/test-data/output/Rplots.zip hotspots/test-data/output/all_eQTL_lists.txt hotspots/test-data/output/all_hotspots_out.txt hotspots/test-data/output/cis_eQTL_lists.txt hotspots/test-data/output/cis_hotspots_out.txt hotspots/test-data/output/full_summary.txt hotspots/test-data/output/trans_eQTL_lists.txt hotspots/test-data/output/trans_hotspots_out.txt hotspots/threshold_chisq.txt hotspots/tool_dependencies.xml |
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| diff -r 000000000000 -r 0b383b61074d hotspots/Rplots.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/hotspots/Rplots.txt Fri Mar 18 05:26:20 2016 -0400 |
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| @@ -0,0 +1,215 @@ +#setwd("/Users/nanettecoetzer/Documents/Bioinformatics/MAIZE_project/eQTL_pipeline/April_2012_pipeline_scripts/July_2012/output_July") + +d.all <- read.table("all_hotspots_out.txt", header=T, sep="\t") +d.cis <- read.table("cis_hotspots_out.txt", header=T, sep="\t") +d.trans <- read.table("trans_hotspots_out.txt", header=T, sep="\t") + +t <- read.table("full_summary.txt", header=F, sep="\t") +thresh.all = as.numeric(paste(t[12,2])) +thresh.cis = as.numeric(paste(t[15,2])) +thresh.trans = as.numeric(paste(t[18,2])) + +chr_ends <- c() +for (i in 1:d.all[dim(d.all)[1],2]) { + k = d.all[d.all[,2]==i,] + chr_ends <- c(chr_ends,k[dim(k)[1],1]) +} +num.chr = length(chr_ends) + +prev.i = 0 +chr_ends.mid = c() +for (i in chr_ends) { + n = floor((i-prev.i)/2) + chr_ends.mid = c(chr_ends.mid,prev.i+n) + prev.i = i +} + +chrvector = c() +for (j in 1:num.chr) { + chrvector = c(chrvector,paste("chr",j,sep="")) +} + +excess.all = d.all[(d.all[,9]=='*'),] +excess.cis = d.cis[(d.cis[,9]=='*'),] +excess.trans = d.trans[(d.trans[,9]=='*'),] + +########################## all eQTL ######################### +# plot eQTL per cM --> all + +m = sort(d.all[,6],TRUE)[1] +s = sort(d.all[,6],TRUE)[2] +if (m > (s+100)) { + max_eqtl_freq = s + } +if (m <= (s+100)) { + max_eqtl_freq = m + } + +pdf("genome_wide_EcM_all.pdf",width=12) + +par(mfrow=c(1,1)) +plot(cbind(d.all[,1],d.all[,6]),type="h",ylab="eQTL per cM",main="Frequency plot",xlab="Sliding window bins (4 to 5.9 cM each)",lwd=1.5, ylim = c(-(0.03*m), m), col="black") + +lines(cbind(excess.all[,1],excess.all[,6]),col="red",type="h",lwd=1.5) + +dotted = c(0,chr_ends[1:length(chr_ends)]+0.5) +abline(h=thresh.all) +abline(v=dotted,lty="dotted",col="grey2",lwd=2) + +text(chr_ends.mid,rep(-(max_eqtl_freq*0.03),num.chr),labels=chrvector,cex=0.8) + +dev.off() + +pdf("chr_plots_EcM_all.pdf",width=12) + +if (num.chr <= 6) { + par(mfrow=c(2,3)) + } +if (num.chr>6 & num.chr<=9) { + par(mfrow=c(3,3)) + } +if (num.chr>9 & num.chr<=12) { + par(mfrow=c(3,4)) + } +if (num.chr>12 & num.chr<=15) { + par(mfrow=c(3,5)) + } +if (num.chr>15 & num.chr<=20) { + par(mfrow=c(4,5)) + } +prev_k <- 0 +#m = max_eqtl_freq +for (k in chr_ends) { + nr = which(k == chr_ends) + plot(cbind(d.all[(prev_k+1):k,1],d.all[(prev_k+1):k,6]),type="l",ylab="eQTL per cM",main=paste("Chr ",nr),xlab="Sliding window bins",lwd=1.5, ylim = c(-(0.03*s), s), col="black") + dotted = c(prev_k,k+1) + abline(h=thresh.all) + abline(v=dotted,lty="dotted",col="grey2",lwd=2) + + sub_excess = excess.all[excess.all[,2]==nr,] + lines(cbind(sub_excess[,1], sub_excess[,6]),col="red",type="h",lwd=1.5) + prev_k <- k +} + +dev.off() + + +########################## cis eQTL ######################### +# plot eQTL per cM --> cis + +m = sort(d.cis[,6],TRUE)[1] +s = sort(d.cis[,6],TRUE)[2] +if (m > (s+100)) { + max_eqtl_freq = s + } +if (m <= (s+100)) { + max_eqtl_freq = m + } + +pdf("genome_wide_EcM_cis.pdf",width=12) + +par(mfrow=c(1,1)) +plot(cbind(d.cis[,1],d.cis[,6]),type="h",ylab="eQTL per cM",main="Frequency plot",xlab="Sliding window bins (4 to 5.9 cM each)",lwd=1.5, ylim = c(-(0.03*m), m), col="black") + +lines(cbind(excess.cis[,1],excess.cis[,6]),col="red",type="h",lwd=1.5) + +dotted = c(0,chr_ends[1:length(chr_ends)]+0.5) +abline(h=thresh.cis) +abline(v=dotted,lty="dotted",col="grey2",lwd=2) + +text(chr_ends.mid,rep(-(max_eqtl_freq*0.03),num.chr),labels=chrvector,cex=0.8) + +dev.off() + +pdf("chr_plots_EcM_cis.pdf",width=12) + +if (num.chr <= 6) { + par(mfrow=c(2,3)) + } +if (num.chr>6 & num.chr<=9) { + par(mfrow=c(3,3)) + } +if (num.chr>9 & num.chr<=12) { + par(mfrow=c(3,4)) + } +if (num.chr>12 & num.chr<=15) { + par(mfrow=c(3,5)) + } +if (num.chr>15 & num.chr<=20) { + par(mfrow=c(4,5)) + } +prev_k <- 0 +#m = max_eqtl_freq +for (k in chr_ends) { + nr = which(k == chr_ends) + plot(cbind(d.cis[(prev_k+1):k,1],d.cis[(prev_k+1):k,6]),type="l",ylab="eQTL per cM",main=paste("Chr ",nr),xlab="Sliding window bins",lwd=1.5, ylim = c(-(0.03*s), s), col="black") + dotted = c(prev_k,k+1) + abline(h=thresh.cis) + abline(v=dotted,lty="dotted",col="grey2",lwd=2) + + sub_excess = excess.cis[excess.cis[,2]==nr,] + lines(cbind(sub_excess[,1], sub_excess[,6]),col="red",type="h",lwd=1.5) + prev_k <- k +} + +dev.off() + +########################## trans eQTL ######################### +# plot eQTL per cM --> trans + +m = sort(d.trans[,6],TRUE)[1] +s = sort(d.trans[,6],TRUE)[2] +if (m > (s+100)) { + max_eqtl_freq = s + } +if (m <= (s+100)) { + max_eqtl_freq = m + } + +pdf("genome_wide_EcM_trans.pdf",width=12) + +par(mfrow=c(1,1)) +plot(cbind(d.trans[,1],d.trans[,6]),type="h",ylab="eQTL per cM",main="Frequency plot",xlab="Sliding window bins (4 to 5.9 cM each)",lwd=1.5, ylim = c(-(0.03*m), m), col="black") + +lines(cbind(excess.trans[,1],excess.trans[,6]),col="red",type="h",lwd=1.5) + +dotted = c(0,chr_ends[1:length(chr_ends)]+0.5) +abline(h=thresh.trans) +abline(v=dotted,lty="dotted",col="grey2",lwd=2) + +text(chr_ends.mid,rep(-(max_eqtl_freq*0.03),num.chr),labels=chrvector,cex=0.8) + +dev.off() + +pdf("chr_plots_EcM_trans.pdf",width=12) + +if (num.chr <= 6) { + par(mfrow=c(2,3)) + } +if (num.chr>6 & num.chr<=9) { + par(mfrow=c(3,3)) + } +if (num.chr>9 & num.chr<=12) { + par(mfrow=c(3,4)) + } +if (num.chr>12 & num.chr<=15) { + par(mfrow=c(3,5)) + } +if (num.chr>15 & num.chr<=20) { + par(mfrow=c(4,5)) + } +prev_k <- 0 +#m = max_eqtl_freq +for (k in chr_ends) { + nr = which(k == chr_ends) + plot(cbind(d.trans[(prev_k+1):k,1],d.trans[(prev_k+1):k,6]),type="l",ylab="eQTL per cM",main=paste("Chr ",nr),xlab="Sliding window bins",lwd=1.5, ylim = c(-(0.03*s), s), col="black") + dotted = c(prev_k,k+1) + abline(h=thresh.trans) + abline(v=dotted,lty="dotted",col="grey2",lwd=2) + + sub_excess = excess.trans[excess.trans[,2]==nr,] + lines(cbind(sub_excess[,1], sub_excess[,6]),col="red",type="h",lwd=1.5) + prev_k <- k +} + +dev.off() |
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| diff -r 000000000000 -r 0b383b61074d hotspots/hotspots.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/hotspots/hotspots.py Fri Mar 18 05:26:20 2016 -0400 |
