Mercurial > repos > nanettec > frequency_sliding
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/frequency_sliding/eqtl_genes_polygon_plot.txt Fri Mar 18 05:22:30 2016 -0400 @@ -0,0 +1,43 @@ +# polygon eqtl + genes plots + +#setwd("/Users/nanettecoetzer/Documents/Bioinformatics/MAIZE_project/eQTL_pipeline/April_2012_pipeline_scripts/July_2012") +data <- read.table("sliding_frequency.txt",sep="\t",header=TRUE) +num.chr = max(data[,2]) + + +pdf(paste("Rplot_eQTL_genes_polygon.pdf",sep=""),width=20,height=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)) + } + +len_trans <- length(data[,6]) +max_trans <- sort(data[,6])[len_trans-3] + +for (k in 1:num.chr) { + bin1 <- data[data[,2]==k,1] + bin <- c(1:length(bin1)) + cis <- data[data[,2]==k,5] + trans <- data[data[,2]==k,6] + genes <- data[data[,2]==k,7] + m = max(trans) + + plot(bin,trans, ylim=c(0, max_trans), type="n",col="red", lwd=1, ylab="Frequency",main=paste("Chr ",k),xlab="Sliding window bins") + polygon(c(0,genes,0),col="green",border="green") + polygon(c(0,trans,0),col="red",border="red") + polygon(c(0,cis,0),col="blue",border="blue") + x <- 2.2*(max(bin)/3) + legend(x,max_trans,c("genes","trans","cis"),col=c("green","red","blue"),lty=1,lwd=2) + } +dev.off() \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/frequency_sliding/frequency_sliding.py Fri Mar 18 05:22:30 2016 -0400 @@ -0,0 +1,345 @@ +""" +@summary: Calculate the frequency of eQTLs and genes per sliding window bin +@author: nanette.coetzer@gmail.com +@version 5 + +""" +import optparse, sys +import subprocess +import tempfile +import os, re + +def stop_err( msg ): + sys.stderr.write( "%s\n" % msg ) + sys.exit() + +def __main__(): + #Parse Command Line + parser = optparse.OptionParser() + parser.add_option("-m", "--rscript", default=None, dest="rscript", + help="R script") + parser.add_option("-i", "--input1", default=None, dest="input1", + help="Frequency per bin file") + parser.add_option("-j", "--input2", default=None, dest="input2", + help="Lookup summary file") + parser.add_option("-k", "--input3", default=None, dest="input3", + help="Frequency summary file") + parser.add_option("-o", "--output1", default=None, dest="output1", + help="Sliding frequency file") + parser.add_option("-p", "--output2", default=None, dest="output2", + help="Sliding lookup file") + parser.add_option("-q", "--output3", default=None, dest="output3", + help="eQTL and genes polygon plot") + (options, args) = parser.parse_args() + + try: + open(options.input1, "r").close() + except TypeError, e: + stop_err("You need to supply the Lookup frequency file:\n" + str(e)) + except IOError, e: + stop_err("Can not open the Lookup frequency file:\n" + str(e)) + + try: + open(options.input2, "r").close() + except TypeError, e: + stop_err("You need to supply the Lookup summary file:\n" + str(e)) + except IOError, e: + stop_err("Can not open the Lookup summary file:\n" + str(e)) + + try: + open(options.input3, "r").close() + except TypeError, e: + stop_err("You