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| b'@@ -0,0 +1,550 @@\n+"""\n+@summary: Get lists of eQTLs liked to significant hotspots\n+\n+@author: nanette.coetzer@gmail.com\n+@version 0.1\n+\n+"""\n+import optparse, sys\n+import subprocess\n+import tempfile\n+import os, re\n+\n+def stop_err( msg ):\n+ sys.stderr.write( "%s\\n" % msg )\n+ sys.exit()\n+ \n+def __main__():\n+ #Parse Command Line\n+ parser = optparse.OptionParser()\n+ parser.add_option("-a", "--rscript1", default=None, dest="rscript1", \n+ help="R script 1")\n+ parser.add_option("-b", "--rscript2", default=None, dest="rscript2", \n+ help="R script 2")\n+ parser.add_option("-i", "--input1", default=None, dest="input1", \n+ help="Gene and eQTL frequency per bin table")\n+ parser.add_option("-j", "--input2", default=None, dest="input2", \n+ help="Gene and eQTL sliding frequency")\n+ parser.add_option("-k", "--input3", default=None, dest="input3", \n+ help="Frequency summary file")\n+ parser.add_option("-l", "--input4", default=None, dest="input4", \n+ help="all eQTL classification file")\n+ parser.add_option("-m", "--input5", default=None, dest="input5", \n+ help="cis-eQTL classification file")\n+ parser.add_option("-n", "--input6", default=None, dest="input6", \n+ help="trans-eQTL classification file")\n+ parser.add_option("-g", "--input7", default=None, dest="input7", \n+ help="Sliding map file")\n+ \n+ parser.add_option("-o", "--output1", default=None, dest="output1", \n+ help="Unbiased all eQTL hotspots result file")\n+ parser.add_option("-p", "--output2", default=None, dest="output2", \n+ help="List of all eQTLs per hotspot")\n+ parser.add_option("-q", "--output3", default=None, dest="output3", \n+ help="Unbiased cis eQTL hotspots result file")\n+ parser.add_option("-r", "--output4", default=None, dest="output4", \n+ help="List of cis eQTLs per hotspot")\n+ parser.add_option("-s", "--output5", default=None, dest="output5", \n+ help="Unbiased trans eQTL hotspots result file")\n+ parser.add_option("-t", "--output6", default=None, dest="output6", \n+ help="List of trans eQTLs per hotspot")\n+ parser.add_option("-u", "--output7", default=None, dest="output7", \n+ help="Full summary file")\n+ parser.add_option("-v", "--output8", default=None, dest="output8", \n+ help="zip folder with R plots")\n+ (options, args) = parser.parse_args()\n+\n+ try:\n+ open(options.input1, "r").close()\n+ except TypeError, e:\n+ stop_err("You need to supply the Gene and eQTL frequency file:\\n" + str(e))\n+ except IOError, e:\n+ stop_err("Can not open the Gene and eQTL frequency file:\\n" + str(e))\n+ \n+ try:\n+ open(options.input2, "r").close()\n+ except TypeError, e:\n+ stop_err("You need to supply the Gene and eQTL sliding window frequency file:\\n" + str(e))\n+ except IOError, e:\n+ stop_err("Can not open the Gene and eQTL sliding window frequency file:\\n" + str(e))\n+\n+ try:\n+ open(options.input3, "r").close()\n+ except TypeError, e:\n+ stop_err("You need to supply the Frequency summary file:\\n" + str(e))\n+ except IOError, e:\n+ stop_err("Can not open the Frequency summary file:\\n" + str(e))\n+\n+ try:\n+ open(options.input4, "r").close()\n+ except TypeError, e:\n+ stop_err("You need to supply the all eQTL classification file:\\n" + str(e))\n+ except IOError, e:\n+ stop_err("Can not open the all eQTL classification file:\\n" + str(e))\n+\n+ try:\n+ open(options.input5, "r").close()\n+ except TypeError, e:\n+ stop_err("You need to supply the cis-eQTL classification file:\\n" + str(e))\n+ except IOError, e:\n+ stop_err("Can not open the cis-eQTL class'..b'ts_results_cis.write("\\n\\n= = = = = Hotspot "+str(hid)+" chr "+str(chr)+"\tsliding.ids: "+str(sl_ids)+"\tint.ids: "+str(lu_ids)+"\tnr.eQTL: "+str(freq_count)+" = = = = =\\n")\n+\tfor l in lu_ids:\n+\t intpos = lookup_tmp_dict[str(l)]\n+\t eqtl = open(options.input5,\'r\') # eqtls.txt \n+\t for eqtlline in eqtl:\n+\t \tel = eqtlline.strip().split("\\t")\n+\t \tif not el[2].startswith("c"):\n+\t \t pos = [el[2],str(round(float(el[8]),4))]\n+\t \t if intpos == pos:\n+\t\t\tgene_lists_results_cis.write("\\t".join(el)+"\\n")\n+\t eqtl.close()\n+ gene_lists_results_cis.close()\n+ \n+ # WRITE gene_lists_results --> trans\n+ for i in range(0,len(hotspot_slID_dict_trans.keys())):\n+ \thid = hotspot_slID_dict_trans.keys()[i]\n+\tsl_ids = hotspot_slID_dict_trans[int(i)+1]\n+\tlu_ids = []\n+\tfor j in sl_ids:\n+\t for k in sl_lookup_dict[str(j)]:\n+\t if int(k.strip()) not in lu_ids:\n+\t\t lu_ids.append(int(k.strip()))\n+\tchr = lookup_tmp_dict[str(lu_ids[0])][0]\n+\tfreq_count = 0\n+\tfor luid in lu_ids:\n+\t freq_count = freq_count + freq_dict_trans[str(luid)]\n+\t#tot_in_hotspots = tot_in_hotspots + freq_count\n+\tgene_lists_results_trans.write("\\n\\n= = = = = Hotspot "+str(hid)+" chr "+str(chr)+"\tsliding.ids: "+str(sl_ids)+"\tint.ids: "+str(lu_ids)+"\tnr.eQTL: "+str(freq_count)+" = = = = =\\n")\n+\tfor l in lu_ids:\n+\t intpos = lookup_tmp_dict[str(l)]\n+\t eqtl = open(options.input6,\'r\') # eqtls.txt \n+\t for eqtlline in eqtl:\n+\t \tel = eqtlline.strip().split("\\t")\n+\t \tif not el[2].startswith("c"):\n+\t \t pos = [el[2],str(round(float(el[8]),4))]\n+\t \t if intpos == pos:\n+\t\t\tgene_lists_results_trans.write("\\t".join(el)+"\\n")\n+\t eqtl.close()\n+ gene_lists_results_trans.close()\n+ \n+ \n+ ########################################## R plots ##########################################\n+ \n+ # Create temp direcotry\n+ tempdir = tempfile.mkdtemp()\n+\n+ # copy INPUT file to the temp directory\n+ s = "cp %s %s/all_hotspots_out.txt" %(options.output1, tempdir)\n+ subprocess.call(s, shell=True)\n+ s = "cp %s %s/cis_hotspots_out.txt" %(options.output3, tempdir)\n+ subprocess.call(s, shell=True)\n+ s = "cp %s %s/trans_hotspots_out.txt" %(options.output5, tempdir)\n+ subprocess.call(s, shell=True)\n+ s = "cp %s %s/full_summary.txt" %(options.output7, tempdir)\n+ subprocess.call(s, shell=True)\n+\n+ # create R script => save in temp directory\n+ # generate new header\n+ new_script = open(tempdir+"/new_script.r","w")\n+ header = "setwd(\\"%s\\")" %tempdir\n+ new_script.write(header+"\\n")\n+ # add script body\n+ \n+ script = open(options.rscript2,"r")\n+ for line in script:\n+ new_script.write(line.strip()+"\\n")\n+ new_script.close()\n+ \n+ # run R script from temp directory\n+ s = "R CMD BATCH %s/new_script.r out.txt" %tempdir\n+ subprocess.call(s, shell=True)\n+\n+ tempdir2 = tempfile.mkdtemp()\n+ #os.system("mv %s/genome_wide_EcM10G.pdf %s/genome_wide_EcM10G.pdf" %(tempdir,tempdir2))\n+ #os.system("mv %s/chr_plots_EcM10G.pdf %s/chr_plots_EcM10G.pdf" %(tempdir,tempdir2))\n+ os.system("mv %s/genome_wide_EcM_all.pdf %s/genome_wide_EcM_all.pdf" %(tempdir,tempdir2))\n+ os.system("mv %s/chr_plots_EcM_all.pdf %s/chr_plots_EcM_all.pdf" %(tempdir,tempdir2))\n+ os.system("mv %s/genome_wide_EcM_cis.pdf %s/genome_wide_EcM_cis.pdf" %(tempdir,tempdir2))\n+ os.system("mv %s/chr_plots_EcM_cis.pdf %s/chr_plots_EcM_cis.pdf" %(tempdir,tempdir2))\n+ os.system("mv %s/genome_wide_EcM_trans.pdf %s/genome_wide_EcM_trans.pdf" %(tempdir,tempdir2))\n+ os.system("mv %s/chr_plots_EcM_trans.pdf %s/chr_plots_EcM_trans.pdf" %(tempdir,tempdir2))\n+ s = "zip -j %s/output.zip %s/*" %(tempdir,tempdir2)\n+ subprocess.call(s, shell=True)\n+ \n+ # move the zipped temp directory to options.output\n+ os.system("mv %s/output.zip %s" %(tempdir,options.output8))\n+ \n+ \n+\n+ ##############################################\n+ \n+if __name__=="__main__": \n+ __main__()\n+\n+\n+\n' |