need to supply the Frequency summary file:\n" + str(e)) + except IOError, e: + stop_err("Can not open the Frequency summary file:\n" + str(e)) + + ############################################## + ############################################## + + infile3 = open(options.input3,'r') # Frequency summary file + for line in infile3: + if line.startswith("Number"): + num_intervals = int(line.strip().split("\t")[1]) + #print num_intervals + infile3.close() + + chr_second_last = [] + chr_end = [] + tot = 0 + infile2 = open(options.input2,'r') # Lookup summary file + for line in infile2: + l = line.strip().split("\t") + if not l[4].startswith("i"): + tot += int(l[4]) + chr_second_last.append(tot-2) + chr_end.append(tot) + + freq_dict = {} + sliding_id = 0 + prev_size = 0 + idlist = [] + slidingdict = {} + cur_size = 0 + add_last = 0 + i = 0 + sizelist = [] + + infile1 = open(options.input1,'r') # Frequency.txt + + # 1b is where an interval always starts with a 2cM bin (plus a small bin if available) --> never split 2 bins on either sides of a marker + if num_intervals == 1: + for line in infile1: + l2 = line.strip().split("\t") + if not l2[0].startswith("int"): + i += 1 + freq_dict[l2[0]] = l2 + if prev_size == 0: + # end of chromosome + if int(l2[0]) in chr_end: + pass + else: + prev_size = float(l2[6]) + idlist.append(int(l2[0])) + sizelist.append(float(l2[6])) + cur_size = float(l2[6]) + add_last = 0 + else: + prev_size = float(l2[6]) + + if prev_size < 2 and add_last == 0: + cur_size = float(cur_size) + float(l2[6]) + idlist.append(int(l2[0])) + sizelist.append(float(l2[6])) + elif prev_size == 2: + sliding_id = sliding_id + 1 + slidingdict[int(sliding_id)] = idlist + idlist = [int(l2[0])] + sizelist = [float(l2[6])] + prev_size = float(l2[6]) + cur_size = float(l2[6]) + + if add_last == 1: + cur_size = float(cur_size) + float(l2[6]) + idlist.append(int(l2[0])) + sizelist.append(float(l2[6])) + sliding_id = sliding_id + 1 + slidingdict[sliding_id] = idlist + prev_size = 0 + idlist = [] + sizelist = [] + cur_size = 0 + + if int(l2[0]) in chr_second_last: + add_last = 1 + + # 1 is where an interval starts with a small bin if available (plus a 2cM bin) + if num_intervals == 9: + for line in infile1: + l2 = line.strip().split("\t") + if not l2[0].startswith("int"): + i += 1 + freq_dict[l2[0]] = l2 + print slidingdict + if prev_size == 0: + # end of chromosome + if int(l2[0]) in chr_end: + pass + else: + prev_size = float(l2[6]) + idlist.append(int(l2[0])) + cur_size = float(l2[6]) + add_last = 0 + if float(cur_size) >= 2 and add_last == 0: + sliding_id = sliding_id + 1 + slidingdict[int(sliding_id)] = idlist + + prev_size = float(l2[6]) + idlist = [] + cur_size = float(0) + else: + cur_size = float(cur_size) + float(l2[6]) + idlist.append(int(l2[0])) + prev_size = float(l2[6]) + if add_last == 1: + sliding_id = sliding_id + 1 + slidingdict[sliding_id] = idlist + prev_size = 0 + idlist = [] + cur_size = 0 + + if int(l2[0]) in chr_second_last: + add_last = 1 + if float(cur_size) >= 2 and add_last == 0: + sliding_id = sliding_id + 1 + slidingdict[int(sliding_id)] = idlist + prev_size = float(l2[6]) + idlist = [] + cur_size = float(0) + + + if num_intervals == 2: + for line in infile1: + l2 = line.strip().split("\t") + if not l2[0].startswith("int"): + i += 1 + freq_dict[l2[0]] = l2 + if prev_size == 0: + # end of chromosome + if int(l2[0]) in chr_end: + pass + else: + prev_size = float(l2[6]) + idlist.append(int(l2[0])) + cur_size = float(l2[6]) + add_last = 0 + else: + cur_size = float(cur_size) + float(l2[6]) + idlist.append(int(l2[0])) + prev_size = float(l2[6]) + if add_last == 1: + sliding_id = sliding_id + 1 + slidingdict[sliding_id] = idlist + prev_size = 0 + idlist = [] + cur_size = 0 + + if int(l2[0]) in chr_second_last: + add_last = 1 + if float(cur_size) >= 4 and add_last == 0: + sliding_id = sliding_id + 1 + slidingdict[int(sliding_id)] = idlist + + prev_size = float(l2[6]) + idlist = [int(l2[0])] + cur_size = float(prev_size) + + if num_intervals == 3: + for line in infile1: + l2 = line.strip().split("\t") + if not l2[0].startswith("int"): + i += 1 + freq_dict[l2[0]] = l2 + if prev_size == 0: + # end of chromosome + if int(l2[0]) in chr_end: + pass + else: + prev_size = float(l2[6]) + idlist.append(int(l2[0])) + sizelist.append(float(l2[6])) + cur_size = float(l2[6]) + add_last = 0 + else: + cur_size = float(cur_size) + float(l2[6]) + idlist.append(int(l2[0])) + sizelist.append(float(l2[6])) + prev_size = float(l2[6]) + if add_last == 1: + sliding_id = sliding_id + 1 + slidingdict[sliding_id] = idlist + prev_size = 0 + idlist = [] + sizelist = [] + cur_size = 0 + + if int(l2[0]) in chr_second_last: + add_last = 1 + if float(cur_size) >= 6 and add_last == 0: + sliding_id = sliding_id + 1 + slidingdict[int(sliding_id)] = idlist + prev_size = float(l2[6]) + newsizelist = [] + newidlist = [] + newstart = 0 + c = 0 + cur_size = 0 + for s in range(len(sizelist)): + if newstart == 1: + newsizelist.append(sizelist[s]) + newidlist.append(idlist[s]) + cur_size += float(sizelist[s]) + if sizelist[s] == 2.0 and newstart == 0: + c += 1 + if c == 2: + newsizelist.append(sizelist[s]) + newidlist.append(idlist[s]) + cur_size += float(sizelist[s]) + newstart = 1 + idlist = newidlist + sizelist = newsizelist + + out1 = open(options.output1,'w') # Frequency.txt + out2 = open(options.output2,'w') + #out1.write("sliding.id\tchr\tsliding.cM\tsliding.eQTL\tsliding.cis.eQTL\tsliding.trans.eQTL\tsliding.genes\tsliding.eQTL/cM\tsliding.eQTL/cM/10genes\n") + out1.write("sliding.id\tchr\tsliding.cM\tsliding.all.eQTL\tsliding.cis.eQTL\tsliding.trans.eQTL\tsliding.genes\tsliding.all.eQTL/cM\tsliding.cis.eQTL/cM\tsliding.trans.eQTL/cM\tsliding.genes/cM\n") + tcM = 0 + tEQTL = 0 + tGENES = 0 + + for j in range(len(slidingdict.keys())): + totcM = 0 + toteqtl = 0 + totcis = 0 + tottrans = 0 + totgenes = 0 + totEcM_all = 0 + totEcM_cis = 0 + totEcM_trans = 0 + totGcM = 0 + #totEcM10G = 0 + out2.write(str(j+1)+"\t"+str(slidingdict[j+1])+"\n") + for