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| diff -r 000000000000 -r 0b383b61074d hotspots/hotspots.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/hotspots/hotspots.xml Fri Mar 18 05:26:20 2016 -0400 |
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| b'@@ -0,0 +1,230 @@\n+<tool id="hotspots5" name="Identify eQTL hotspots" version="5.0.0">\n+\t<description>using permutation threshold and chi-squared test</description>\n+\t<command interpreter="python">\n+ hotspots.py --rscript1 \\$R_SCRIPT_PATH/hotspots/threshold_chisq.txt --rscript2 \\$R_SCRIPT_PATH/hotspots/Rplots.txt --input1 $input1 --input2 $input2 --input3 $input3 --input4 $input4 --input5 $input5 --input6 $input6 --input7 $input7 --output1 $output1 --output2 $output2 --output3 $output3 --output4 $output4 --output5 $output5 --output6 $output6 --output7 $output7 --output8 $output8\n+\t</command>\n+ <inputs>\n+\t <param label="Frequency per bin file" name="input1" type="data" format="tabular" help="A tabular file with cM and bp positions, as well as the number of eQTL and genes for each interval"></param>\n+\t <param label="Sliding frequency file" name="input2" type="data" format="tabular" help="A tabular file with the gene and eQTL frequency per sliding window interval"></param>\n+\t <param label="Frequency summary file" name="input3" type="data" format="tabular" help="A tabular file with the total number of genes, eQTLs, cM and number of permutations."></param>\n+\t <param label="all eQTL classification file" name="input4" type="data" format="tabular" help="A tabular classification file with all eQTL"></param>\n+\t <param label="cis- eQTL classification file" name="input5" type="data" format="tabular" help="A tabular classification file with only cis eQTL"></param>\n+\t <param label="trans eQTL classification file" name="input6" type="data" format="tabular" help="A tabular classification file with only trans eQTL"></param>\n+\t <param label="Sliding-lookup map file" name="input7" type="data" format="tabular" help="A tabular file mapping sliding window IDs to lookup table IDs"></param>\n+\t</inputs>\n+\t<outputs>\n+ <data format="tabular" name="output1" />\n+\t\t<data format="tabular" name="output2" />\n+\t\t<data format="tabular" name="output3" />\n+\t\t<data format="tabular" name="output4" />\n+\t\t<data format="tabular" name="output5" />\n+\t\t<data format="tabular" name="output6" />\n+\t\t<data format="tabular" name="output7" />\n+\t\t<data format="zip" name="output8" />\n+\t</outputs>\n+\t<requirements>\n+\t\t<requirement type="set_environment">R_SCRIPT_PATH</requirement>\n+\t</requirements>\n+\t<tests>\n+ <test>\n+ </test>\n+\t</tests>\n+\t<help>\n+\t\t\n+**What it does**\n+\n+Identify the max number of eQTL expected by chance per cM using a permutation approach.\n+\n+Eliminate differential gene density as an explanatory factor for eQTL hotspots, by performing a chi-squared test per bin.\n+\n+* Calculate the proportion of genes to eQTLs, use this as the population estimates and test the null hypothesis that the number of genes and eQTLs in each interval is consistent.\n+\n+* Mark bins where the expected number (genes + eQTLs) of every interval is not 5 or more (assumption for chi-squared test). For these bins the chi-squared test cannot be performed.\n+\n+Extract lists of eQTLs linked to each unbiased eQTL hotspot.\n+\n+Genome wide eQTL freqeuncy plots. \n+\n+-------\n+\n+**Example input files**\n+\n+Frequency per bin file: frequency of all, cis and trans eQTLs and genes, each row correspond to a 2cM (or smaller) interval (11 columns; only a part of the file is shown)::\n+\n+ int.id chr marker interval cM bp length_cM num.eQTL.all\tnum.eQTL.cis num.eQTL.trans\tnum.genes\n+ 1 1 1 0.0001 \t0.0 2038278 \t2.0 94.0 \t2.0 \t64.0 \t12.0\n+ 2 1 1 0.0201 \t2.0 2466324 \t2.0 17.0 \t3.0 \t11.0 \t34.0\n+ 3 1 1 0.0401 \t4.0 2894370 \t2.0 8.0 \t2.0 \t5.0 \t29.0\n+ 4 1 1 0.0601 \t6.0 3322416 \t1.53 11.0 \t5.0 \t3.0 \t10.0\n+ 5 1 2 0.0754 \t7.53 3649871 \t2.0 27.0 \t6.0 \t19.0 \t18.0\n+ 6 1 2 0.0954 \t9.53 4095673 \t2.0 8.0 \t4.0 \t3.0 '..b' \t \t47.0 \t64.0 \t11.75 \t\t0 \t0 \n+\n+\n+eQTL/gene lists extracted for significant hotspots (Only the first 3 eQTLs linked to hotspots 1 - 5 are shown).\n+The chromosome, list of IDs and number of eQTLs in each hotspot is given in the header.\n+Three output file like this are generated, for all, cis and trans eQTLs respectively::\n+\n+ = = = = = Hotspot 1 chr 1 sliding.ids: [17, 18] int.ids: [19, 20, 21, 22] nr.eQTL: 257 = = = = =\t\t\t\t\t\t\t\t\t\t\t\t\n+ geneA 639 1 3 0.2878 4 0.3872 3 0.3478 13.7958496 0.110934 0.487661\t parentB no_result\t 19 NA\n+ geneL 800 1 3 0.2478 4 0.4072 3 0.3478 24.2128991 0.2848178 0.4639009 parentB no_result 19 NA\n+ geneB 382 1 3 0.2878 4 0.3872 3 0.3478 13.7048724 0.1522281 0.3023807 parentB trans \t 19 757\n+ geneD 457 1 3 0.2678 4 0.4072 3 0.3478 16.2210425 0.1537186 0.3527068 parentA trans \t 19 722\n+ geneE 381 1 3 0.2678 4 0.4272 3 0.3478 19.2398655 0.1747831 0.4636225 parentA cis \t 19 16\n+\n+ \xe2\x80\xa6\t\t\t\t\t\t\t\t\t\t\t\t\n+\n+ = = = = = Hotspot 2 chr 1 sliding.ids: [36, 37] int.ids: [43, 44, 45, 46] nr.eQTL: 268 = = = = =\t\t\t\t\t\t\t\t\t\t\t\t\n+ geneW 146 1 8 0.6998 9 0.9588 8 0.7798 17.6058658 0.168243 0.3517602 parentA cis 43 41\n+ geneP 510 1 8 0.6998 8 0.7998 8 0.7798 48.9321454 0.6530789 0.7453719 parentB trans 43 566\n+ geneF 231 1 8 0.7598 8 0.7998 8 0.7798 13.2268263 0.1715268 0.4169803 parentB trans 43 491\n+ geneY 480 1 7 0.6922 8 0.7998 8 0.7798 71.8820179 0.7463132 0.8353116 parentB no_result 43 NA\n+ geneG 652 1 8 0.7798 8 0.7798 8 0.7798 11.5596194 0.1168083 0.3429812 parentB trans 43 753\n+ geneJ 760 1 8 0.6998 9 0.9188 8 0.7798 22.0870242 0.2083328 0.396835 parentA cis 43 49\n+\n+ \xe2\x80\xa6\t\t\t\t\t\t\t\t\t\t\t\t\n+\n+\n+Full summary file (2 columns; 11 rows)::\n+\n+ Total number of eQTLs (all) \t\t\t31549\n+ Total number of cis-eQTLs \t\t\t4863\n+ Total number of trans-eQTLs \t\t\t21428\n+ Total number of genes \t\t\t\t31036\n+ Total number of cM \t\t\t\t1861.57\n+ Expected number of eQTL per cM (all) \t\t16.95\n+ Expected number of cis-eQTL per cM \t\t2.61\n+ Expected number of trans-eQTL per cM \t\t11.51\n+ Expected number of genes per cM \t\t\t16.67\n+ User specified number of permutations \t\t10\n+ Number of intervals per sliding window \t\t2\n+ Calculated permutation threshold for all eQTL (eQTL/cM) \t\t\t 33.55\n+ Chi-squared test population estimate for all eQTL (genes:eQTL) \t\t 0.496:0.504\n+ Chi-squared test assumption for all eQTL: min number of [eQTL + genes] in bin 10.08\n+ Calculated permutation threshold for all eQTL (eQTL/cM) \t\t\t 10.55\n+ Chi-squared test population estimate for cis-eQTL (genes:eQTL) \t\t 0.865:0.135\n+ Chi-squared test assumption for cis-eQTL: min number of [eQTL + genes] in bin 36.91\n+ Calculated permutation threshold for all eQTL (eQTL/cM) \t\t\t 27.55\n+ Chi-squared test population estimate for trans-eQTL (genes:eQTL) \t 0.592:0.408\n+ Chi-squared test assumption for trans-eQTL: min number of [eQTL + genes] in bin 12.24\n+\n+\n+Frequency plots of the eQTLs where significant hotspots are marked in red. The plot is generated using R and saved in pdf format.