k in slidingdict[j+1]: + totcM += float(freq_dict[str(k)][6]) + toteqtl += float(freq_dict[str(k)][7]) + totcis += float(freq_dict[str(k)][8]) + tottrans += float(freq_dict[str(k)][9]) + totgenes += float(freq_dict[str(k)][10]) + + chr = freq_dict[str(k)][1] + if totgenes == 0: + totgenes = 1 + + totEcM_all += round((toteqtl/totcM),2) + totEcM_cis += round((totcis/totcM),2) + totEcM_trans += round((tottrans/totcM),2) + totGcM += round((totgenes/totcM),2) + out1.write(str(j+1)+"\t"+str(chr)+"\t"+str(totcM)+"\t"+str(toteqtl)+"\t"+str(totcis)+"\t"+str(tottrans)+"\t"+str(totgenes)+"\t"+str(totEcM_all)+"\t"+str(totEcM_cis)+"\t"+str(totEcM_trans)+"\t"+str(totGcM)+"\n") + + out1.close() + infile1.close() + infile2.close() + out2.close() + + + # Create temp direcotry + tempdir = tempfile.mkdtemp() + + # copy INPUT file to the temp directory + s = "cp %s %s/sliding_frequency.txt" %(options.output1, tempdir) + subprocess.call(s, shell=True) + + # create R script => save in temp directory + # generate new header + new_script = open(tempdir+"/new_script.r","w") + header = "setwd(\"%s\")" %tempdir + new_script.write(header+"\n") + # add script body + script = open(options.rscript,"r") + for line in script: + new_script.write(line.strip()+"\n") + new_script.close() + + # run R script from temp directory + s = "R CMD BATCH %s/new_script.r out.txt" %tempdir + subprocess.call(s, shell=True) + + # run R script from temp directory + s = "R CMD BATCH %s/new_script.r out.txt" %tempdir + subprocess.call(s, shell=True) + + os.system("mv %s/Rplot_eQTL_genes_polygon.pdf %s" %(tempdir,options.output3)) + + ############################################## + +if __name__=="__main__": + __main__()
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/frequency_sliding/frequency_sliding.xml Fri Mar 18 05:22:30 2016 -0400 @@ -0,0 +1,132 @@ +<tool id="sliding_frequency5" name="Sliding Window frequency" version="5.0.0"> + <description>of eQTLs and genes</description> + <command interpreter="python"> + frequency_sliding.py --rscript \$R_SCRIPT_PATH/frequency_sliding/eqtl_genes_polygon_plot.txt --input1 $input1 --input2 $input2 --input3 $input3 --output1 $output1 --output2 $output2 --output3 $output3 + </command> + <inputs> + <param label="Frequency per bin file" name="input1" type="data" format="tabular" help="A tabular file with eQTL and gene frequencies for each interval."></param> + <param label="Lookup summary file" name="input2" type="data" format="tabular" help="A tabular file number of cM, bp, inteval positions and bins on each chromosome."