\n+\n+(i) Hotspot genome-wide plot [three plots are generated: all eQTL, cis eQTL and trans eQTL]\n+\n+(ii) Hotspot chr plots - eQTL / cM [three plots are generated: all eQTL, cis eQTL and trans eQTL]\n+\n+ </help>\n+</tool>\n' |
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| @@ -0,0 +1,30 @@ +====================================================================== +hotspots +====================================================================== +### This is the sixth tool in the eQTL backend pipeline: +lookup, classification, frequency, sliding window frequency, hotspots, GO enrichment + +Link to the workflow (for import into Galaxy): http://chewbacca.bi.up.ac.za:8080/u/nanette/w/back-end-workflow-2 + +Identify the max number of eQTL expected by chance per cM using a permutation approach. + +Eliminate differential gene density as an explanatory factor for eQTL hotspots, by performing a chi-squared test per bin. + +* Calculate the proportion of genes to eQTLs, use this as the population estimates and test the null hypothesis that the number of genes and eQTLs in each interval is consistent. +* Mark bins where the expected number (genes + eQTLs) of every interval is not 5 or more (assumption for chi-squared test). For these bins the chi-squared test cannot be performed. + +Extract lists of eQTLs linked to each unbiased eQTL hotspot. + +Genome wide eQTL freqeuncy plots. + +--------------- +Installation +--------------- + +The eQTL backend pipeline is available for: +* command line usage +* integration into Galaxy servers + + +Requirements: Python 2.7 + R 3.1.1 \ No newline at end of file |
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|
| b |
| diff -r 000000000000 -r 0b383b61074d hotspots/test-data/input/cis_classification_test.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/hotspots/test-data/input/cis_classification_test.txt Fri Mar 18 05:26:20 2016 -0400 |
| b |
| b'@@ -0,0 +1,4481 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|
| b |
| diff -r 000000000000 -r 0b383b61074d hotspots/test-data/input/frequency.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/hotspots/test-data/input/frequency.txt Fri Mar 18 05:26:20 2016 -0400 |
| b |
| b'@@ -0,0 +1,1020 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|
| b |
| diff -r 000000000000 -r 0b383b61074d hotspots/test-data/input/frequency_summary.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/hotspots/test-data/input/frequency_summary.txt Fri Mar 18 05:26:20 2016 -0400 |
| b |
| @@ -0,0 +1,11 @@ +Total number of eQTLs (all) 20206 +Total number of cis-eQTLs 4480 +Total number of trans-eQTLs 12539 +Total number of genes 31036 +Total number of cM 1861.57 +Expected number of eQTL per cM (all) 10.85 +Expected number of cis-eQTL per cM 2.41 +Expected number of trans-eQTL per cM 6.74 +Expected number of genes per cM 16.67 +User specified number of permutations 10 +Number of intervals per sliding window 2 |
| b |
| diff -r 000000000000 -r 0b383b61074d hotspots/test-data/input/sliding_frequency.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/hotspots/test-data/input/sliding_frequency.txt Fri Mar 18 05:26:20 2016 -0400 |
| b |
| b'@@ -0,0 +1,844 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|
| b |
| diff -r 000000000000 -r 0b383b61074d hotspots/test-data/input/sliding_lookup.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/hotspots/test-data/input/sliding_lookup.txt Fri Mar 18 05:26:20 2016 -0400 |
| [ |
| b'@@ -0,0 +1,843 @@\n+1\t[1, 2]\n+2\t[2, 3]\n+3\t[3, 4, 5]\n+4\t[5, 6]\n+5\t[6, 7]\n+6\t[7, 8]\n+7\t[8, 9]\n+8\t[9, 10, 11]\n+9\t[11, 12]\n+10\t[12, 13]\n+11\t[13, 14]\n+12\t[14, 15]\n+13\t[15, 16]\n+14\t[16, 17]\n+15\t[17, 18]\n+16\t[18, 19]\n+17\t[19, 20, 21]\n+18\t[21, 22]\n+19\t[22, 23, 24]\n+20\t[24, 25]\n+21\t[25, 26, 27]\n+22\t[27, 28]\n+23\t[28, 29, 30]\n+24\t[30, 31]\n+25\t[31, 32]\n+26\t[32, 33]\n+27\t[33, 34]\n+28\t[34, 35]\n+29\t[35, 36]\n+30\t[36, 37]\n+31\t[37, 38, 39]\n+32\t[39, 40]\n+33\t[40, 41]\n+34\t[41, 42]\n+35\t[42, 43]\n+36\t[43, 44, 45]\n+37\t[45, 46]\n+38\t[46, 47]\n+39\t[47, 48]\n+40\t[48, 49]\n+41\t[49, 50]\n+42\t[50, 51]\n+43\t[51, 52, 53]\n+44\t[53, 54]\n+45\t[54, 55]\n+46\t[55, 56]\n+47\t[56, 57]\n+48\t[57, 58]\n+49\t[58, 59]\n+50\t[59, 60]\n+51\t[60, 61, 62]\n+52\t[62, 63]\n+53\t[63, 64]\n+54\t[64, 65]\n+55\t[65, 66]\n+56\t[66, 67]\n+57\t[67, 68]\n+58\t[68, 69, 70]\n+59\t[70, 71]\n+60\t[71, 72]\n+61\t[72, 73]\n+62\t[73, 74]\n+63\t[74, 75]\n+64\t[75, 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828]\n+686\t[828, 829, 830]\n+687\t[830, 831, 832]\n+688\t[832, 833]\n+689\t[833, 834]\n+690\t[834, 835]\n+691\t[835, 836]\n+692\t[836, 837]\n+693\t[837, 838]\n+694\t[838, 839, 840]\n+695\t[840, 841]\n+696\t[841, 842]\n+697\t[842, 843]\n+698\t[843, 844, 845]\n+699\t[845, 846, 847]\n+700\t[847, 848]\n+701\t[848, 849]\n+702\t[849, 850]\n+703\t[850, 851, 852]\n+704\t[854, 855]\n+705\t[855, 856]\n+706\t[856, 857]\n+707\t[857, 858]\n+708\t[858, 859]\n+709\t[859, 860]\n+710\t[860, 861]\n+711\t[861, 862, 863]\n+712\t[863, 864]\n+713\t[864, 865]\n+714\t[865, 866]\n+715\t[866, 867, 868]\n+716\t[868, 869]\n+717\t[869, 870]\n+718\t[870, 871]\n+719\t[871, 872]\n+720\t[872, 873]\n+721\t[873, 874]\n+722\t[874, 875]\n+723\t[875, 876]\n+724\t[876, 877, 878]\n+725\t[878, 879]\n+726\t[879, 880]\n+727\t[880, 881]\n+728\t[881, 882]\n+729\t[882, 883]\n+730\t[883, 884]\n+731\t[884, 885]\n+732\t[885, 886]\n+733\t[886, 887, 888]\n+734\t[888, 889]\n+735\t[889, 890]\n+736\t[890, 891]\n+737\t[891, 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954]\n+791\t[954, 955, 956]\n+792\t[956, 957]\n+793\t[957, 958]\n+794\t[958, 959]\n+795\t[959, 960]\n+796\t[960, 961]\n+797\t[961, 962, 963]\n+798\t[963, 964]\n+799\t[964, 965]\n+800\t[965, 966, 967]\n+801\t[967, 968]\n+802\t[968, 969]\n+803\t[969, 970]\n+804\t[970, 971]\n+805\t[971, 972]\n+806\t[972, 973]\n+807\t[973, 974]\n+808\t[974, 975]\n+809\t[975, 976]\n+810\t[976, 977]\n+811\t[977, 978, 979]\n+812\t[979, 980]\n+813\t[980, 981]\n+814\t[981, 982, 983]\n+815\t[983, 984]\n+816\t[984, 985]\n+817\t[985, 986]\n+818\t[986, 987, 988]\n+819\t[988, 989]\n+820\t[989, 990]\n+821\t[990, 991]\n+822\t[991, 992, 993]\n+823\t[993, 994]\n+824\t[994, 995, 996]\n+825\t[996, 997]\n+826\t[997, 998]\n+827\t[998, 999]\n+828\t[999, 1000]\n+829\t[1000, 1001]\n+830\t[1001, 1002, 1003]\n+831\t[1003, 1004]\n+832\t[1004, 1005]\n+833\t[1005, 1006]\n+834\t[1006, 1007]\n+835\t[1007, 1008]\n+836\t[1008, 1009, 1010]\n+837\t[1010, 1011]\n+838\t[1011, 1012]\n+839\t[1012, 1013]\n+840\t[1013, 1014]\n+841\t[1014, 1015]\n+842\t[1015, 1016]\n+843\t[1016, 1017, 1018]\n' |
| b |
| diff -r 000000000000 -r 0b383b61074d hotspots/test-data/input/trans_classification_test.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/hotspots/test-data/input/trans_classification_test.txt Fri Mar 18 05:26:20 2016 -0400 |
| b |
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| [ |
| b'@@ -0,0 +1,6670 @@\n+\n+\n+= = = = = Hotspot 1 chr 1\tsliding.ids: [74, 75]\tint.ids: [87, 88, 89, 90]\tnr.eQTL: 267 = = = = =\n+A_92_P003179\t38\t1\t14\t1.5189\t15\t1.7242\t14\t1.5898\t13.0923923\t0.1160958\t0.4419218\t-717.8261159\ttrans\t87\t564\t0\t.\n+A_92_P040234\t113\t1\t14\t1.523\t14\t1.6374\t14\t1.5898\t13.2375371\t0.1735545\t0.3289205\t59.89843\ttrans\t87\t249\t0\t.\n+A_92_P030801\t481\t1\t14\t1.5112\t15\t1.685\t14\t1.5898\t13.6472813\t0.159372\t0.3139351\t169.4014923\tno_result\t87\tNA\t0\t.\n+A_92_P010026\t281\t1\t13\t1.4894\t15\t1.7176\t14\t1.5898\t14.0601315\t0.1384158\t0.3598481\t73.9672424\ttrans\t87\t582\t0\t.\n+A_92_P018970\t421\t1\t13\t1.4896\t15\t1.6781\t14\t1.5898\t14.2866823\t0.1375551\t0.367953\t23.7538055\tcis\t87\t86\t0.935967581087\tfull\n+A_92_P028857\t58\t1\t14\t1.5279\t15\t1.6873\t14\t1.5898\t14.603183\t0.176565\t0.3258133\t600.7075678\tno_result\t87\tNA\t0\t.\n+A_92_P013318\t83\t1\t14\t1.5128\t15\t1.704\t14\t1.5898\t14.6497404\t0.1577078\t0.3506962\t61.3618832\ttrans\t87\t307\t0\t.\n+A_92_P010934\t316\t1\t14\t1.5058\t15\t1.657\t14\t1.5898\t14.7928872\t0.1538131\t0.4378542\t447.3949532\ttrans\t87\t229\t0\t.\n+A_92_P005089\t213\t1\t14\t1.5317\t15\t1.6638\t14\t1.5898\t15.3848572\t0.1430201\t0.5322223\t-510.4079798\ttrans\t87\t606\t0\t.\n+A_92_P019196\t146\t1\t14\t1.5161\t15\t1.6795\t14\t1.5898\t15.4363838\t0.210801\t0.3489457\t45.5565171\ttrans\t87\t304\t0\t.\n+A_92_P034484\t314\t1\t14\t1.5351\t14\t1.6344\t14\t1.5898\t15.6193027\t0.2667804\t0.4981222\t83.116333\ttrans\t87\t315\t0\t.\n+A_92_P029527\t88\t1\t14\t1.5085\t15\t1.6749\t14\t1.5898\t15.8585378\t0.1866631\t0.4132141\t43.4457378\ttrans\t87\t51\t0\t.\n+A_92_P019550\t465\t1\t14\t1.5255\t15\t1.6937\t14\t1.5898\t16.3973945\t0.1825587\t0.4307305\t70.9673904\ttrans\t87\t973\t0\t.\n+A_92_P015509\t433\t1\t14\t1.5238\t15\t1.6782\t14\t1.5898\t16.5765696\t0.1918636\t0.4102299\t44.5146505\ttrans\t87\t103\t0\t.\n+A_92_P023671\t509\t1\t14\t1.5315\t14\t1.633\t14\t1.5898\t16.8700588\t0.2062716\t0.379134\t192.3525336\tno_result\t87\tNA\t0\t.\n+A_92_P020228\t491\t1\t14\t1.5225\t15\t1.7139\t14\t1.5898\t17.0050812\t0.181226\t0.4329947\t33.041952\ttrans\t87\t305\t0\t.\n+A_92_P022971\t7\t1\t14\t1.5232\t15\t1.6508\t14\t1.5898\t17.379494\t0.1662458\t0.7298192\t47.7807209\tno_result\t87\tNA\t0\t.\n+A_92_P020952\t272\t1\t14\t1.5245\t15\t1.6678\t14\t1.5898\t17.7956999\t0.1753027\t0.4275846\t82.4954784\ttrans\t87\t719\t0\t.\n+A_92_P035419\t163\t1\t14\t1.5251\t15\t1.6805\t14\t1.5898\t18.1336444\t0.1862053\t0.4747777\t-580.4085042\ttrans\t87\t551\t0\t.\n+A_92_P024212\t422\t1\t14\t1.5448\t14\t1.6326\t14\t1.5898\t18.1712392\t0.2676188\t0.6450103\t55.3143304\ttrans\t87\t19\t0\t.\n+A_92_P018238\t427\t1\t14\t1.5263\t14\t1.6418\t14\t1.5898\t18.6969557\t0.2559993\t0.6946255\t24.778157\ttrans\t87\t140\t0\t.\n+A_92_P027791\t460\t1\t14\t1.5335\t15\t1.6739\t14\t1.5898\t19.0296161\t0.15211\t0.5963342\t102.1026941\ttrans\t87\tNA\t0\t.\n+A_92_P020251\t438\t1\t14\t1.5218\t15\t1.7031\t14\t1.5898\t19.5125058\t0.1877314\t0.4669267\t41.5530694\ttrans\t87\t359\t0\t.\n+A_92_P023786\t243\t1\t14\t1.5274\t15\t1.673\t14\t1.5898\t20.0286426\t0.3235791\t0.6273064\t28.9275016\tno_result\t87\tNA\t0\t.\n+A_92_P019386\t429\t1\t14\t1.5312\t15\t1.6945\t14\t1.5898\t20.4233172\t0.2305457\t0.3641347\t181.037916\ttrans\t87\t743\t0\t.\n+A_92_P031316\t89\t1\t14\t1.5241\t15\t1.6676\t14\t1.5898\t20.4552067\t0.1933242\t0.4532889\t102.7859024\ttrans\t87\t112\t0\t.\n+A_92_P008124\t132\t1\t14\t1.5264\t15\t1.683\t14\t1.5898\t20.8435472\t0.1892662\t0.4637044\t-330.5978593\ttrans\t87\t23\t0\t.\n+A_92_P038075\t506\t1\t14\t1.5172\t15\t1.7376\t14\t1.5898\t21.0581086\t0.1994937\t0.5670474\t44.4812347\tno_result\t87\tNA\t0\t.\n+A_92_P020547\t147\t1\t14\t1.5307\t15\t1.686\t14\t1.5898\t24.7980591\t0.2130294\t0.4734666\t130.4842818\tcis\t87\t89\t0.925783637282\tfull\n+A_92_P014832\t344\t1\t14\t1.5166\t15\t1.6494\t14\t1.5898\t27.4311982\t0.2471627\t0.4651858\t114.6228674\ttrans\t87\t141\t0\t.\n+A_92_P036378\t357\t1\t14\t1.5411\t14\t1.6261\t14\t1.5898\t30.8567878\t0.385263\t0.5434175\t183.8262266\ttrans\t87\t286\t0\t.\n+A_92_P034671\t70\t1\t14\t1.5292\t14\t1.6307\t14\t1.5898\t38.5498946\t0.4156107\t0.4744508\t-155.7969017\ttrans\t87\t92\t0\t.\n+A_92_P038464\t76\t1\t14\t1.5537\t15\t1.6885\t14\t1.5898\t41.5376464\t0.540404\t0.7521281\t-51.7364193\tno_result\t87\tNA\t0\t.\n+A_92_P034705\t474\t1\t14\t1.549\t14\t1.6193\t14\t1.5898\t76.2319063\t0.5726133\t0.7102597\t2893.63448\tcis\t87\t89\t0.356023539516\tpartial\n+A_92_P031716\t462\t1\t14\t1.5506\t14\t1.6302\t14\t1.5898\t86.4037424\t0.6456094\t0.7603014\t-1011.354804\tcis\t87\t91\t0.209786315917\tparti'..b'805079\t0.4249404\t21.8416197\ttrans\t1018\t544\t0\t.\n+A_92_P025425\t410\t10\t12\t1.4043\t12\t1.4654\t12\t1.4654\t18.8789084\t0.1657852\t0.3476669\t48.4248141\ttrans\t1018\t470\t0\t.\n+A_92_P023020\t311\t10\t12\t1.4134\t12\t1.4654\t12\t1.4654\t18.9176079\t0.2347249\t0.4361272\t41.1763746\tno_result\t1018\tNA\t0\t.\n+A_92_P022234\t341\t10\t12\t1.3865\t12\t1.4654\t12\t1.4654\t19.1075367\t0.2133459\t0.4348225\t57.420108\ttrans\t1018\t212\t0\t.\n+A_92_P040864\t182\t10\t12\t1.377\t12\t1.4654\t12\t1.4654\t19.1785239\t0.1940997\t0.2841756\t127.3066114\tno_result\t1018\tNA\t0\t.\n+A_92_P025306\t112\t10\t12\t1.3958\t12\t1.4654\t12\t1.4654\t19.3425356\t0.1482326\t0.3938621\t52.402676\ttrans\t1018\tNA\t0\t.\n+A_92_P009598\t541\t10\t12\t1.3937\t12\t1.4654\t12\t1.4654\t19.5381805\t0.1251372\t0.6625968\t-712.4099878\ttrans\t1018\t229\t0\t.\n+A_92_P024212\t422\t10\t12\t1.3992\t12\t1.4654\t12\t1.4654\t19.6064977\t0.2375823\t0.5002322\t52.7638845\ttrans\t1018\t19\t0\t.\n+A_92_P026028\t79\t10\t12\t1.3914\t12\t1.4654\t12\t1.4654\t20.3992708\t0.1855026\t0.3085852\t93.1442027\ttrans\t1018\t661\t0\t.