></param> + <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> + </inputs> + <outputs> + <data format="tabular" name="output1" /> + <data format="tabular" name="output2" /> + <data format="pdf" name="output3" /> + </outputs> + <requirements> + <requirement type="set_environment">R_SCRIPT_PATH</requirement> + </requirements> + <tests> + <test> + </test> + </tests> + <help> + +**What it does** + +Combine x cM intervals (size of lookup bins; for example 2 cM), to be used in a sliding window approach. + +For 2 cM lookup bins: + +* For two intervals per sliding window, intervals smaller than 2 cM are combined with its two flanking 2 cM intervals. + +Calculate the number of eQTLs per sliding window (4 - 5.9 cM intervals). + +Calculate the number of genes per sliding window (4 - 5.9 cM intervals). + +* For three intervals per sliding window, intervals smaller than 2 cM are combined with 3 flanking 2 cM intervals. + +Calculate the number of eQTLs per sliding window (6 - 7.9 cM intervals). + +Calculate the number of genes per sliding window (6 - 7.9 cM intervals). + +------- + +**Example input files** + +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):: + + int.id chr marker interval cM bp length_cM num.eQTL.all num.eQTL.cis num.eQTL.trans num.genes + 1 1 1 0.0001 0.0 2038278 2.0 94.0 2.0 64.0 12.0 + 2 1 1 0.0201 2.0 2466324 2.0 17.0 3.0 11.0 34.0 + 3 1 1 0.0401 4.0 2894370 2.0 8.0 2.0 5.0 29.0 + 4 1 1 0.0601 6.0 3322416 1.53 11.0 5.0 3.0 10.0 + 5 1 2 0.0754 7.53 3649871 2.0 27.0 6.0 19.0 18.0 + 6 1 2 0.0954 9.53 4095673 2.0 8.0 4.0 3.0 12.0 + 7 1 2 0.1154 11.53 4541476 2.0 4.0 2.0 2.0 17.0 + 8 1 2 0.1354 13.53 4987278 2.0 8.0 4.0 2.0 19.0 + 9 1 2 0.1554 15.53 5433081 2.0 5.0 0 3.0 15.0 + + +Chromosome summary file, each row correspond to a chromosome (6 columns; only a part of the file is shown). The last row gives the total across the genome:: + + chr markers cM bp int_positions bins + 1 27 324.4 301354135 177 176 + 2 14 169.11 237068873 92 91 + 3 19 221.29 232140174 123 122 + 4 20 188.37 241473504 105 104 + 5 20 203.82 217872852 110 109 + 6 17 195.85 169174353 106 105 + Total 117 1302.84 1399083891 713 707 + + +Frequency summary file (2 columns):: + + Total number of eQTLs (all) 31549 + Total number of cis-eQTLs 4863 + Total number of trans-eQTLs 21428 + Total number of genes 31036 + Total number of cM 1861.57 + Expected number of eQTL per cM (all) 16.95 + Expected number of cis-eQTL per cM 2.61 + Expected number of trans-eQTL per cM 11.51 + Expected number of genes per cM 16.67 + User specified number of permutations 1000 + Number of intervals per sliding window 2 + +------- + +**Example output files** + + +Sliding frequency file: Frequency of eQTLs and genes per sliding window interval (4 - 5.9 cM) output file, each row correspond to a sliding window interval (11 columns; only a part of the file is shown):: + + sliding.id chr sliding.cM sliding.all.eQTL sliding.cis.eQTL sliding.trans.eQTL sliding.genes sliding.all.eQTL/cM sliding.cis.eQTL/cM sliding.trans.eQTL/cM sliding.genes/cM + 1 1 4.0 111.0 5.0 75.0 46.0 27.75 1.25 18.75 11.5 + 2 1 4.0 25.0 5.0 16.0 63.0 6.25 1.25 4.0 15.75 + 3 1 5.53 46.0 13.0 27.0 57.0 8.32 2.35 4.88 10.31 + 4 1 4.0 35.0 10.0 22.0 30.0 8.75 2.5 5.5 7.5 + 5 1 4.0 12.0 6.0 5.0 29.0 3.0 1.5 1.25 7.25 + 6 1 4.0 12.0 6.0 4.0 36.0 3.0 1.5 1.0 9.0 + 7 1 4.0 13.0 4.0 5.0 34.0 3.25 1.0 1.25 8.5 + 8 1 5.24 67.0 5.0 46.0 41.0 12.79 0.95 8.78 