\n+A_92_P021863\t515\t10\t12\t1.4073\t12\t1.4654\t12\t1.4654\t20.5831168\t0.1885752\t0.3996008\t46.6019616\ttrans\t1018\t470\t0\t.\n+A_92_P019500\t527\t10\t12\t1.3909\t12\t1.4654\t12\t1.4654\t20.7811533\t0.2171057\t0.5712754\t48.5459071\ttrans\t1018\tNA\t0\t.\n+A_92_P018605\t411\t10\t12\t1.4\t12\t1.4654\t12\t1.4654\t21.1040807\t0.2470094\t0.4272557\t18.6917552\ttrans\t1018\t430\t0\t.\n+A_92_P040676\t462\t10\t12\t1.4196\t12\t1.4654\t12\t1.4654\t21.4474993\t0.183169\t0.3762722\t222.4201279\ttrans\t1018\t18\t0\t.\n+A_92_P038891\t510\t10\t12\t1.3729\t12\t1.4654\t12\t1.4654\t22.8191001\t0.2003765\t0.3699092\t219.5405688\tno_result\t1018\tNA\t0\t.\n+A_92_P011881\t8\t10\t12\t1.3883\t12\t1.4654\t12\t1.4654\t23.4445413\t0.2030384\t0.4395421\t-73.9299533\tcis\t1018\t1014\t0.425841037378\tpartial\n+A_92_P028742\t340\t10\t12\t1.4343\t12\t1.4654\t12\t1.4654\t23.5373748\t0.2466954\t0.3766208\t-65.1331884\ttrans\t1018\tNA\t0\t.\n+A_92_P025620\t43\t10\t12\t1.3991\t12\t1.4654\t12\t1.4654\t23.9309014\t0.2736644\t0.4796374\t116.16188\ttrans\t1018\t804\t0\t.\n+A_92_P016350\t531\t10\t12\t1.4083\t12\t1.4654\t12\t1.4654\t24.3372991\t0.1321456\t0.5915645\t915.05996\ttrans\t1018\t539\t0\t.\n+A_92_P034395\t281\t10\t12\t1.4188\t12\t1.4654\t12\t1.4654\t24.5032178\t0.2368342\t0.4777931\t953.68815\ttrans\t1018\t823\t0\t.\n+A_92_P001652\t289\t10\t12\t1.4153\t12\t1.4654\t12\t1.4654\t24.7282091\t0.312855\t0.4191383\t-91.6854094\tcis\t1018\t1016\t0.908282570119\tfull\n+A_92_P019294\t257\t10\t12\t1.4275\t12\t1.4654\t12\t1.4654\t25.007352\t0.2890627\t0.560038\t29.7095764\ttrans\t1018\t282\t0\t.\n+A_92_P001577\t424\t10\t12\t1.3963\t12\t1.4654\t12\t1.4654\t25.1995957\t0.2378581\t0.3417466\t-223.6678649\tcis\t1018\t1018\t0.671213773773\tpartial\n+A_92_P028902\t346\t10\t12\t1.4242\t12\t1.4654\t12\t1.4654\t25.7049413\t0.2114093\t0.5586152\t-39.2568299\ttrans\t1018\tNA\t0\t.\n+A_92_P006006\t162\t10\t12\t1.4106\t12\t1.4654\t12\t1.4654\t26.0644596\t0.2795096\t0.4312353\t-190.7323527\tno_result\t1018\tNA\t0\t.\n+A_92_P033721\t509\t10\t12\t1.4111\t12\t1.4654\t12\t1.4654\t26.3758182\t0.3486156\t0.5568993\t58.1042743\ttrans\t1018\t850\t0\t.\n+A_92_P017792\t494\t10\t12\t1.4226\t12\t1.4654\t12\t1.4654\t28.3108534\t0.3267935\t0.5538729\t50.1565754\ttrans\t1018\t900\t0\t.\n+A_92_P029608\t28\t10\t12\t1.3811\t12\t1.4654\t12\t1.4654\t29.7148963\t0.1541602\t0.6267279\t-98.5869791\ttrans\t1018\tNA\t0\t.\n+A_92_P041862\t179\t10\t12\t1.432\t12\t1.4654\t12\t1.4654\t30.1747473\t0.2481949\t0.3969381\t-1073.195619\tcis\t1018\t1015\t0.399130872814\tpartial\n+A_92_P038669\t350\t10\t12\t1.4122\t12\t1.4654\t12\t1.4654\t30.2337867\t0.3997162\t0.5304303\t63.9955185\ttrans\t1018\t676\t0\t.\n+A_92_P026030\t144\t10\t12\t1.4316\t12\t1.4654\t12\t1.4654\t30.3489326\t0.2548777\t0.408289\t248.3330196\tno_result\t1018\tNA\t0\t.\n+A_92_P013644\t147\t10\t12\t1.4392\t12\t1.4654\t12\t1.4654\t36.302691\t0.2704067\t0.4321638\t485.5732024\tcis\t1018\tNA\t0.511504817973\tpartial\n+A_92_P013701\t386\t10\t12\t1.4348\t12\t1.4654\t12\t1.4654\t43.430415\t0.2896725\t0.53836\t-512.8364238\tcis\t1018\t1016\t0.890462499976\tfull\n+A_92_P005353\t136\t10\t12\t1.4333\t12\t1.4654\t12\t1.4654\t60.9634385\t0.546986\t0.6811763\t513.4044466\tno_result\t1018\tNA\t0\t.\n+A_92_P008858\t492\t10\t12\t1.4113\t12\t1.4654\t12\t1.4654\t74.0214603\t0.4969076\t0.7496752\t-724.8010249\tcis\t1018\t1016\t0.905396130134\tfull\n+A_92_P021191\t390\t10\t12\t1.4354\t12\t1.4654\t12\t1.4654\t138.6569417\t0.7780008\t0.8424187\t2660.007396\tcis\t1018\t1018\t0.564579761709\tpartial\n' |
| b |
| diff -r 000000000000 -r 0b383b61074d hotspots/test-data/output/all_hotspots_out.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/hotspots/test-data/output/all_hotspots_out.txt Fri Mar 18 05:26:20 2016 -0400 |
| b |
| b'@@ -0,0 +1,844 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|
| b |
| diff -r 000000000000 -r 0b383b61074d hotspots/test-data/output/cis_eQTL_lists.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/hotspots/test-data/output/cis_eQTL_lists.txt Fri Mar 18 05:26:20 2016 -0400 |
| [ |
| b'@@ -0,0 +1,174 @@\n+\n+\n+= = = = = Hotspot 1 chr 2\tsliding.ids: [198]\tint.ids: [231, 232]\tnr.eQTL: 54 = = = = 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|
| b |
| diff -r 000000000000 -r 0b383b61074d hotspots/test-data/output/cis_hotspots_out.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/hotspots/test-data/output/cis_hotspots_out.txt Fri Mar 18 05:26:20 2016 -0400 |
| b |
| b'@@ -0,0 +1,844 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0\t36.0\t1.25\t0\t0\t\t\n+832\t10\t4.0\t4.0\t33.0\t1.0\t0\t0\t\t\n+833\t10\t4.0\t0.0\t38.0\t0.0\t0\t0\t\t\n+834\t10\t4.0\t2.0\t26.0\t0.5\t0\t0\t\t\n+835\t10\t4.0\t4.0\t20.0\t1.0\t0\t0\t\t\n+836\t10\t4.9\t7.0\t38.0\t1.43\t0\t0\t\t\n+837\t10\t4.0\t8.0\t33.0\t2.0\t0\t0\t\t\n+838\t10\t4.0\t12.0\t48.0\t3.0\t0\t0\t\t\n+839\t10\t4.0\t8.0\t60.0\t2.0\t0\t0\t\t\n+840\t10\t4.0\t2.0\t49.0\t0.5\t0\t0\t\t\n+841\t10\t4.0\t2.0\t53.0\t0.5\t0\t0\t\t\n+842\t10\t4.0\t5.0\t57.0\t1.25\t0\t0\t\t\n+843\t10\t4.95\t16.0\t43.0\t3.23\t0\t0\t\t\n' |
| b |
| diff -r 000000000000 -r 0b383b61074d hotspots/test-data/output/full_summary.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/hotspots/test-data/output/full_summary.txt Fri Mar 18 05:26:20 2016 -0400 |
| [ |
| @@ -0,0 +1,20 @@ +Total number of eQTLs (all) 20206 +Total number of cis-eQTLs 4480 +Total number of trans-eQTLs 12539 +Total number of genes 31036 +Total number of cM 1861.57 +Expected number of eQTL per cM (all) 10.85 +Expected number of cis-eQTL per cM 2.41 +Expected number of trans-eQTL per cM 6.74 +Expected number of genes per cM 16.67 +User specified number of permutations 10 +Number of intervals per sliding window 2 +Calculated permutation threshold for all eQTL (eQTL/cM) 25.55 +Chi-squared test population estimate for all eQTL (genes:eQTL) 0.606:0.394 +Chi-squared test assumption for all eQTL: min number of [eQTL + genes] in bin 12.68 +Calculated permutation threshold for all eQTL (eQTL/cM) 11.1 +Chi-squared test population estimate for cis-eQTL (genes:eQTL) 0.874:0.126 +Chi-squared test assumption for cis-eQTL: min number of [eQTL + genes] in bin 39.64 +Calculated permutation threshold for all eQTL (eQTL/cM) 19.55 +Chi-squared test population estimate for trans-eQTL (genes:eQTL) 0.712:0.288 +Chi-squared test assumption for trans-eQTL: min number of [eQTL + genes] in bin 17.38 |
| b |
| diff -r 000000000000 -r 0b383b61074d hotspots/test-data/output/trans_eQTL_lists.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/hotspots/test-data/output/trans_eQTL_lists.txt Fri Mar 18 05:26:20 2016 -0400 |
| [ |
| b'@@ -0,0 +1,4394 @@\n+\n+\n+= = = = = Hotspot 1 chr 1\tsliding.ids: [74, 75]\tint.ids: [87, 88, 89, 90]\tnr.eQTL: 210 = = = = =\n+A_92_P003179\t38\t1\t14\t1.5189\t15\t1.7242\t14\t1.5898\t13.0923923\t0.1160958\t0.4419218\t-717.8261159\ttrans\t87\t564\t0\t.\n+A_92_P040234\t113\t1\t14\t1.523\t14\t1.6374\t14\t1.5898\t13.2375371\t0.1735545\t0.3289205\t59.89843\ttrans\t87\t249\t0\t.\n+A_92_P010026\t281\t1\t13\t1.4894\t15\t1.7176\t14\t1.5898\t14.0601315\t0.1384158\t0.3598481\t73.9672424\ttrans\t87\t582\t0\t.\n+A_92_P013318\t83\t1\t14\t1.5128\t15\t1.704\t14\t1.5898\t14.6497404\t0.1577078\t0.3506962\t61.3618832\ttrans\t87\t307\t0\t.\n+A_92_P010934\t316\t1\t14\t1.5058\t15\t1.657\t14\t1.5898\t14.7928872\t0.1538131\t0.4378542\t447.3949532\ttrans\t87\t229\t0\t.\n+A_92_P005089\t213\t1\t14\t1.5317\t15\t1.6638\t14\t1.5898\t15.3848572\t0.1430201\t0.5322223\t-510.4079798\ttrans\t87\t606\t0\t.\n+A_92_P019196\t146\t1\t14\t1.5161\t15\t1.6795\t14\t1.5898\t15.4363838\t0.210801\t0.3489457\t45.5565171\ttrans\t87\t304\t0\t.\n+A_92_P034484\t314\t1\t14\t1.5351\t14\t1.6344\t14\t1.5898\t15.6193027\t0.2667804\t0.4981222\t83.116333\ttrans\t87\t315\t0\t.\n+A_92_P029527\t88\t1\t14\t1.5085\t15\t1.6749\t14\t1.5898\t15.8585378\t0.1866631\t0.4132141\t43.4457378\ttrans\t87\t51\t0\t.\n+A_92_P019550\t465\t1\t14\t1.5255\t15\t1.6937\t14\t1.5898\t16.3973945\t0.1825587\t0.4307305\t70.9673904\ttrans\t87\t973\t0\t.\n+A_92_P015509\t433\t1\t14\t1.5238\t15\t1.6782\t14\t1.5898\t16.5765696\t0.1918636\t0.4102299\t44.5146505\ttrans\t87\t103\t0\t.\n+A_92_P020228\t491\t1\t14\t1.5225\t15\t1.7139\t14\t1.5898\t17.0050812\t0.181226\t0.4329947\t33.041952\ttrans\t87\t305\t0\t.\n+A_92_P020952\t272\t1\t14\t1.5245\t15\t1.6678\t14\t1.5898\t17.7956999\t0.1753027\t0.4275846\t82.4954784\ttrans\t87\t719\t0\t.\n+A_92_P035419\t163\t1\t14\t1.5251\t15\t1.6805\t14\t1.5898\t18.1336444\t0.1862053\t0.4747777\t-580.4085042\ttrans\t87\t551\t0\t.\n+A_92_P024212\t422\t1\t14\t1.5448\t14\t1.6326\t14\t1.5898\t18.1712392\t0.2676188\t0.6450103\t55.3143304\ttrans\t87\t19\t0\t.\n+A_92_P018238\t427\t1\t14\t1.5263\t14\t1.6418\t14\t1.5898\t18.6969557\t0.2559993\t0.6946255\t24.778157\ttrans\t87\t140\t0\t.\n+A_92_P027791\t460\t1\t14\t1.5335\t15\t1.6739\t14\t1.5898\t19.0296161\t0.15211\t0.5963342\t102.1026941\ttrans\t87\tNA\t0\t.\n+A_92_P020251\t438\t1\t14\t1.5218\t15\t1.7031\t14\t1.5898\t19.5125058\t0.1877314\t0.4669267\t41.5530694\ttrans\t87\t359\t0\t.\n+A_92_P019386\t429\t1\t14\t1.5312\t15\t1.6945\t14\t1.5898\t20.4233172\t0.2305457\t0.3641347\t181.037916\ttrans\t87\t743\t0\t.\n+A_92_P031316\t89\t1\t14\t1.5241\t15\t1.6676\t14\t1.5898\t20.4552067\t0.1933242\t0.4532889\t102.7859024\ttrans\t87\t112\t0\t.\n+A_92_P008124\t132\t1\t14\t1.5264\t15\t1.683\t14\t1.5898\t20.8435472\t0.1892662\t0.4637044\t-330.5978593\ttrans\t87\t23\t0\t.\n+A_92_P014832\t344\t1\t14\t1.5166\t15\t1.6494\t14\t1.5898\t27.4311982\t0.2471627\t0.4651858\t114.6228674\ttrans\t87\t141\t0\t.\n+A_92_P036378\t357\t1\t14\t1.5411\t14\t1.6261\t14\t1.5898\t30.8567878\t0.385263\t0.5434175\t183.8262266\ttrans\t87\t286\t0\t.\n+A_92_P034671\t70\t1\t14\t1.5292\t14\t1.6307\t14\t1.5898\t38.5498946\t0.4156107\t0.4744508\t-155.7969017\ttrans\t87\t92\t0\t.\n+A_92_P023241\t167\t1\t14\t1.521\t15\t1.7113\t14\t1.6098\t13.028027\t0.122258\t0.3383303\t107.3854869\ttrans\t88\t146\t0\t.\n+A_92_P034274\t40\t1\t14\t1.5319\t15\t1.7128\t14\t1.6098\t13.0654593\t0.1431467\t0.468354\t24.4816303\ttrans\t88\t813\t0\t.\n+A_92_P032985\t317\t1\t14\t1.5291\t15\t1.6971\t14\t1.6098\t13.0663104\t0.1265677\t0.3900438\t-56.1153277\ttrans\t88\t770\t0\t.\n+A_92_P019149\t334\t1\t14\t1.531\t15\t1.703\t14\t1.6098\t13.1030272\t0.116298\t0.3966378\t285.3518075\ttrans\t88\t815\t0\t.\n+A_92_P022739\t245\t1\t14\t1.5286\t15\t1.6982\t14\t1.6098\t13.4051519\t0.1265311\t0.3506904\t170.8891589\ttrans\t88\tNA\t0\t.\n+A_92_P023193\t211\t1\t14\t1.5259\t15\t1.7074\t14\t1.6098\t13.4739726\t0.0941342\t0.5076846\t76.4521831\ttrans\t88\t573\t0\t.\n+A_92_P033701\t281\t1\t14\t1.5218\t15\t1.7336\t14\t1.6098\t13.5284808\t0.1161719\t0.4814762\t45.5715939\ttrans\t88\t981\t0\t.\n+A_92_P029582\t462\t1\t14\t1.5225\t15\t1.7127\t14\t1.6098\t13.5346759\t0.1386997\t0.320134\t65.8201383\ttrans\t88\t1016\t0\t.\n+A_92_P019115\t514\t1\t14\t1.5164\t15\t1.6872\t14\t1.6098\t13.5365553\t0.1342559\t0.3106255\t-229.2124125\ttrans\t88\tNA\t0\t.\n+A_92_P022953\t86\t1\t14\t1.5403\t15\t1.6944\t14\t1.6098\t13.7273862\t0.2171572\t0.485182\t31.1509337\ttrans\t88\t391\t0\t.\n+A_92_P010860\t307\t1\t14\t1.5223\t15\t1.6713\t14\t1.6098\t13.7304423\t0.1387\t0.4219987\t287.7398175\ttrans\t88\t814\t0\t.\n+A_92_P021792\t54\t1\t14\t1.526\t15\t1.7162\t14\t1.6098\t13.7867804\t0.1154861\t0.4159'..b'9\t389\t10\t12\t1.4009\t12\t1.4654\t12\t1.4654\t16.4946379\t0.1289565\t0.3588333\t136.4280208\ttrans\t1018\t65\t0\t.\n+A_92_P017856\t165\t10\t12\t1.3985\t12\t1.4654\t12\t1.4654\t16.5538165\t0.1146083\t0.4619278\t303.0514736\ttrans\t1018\t265\t0\t.\n+A_92_P019451\t484\t10\t12\t1.4053\t12\t1.4654\t12\t1.4654\t16.6075\t0.1687392\t0.2576187\t46.1932181\ttrans\t1018\t546\t0\t.\n+A_92_P028996\t369\t10\t12\t1.3709\t12\t1.4654\t12\t1.4654\t16.6619528\t0.1397577\t0.4290501\t137.0815762\ttrans\t1018\t75\t0\t.\n+A_92_P026685\t257\t10\t12\t1.3958\t12\t1.4654\t12\t1.4654\t16.6886335\t0.1724425\t0.3907943\t34.2811594\ttrans\t1018\t225\t0\t.\n+A_92_P013929\t465\t10\t12\t1.4032\t12\t1.4654\t12\t1.4654\t16.8962486\t0.1778078\t0.3852615\t35.7024229\ttrans\t1018\t101\t0\t.\n+A_92_P021666\t69\t10\t12\t1.3823\t12\t1.4654\t12\t1.4654\t17.1118091\t0.2339957\t0.4673064\t40.0375189\ttrans\t1018\t558\t0\t.\n+A_92_P041671\t528\t10\t12\t1.3782\t12\t1.4654\t12\t1.4654\t17.1941578\t0.1657864\t0.344375\t479.1024425\ttrans\t1018\t534\t0\t.\n+A_92_P027061\t298\t10\t12\t1.3948\t12\t1.4654\t12\t1.4654\t17.363954\t0.1797989\t0.4700252\t27.6240992\ttrans\t1018\tNA\t0\t.\n+A_92_P021184\t71\t10\t12\t1.3684\t12\t1.4654\t12\t1.4654\t17.3851095\t0.1740818\t0.3531018\t66.3308884\ttrans\t1018\t973\t0\t.\n+A_92_P037023\t274\t10\t12\t1.3982\t12\t1.4654\t12\t1.4654\t17.3874606\t0.1323351\t0.4565953\t106.0068081\ttrans\t1018\t544\t0\t.\n+A_92_P024198\t450\t10\t12\t1.3915\t12\t1.4654\t12\t1.4654\t17.6795574\t0.1260373\t0.4285465\t151.8217473\ttrans\t1018\t979\t0\t.\n+A_92_P032670\t404\t10\t12\t1.3545\t12\t1.4654\t12\t1.4654\t17.8113247\t0.1484826\t0.374541\t136.8270242\ttrans\t1018\t250\t0\t.\n+A_92_P023362\t92\t10\t12\t1.4232\t12\t1.4654\t12\t1.4654\t17.9370876\t0.2274342\t0.4691999\t37.6169444\ttrans\t1018\t878\t0\t.\n+A_92_P026076\t337\t10\t12\t1.3786\t12\t1.4654\t12\t1.4654\t18.846987\t0.1799499\t0.4903461\t27.9365639\ttrans\t1018\t899\t0\t.\n+A_92_P017582\t504\t10\t12\t1.4185\t12\t1.4654\t12\t1.4654\t18.8476534\t0.1805079\t0.4249404\t21.8416197\ttrans\t1018\t544\t0\t.\n+A_92_P025425\t410\t10\t12\t1.4043\t12\t1.4654\t12\t1.4654\t18.8789084\t0.1657852\t0.3476669\t48.4248141\ttrans\t1018\t470\t0\t.\n+A_92_P022234\t341\t10\t12\t1.3865\t12\t1.4654\t12\t1.4654\t19.1075367\t0.2133459\t0.4348225\t57.420108\ttrans\t1018\t212\t0\t.\n+A_92_P025306\t112\t10\t12\t1.3958\t12\t1.4654\t12\t1.4654\t19.3425356\t0.1482326\t0.3938621\t52.402676\ttrans\t1018\tNA\t0\t.\n+A_92_P009598\t541\t10\t12\t1.3937\t12\t1.4654\t12\t1.4654\t19.5381805\t0.1251372\t0.6625968\t-712.4099878\ttrans\t1018\t229\t0\t.\n+A_92_P024212\t422\t10\t12\t1.3992\t12\t1.4654\t12\t1.4654\t19.6064977\t0.2375823\t0.5002322\t52.7638845\ttrans\t1018\t19\t0\t.\n+A_92_P026028\t79\t10\t12\t1.3914\t12\t1.4654\t12\t1.4654\t20.3992708\t0.1855026\t0.3085852\t93.1442027\ttrans\t1018\t661\t0\t.\n+A_92_P021863\t515\t10\t12\t1.4073\t12\t1.4654\t12\t1.4654\t20.5831168\t0.1885752\t0.3996008\t46.6019616\ttrans\t1018\t470\t0\t.\n+A_92_P019500\t527\t10\t12\t1.3909\t12\t1.4654\t12\t1.4654\t20.7811533\t0.2171057\t0.5712754\t48.5459071\ttrans\t1018\tNA\t0\t.\n+A_92_P018605\t411\t10\t12\t1.4\t12\t1.4654\t12\t1.4654\t21.1040807\t0.2470094\t0.4272557\t18.6917552\ttrans\t1018\t430\t0\t.\n+A_92_P040676\t462\t10\t12\t1.4196\t12\t1.4654\t12\t1.4654\t21.4474993\t0.183169\t0.3762722\t222.4201279\ttrans\t1018\t18\t0\t.\n+A_92_P028742\t340\t10\t12\t1.4343\t12\t1.4654\t12\t1.4654\t23.5373748\t0.2466954\t0.3766208\t-65.1331884\ttrans\t1018\tNA\t0\t.\n+A_92_P025620\t43\t10\t12\t1.3991\t12\t1.4654\t12\t1.4654\t23.9309014\t0.2736644\t0.4796374\t116.16188\ttrans\t1018\t804\t0\t.\n+A_92_P016350\t531\t10\t12\t1.4083\t12\t1.4654\t12\t1.4654\t24.3372991\t0.1321456\t0.5915645\t915.05996\ttrans\t1018\t539\t0\t.\n+A_92_P034395\t281\t10\t12\t1.4188\t12\t1.4654\t12\t1.4654\t24.5032178\t0.2368342\t0.4777931\t953.68815\ttrans\t1018\t823\t0\t.\n+A_92_P019294\t257\t10\t12\t1.4275\t12\t1.4654\t12\t1.4654\t25.007352\t0.2890627\t0.560038\t29.7095764\ttrans\t1018\t282\t0\t.\n+A_92_P028902\t346\t10\t12\t1.4242\t12\t1.4654\t12\t1.4654\t25.7049413\t0.2114093\t0.5586152\t-39.2568299\ttrans\t1018\tNA\t0\t.\n+A_92_P033721\t509\t10\t12\t1.4111\t12\t1.4654\t12\t1.4654\t26.3758182\t0.3486156\t0.5568993\t58.1042743\ttrans\t1018\t850\t0\t.\n+A_92_P017792\t494\t10\t12\t1.4226\t12\t1.4654\t12\t1.4654\t28.3108534\t0.3267935\t0.5538729\t50.1565754\ttrans\t1018\t900\t0\t.\n+A_92_P029608\t28\t10\t12\t1.3811\t12\t1.4654\t12\t1.4654\t29.7148963\t0.1541602\t0.6267279\t-98.5869791\ttrans\t1018\tNA\t0\t.\n+A_92_P038669\t350\t10\t12\t1.4122\t12\t1.4654\t12\t1.4654\t30.2337867\t0.3997162\t0.5304303\t63.9955185\ttrans\t1018\t676\t0\t.\n' |
| b |
| diff -r 000000000000 -r 0b383b61074d hotspots/test-data/output/trans_hotspots_out.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/hotspots/test-data/output/trans_hotspots_out.txt Fri Mar 18 05:26:20 2016 -0400 |
| b |
| b'@@ -0,0 +1,844 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0\t38.0\t10.5\t0\t1\t\t\n+834\t10\t4.0\t19.0\t26.0\t4.75\t0\t0\t\t\n+835\t10\t4.0\t15.0\t20.0\t3.75\t0\t0\t\t\n+836\t10\t4.9\t31.0\t38.0\t6.33\t0\t0\t\t\n+837\t10\t4.0\t19.0\t33.0\t4.75\t0\t0\t\t\n+838\t10\t4.0\t8.0\t48.0\t2.0\t0\t0\t\t\n+839\t10\t4.0\t10.0\t60.0\t2.5\t0\t0\t\t\n+840\t10\t4.0\t5.0\t49.0\t1.25\t0\t0\t\t\n+841\t10\t4.0\t7.0\t53.0\t1.75\t0\t0\t\t\n+842\t10\t4.0\t18.0\t57.0\t4.5\t0\t0\t\t\n+843\t10\t4.95\t140.0\t43.0\t28.28\t1\t1\t*\t21\n' |
| b |
| diff -r 000000000000 -r 0b383b61074d hotspots/threshold_chisq.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/hotspots/threshold_chisq.txt Fri Mar 18 05:26:20 2016 -0400 |
| [ |
| @@ -0,0 +1,93 @@ +#setwd("/Users/nanettecoetzer/Documents/Bioinformatics/MAIZE_project/eQTL_pipeline/April_2012_pipeline_scripts/July_2012/output_July") + +perm_threshold <- function(p, cm, eqtl) { + m=c() + for (j in 1:p) { + d=c() + x=sample(1:cm, eqtl, replace=T) + for (i in 1:cm) { + s=length(which(x==i)) + d=c(d,s) + } + m=c(m,max(d)) + } +t <- quantile(m, 0.95) +return(t) +} + +chisq_test <- function(m, tot_eqtls, tot_genes, total) { + ans <- c() + for (i in 1:dim(m)[1]) { + c <- chisq.test(m[i,2:3],p=c(tot_eqtls/total,tot_genes/total)) + if (c$p.value < 0.0001 & m[i,4] == 0) { + eqtl_excess_calc = m[i,2]/(m[i,2]+m[i,3]) + + if (eqtl_excess_calc > tot_eqtls/total) { + ans = c(ans, 1) + } + else { + ans = c(ans, -1) + } + + } + else { + ans = c(ans, 0) + } + } + list(ans=ans, exp=exp) +} + +# threshold +summary = read.table("frequency_summary.txt",sep="\t") +num.cm = summary[5,2] +num.perm = summary[10,2] +num.genes = summary[4,2] + +num.all.eqtl = summary[1,2] +num.cis.eqtl = summary[2,2] +num.trans.eqtl = summary[3,2] + +#print(num.perm) +threshold.all <- perm_threshold(p=num.perm,cm=num.cm,eqtl=num.all.eqtl) +threshold.cis <- perm_threshold(p=num.perm,cm=num.cm,eqtl=num.cis.eqtl) +threshold.trans <- perm_threshold(p=num.perm,cm=num.cm,eqtl=num.trans.eqtl) + + +# chi-squared test +#summary <- read.table("freq_summary.txt", header=F, sep="\t") +d <- read.table("sliding_frequency.txt", header=T, sep="\t") + +# calculate the cut-off value so that the expected value of each cell (num.eQTLs and num.genes) is > 5 +# chisq test --> all +total.all = num.genes + num.all.eqtl +t.all = 5* total.all/min(num.genes, num.all.eqtl) +genes_div_total.all = num.genes/total.all +eqtl_div_total.all = num.all.eqtl/total.all + +# chisq test --> cis +total.cis = num.genes + num.cis.eqtl +t.cis = 5* total.cis/min(num.genes, num.cis.eqtl) +genes_div_total.cis = num.genes/total.cis +eqtl_div_total.cis = num.cis.eqtl/total.cis + +# chisq test --> trans +total.trans = num.genes + num.trans.eqtl +t.trans = 5*total.trans/min(num.genes, num.trans.eqtl) +genes_div_total.trans = num.genes/total.trans +eqtl_div_total.trans = num.trans.eqtl/total.trans + +write.table(c(threshold.all ,t.all ,genes_div_total.all, eqtl_div_total.all, threshold.cis ,t.cis ,genes_div_total.cis, eqtl_div_total.cis, threshold.trans, t.trans, genes_div_total.trans, eqtl_div_total.trans), file="threshold_chisq_summary.txt") + + +s.all = cbind(d$sliding.id,d$sliding.all.eQTL,d$sliding.genes,d$sliding.genes+d$sliding.all.eQTL<t.all, d$sliding.cM,d$chr) +s.cis = cbind(d$sliding.id,d$sliding.cis.eQTL,d$sliding.genes,d$sliding.genes+d$sliding.cis.eQTL<t.cis, d$sliding.cM,d$chr) +s.trans = cbind(d$sliding.id,d$sliding.trans.eQTL,d$sliding.genes,d$sliding.genes+d$sliding.trans.eQTL<t.trans, d$sliding.cM,d$chr) + +a.all <- chisq_test(m=s.all, num.all.eqtl, num.genes, total.all) +a.cis <- chisq_test(m=s.cis, num.cis.eqtl, num.genes, total.cis) +a.trans <- chisq_test(m=s.trans, num.trans.eqtl, num.genes, total.trans) + +write.table(cbind(s.all, a.all$ans),"chisq_out_all.txt") +write.table(cbind(s.cis, a.cis$ans),"chisq_out_cis.txt") +write.table(cbind(s.trans, a.trans$ans),"chisq_out_trans.txt") + |
| b |
| diff -r 000000000000 -r 0b383b61074d hotspots/tool_dependencies.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/hotspots/tool_dependencies.xml Fri Mar 18 05:26:20 2016 -0400 |
| b |
| @@ -0,0 +1,6 @@ +<tool_dependency> + <set_environment version="1.0"> + <environment_variable name="R_SCRIPT_PATH" action="set_to">$REPOSITORY_INSTALL_DIR</environment_variable> + </set_environment> +</tool_dependency> + |