7.82 + 9 1 4.0 57.0 5.0 39.0 53.0 14.25 1.25 9.75 13.25 + 10 1 4.0 13.0 3.0 9.0 58.0 3.25 0.75 2.25 14.5 + 11 1 4.0 11.0 3.0 5.0 54.0 2.75 0.75 1.25 13.5 + 12 1 4.0 11.0 4.0 3.0 35.0 2.75 1.0 0.75 8.75 + +Map sliding window IDs (first column) to lookup table IDs (second column) (2 columns; only a part of the file is shown):: + + 1 [1, 2] + 2 [2, 3] + 3 [3, 4, 5] + 4 [5, 6] + 5 [6, 7] + 6 [7, 8] + 7 [8, 9] + 8 [9, 10, 11] + 9 [11, 12] + 10 [12, 13] + 11 [13, 14] + 12 [14, 15] + 13 [15, 16] + 14 [16, 17] + 15 [17, 18] + 16 [18, 19] + 17 [19, 20, 21] + +Frequency per cM plot of cis-eQTL, trans-eQTL and genes (in pdf format, produced using R). + + + </help> +</tool>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/frequency_sliding/readme.txt Fri Mar 18 05:22:30 2016 -0400 @@ -0,0 +1,32 @@ +====================================================================== +frequency_sliding +====================================================================== +### This is the fourth 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 + +Combine x cM intervals (size of lookup bins; for example 2 cM), to be used in a sliding window approach. + +For 2 cM lookup bins: + +* For two intervals per sliding window, intervals smaller than 2 cM are combined with its two flanking 2 cM intervals. +Calculate the number of eQTLs per sliding window (4 - 5.9 cM intervals). +Calculate the number of genes per sliding window (4 - 5.9 cM intervals). + +* For three intervals per sliding window, intervals smaller than 2 cM are combined with 3 flanking 2 cM intervals. +Calculate the number of eQTLs per sliding window (6 - 7.9 cM intervals). +Calculate the number of genes per sliding window (6 - 7.9 cM intervals). + + +--------------- +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
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/frequency_sliding/test-data/input/chr_summary.txt Fri Mar 18 05:22:30 2016 -0400 @@ -0,0 +1,12 @@ +chr markers cM bp interval positions bins +1 27 324.4 301354135 177 176 +2 14 169.11 237068873 92 91 +3 19 221.29 232140174 123 122 +4 20 188.37 241473504 105 104 +5 20 203.82 217872852 110 109 +6 17 195.85 169174353 106 105 +7 12 111.16 176764762 63 62 +8 14 141.31 175793759 77 76 +9 11 158.78 156750706 85 84 +10 13 147.48 150189435 81 80 +Total 167 1861.57 2058582553 1019 1009
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/frequency_sliding/test-data/input/frequency.txt Fri Mar 18 05:22:30 2016 -0400 @@ -0,0 +1,1020 @@ +int.id chr marker interval cM bp length_cM num.eQTL.all num.eQTL.cis num.eQTL.trans num.genes +1 1 1 0.0001 0.0 2038278 2.0 39.0 6.0 26.0 12.0 +2 1 1 0.0201 2.0 2466324 2.0 11.0 2.0 7.0 34.0 +3 1 1 0.0401 4.0 2894370 2.0 6.0 3.0 3.0 29.0 +4 1 1 0.0601 6.0 3322416 1.53 8.0 3.0 5.0 10.0 +5 1 2 0.0754 7.53 3649871 2.0 37.0 11.0 21.0 18.0 +6 1 2 0.0954 9.53 4095673 2.0 7.0 3.0 3.0 12.0 +7 1 2 0.1154 11.53 4541476 2.0 5.0 1.0 4.0 17.0 +8 1 2 0.1354 13.53 4987278 2.0 7.0 4.0 2.0 19.0 +9 1 2 0.1554 15.53 5433081 2.0 6.0 2.0 2.0 15.0 +10 1 2 0.1754 17.53 5878883 1.24 9.0 1.0 8.0 4.0 +11 1 3 0.1878 18.77 6155281 2.0 26.0 4.0 19.0 22.0 +12 1 3 0.2078 20.77 6781464 2.0 3.0 1.0 2.0 31.0 +13 1 3 0.2278 22.77 7407646 2.0 6.0 2.0 4.0 27.0 +14 1 3 0.2478 24.77 8033829 2.0 2.0 0 1.0 27.0 +15 1 3 0.2678 26.77 8660012 2.0 4.0 3.0 0 8.0 +16 1 3 0.2878 28.77 9286194 2.0 2.0 0 1.0 14.0 +17 1 3 0.3078 30.77 9912377 2.0 3.0 1.0 2.0 12.0 +18 1 3 0.3278 32.77 10538560 2.0 6.0 2.0 2.0 14.0 +19 1 3 0.3478 34.77 11164742 2.0 14.0 3.0 6.0 11.0 +20 1 3 0.3678 36.77 11790925 1.94 22.0 2.0 16.0 29.0 +21 1 4 0.3872 38.71 12398322 2.0 88.0 10.0 64.0 19.0 +22 1 4 0.4072 40.71 12998447 2.0 10.0 1.0 7.0 9.0 +23 1 4 0.4272 42.71 13598572 1.91 5.0 0 4.0 20.0 +24 1 5 0.4463 44.62 14171692 2.0 16.0 4.0 8.0 26.0 +25 1 5 0.4663 46.62 15319046 2.0 3.0 0 1.0 38.0 +26 1 5 0.4863 48.62 16466401 0.11 0 0 0 0 +27 1 6 0.4874 48.73 16529505 2.0 17.0 5.0 8.0 23.0 +28 1 6 0.5074 50.73 17676859 2.0 4.0 2.0 1.0 34.0 +29 1 6 0.5274 52.73 18824214 0.48 11.0 5.0 5.0 4.0 +30 1 7 0.5322 53.21 19099579 2.0 15.0 7.0 7.0 38.0 +31 1 7 0.5522 55.21 20991425 2.0 5.0 3.0 1.0 58.0 +32 1 7 0.5722 57.21 22883271 2.0 9.0 7.0 2.0 35.0 +33 1 7 0.5922 59.21 24775117 2.0 3.0 1.0 2.0 58.0 +34 1 7 0.6122 61.21 26666963 2.0 3.0 2.0 1.0 45.0 +35 1 7 0.6322 63.21 28558809 2.0 3.0 1.0 2.0 24.0 +36 1 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10 7 0.8756 87.55 135145732 2.0 23.0 4.0 14.0 26.0 +987 10 7 0.8956 89.55 136540391 1.07 30.0 0 26.0 15.0 +988 10 8 0.9063 90.62 137286534 2.0 189.0 3.0 165.0 5.0 +989 10 8 0.9263 92.62 137578907 2.0 36.0 0 29.0 6.0 +990 10 8 0.9463 94.62 137871280 2.0 15.0 2.0 13.0 5.0 +991 10 8 0.9663 96.62 138163653 2.0 16.0 1.0 12.0 10.0 +992 10 8 0.9863 98.62 138456026 0.05 6.0 1.0 4.0 0 +993 10 9 0.9868 98.67 138463335 2.0 25.0 0 21.0 13.0 +994 10 9 1.0068 100.67 138982567 2.0 8.0 2.0 6.0 8.0 +995 10 9 1.0268 102.67 139501799 1.93 14.0 0 12.0 15.0 +996 10 10 1.0461 104.6 140002858 2.0 56.0 8.0 41.0 13.0 +997 10 10 1.0661 106.6 140522090 2.0 15.0 5.0 9.0 16.0 +998 10 10 1.0861 108.6 141041322 2.0 26.0 7.0 16.0 16.0 +999 10 10 1.1061 110.6 141560554 2.0 19.0 4.0 12.0 34.0 +1000 10 10 1.1261 112.6 142079786 2.0 28.0 4.0 19.0 25.0 +1001 10 10 1.1461 114.6 142599018 2.0 41.0 2.0 32.0 27.0 +1002 10 10 1.1661 116.6 143118250 1.03 36.0 4.0 27.0 14.0 +1003 10 11 1.1764 117.63 143385654 2.0 128.0 1.0 110.0 27.0 +1004 10 11 1.1964 119.63 143836329 2.0 54.0 4.0 45.0 9.0 +1005 10 11 1.2164 121.63 144287005 2.0 34.0 0 30.0 24.0 +1006 10 11 1.2364 123.63 144737680 2.0 17.0 0 12.0 14.0 +1007 10 11 1.2564 125.63 145188355 2.0 11.0 2.0 7.0 12.0 +1008 10 11 1.2764 127.63 145639031 2.0 10.0 2.0 8.0 8.0 +1009 10 11 1.2964 129.63 146089706 0.9 10.0 3.0 6.0 9.0 +1010 10 12 1.3054 130.53 146292510 2.0 27.0 2.0 17.0 21.0 +1011 10 12 1.3254 132.53 146699702 2.0 9.0 6.0 2.0 12.0 +1012 10 12 1.3454 134.53 147106895 2.0 13.0 6.0 6.0 36.0 +1013 10 12 1.3654 136.53 147514087 2.0 7.0 2.0 4.0 24.0 +1014 10 12 1.3854 138.53 147921279 2.0 1.0 0 1.0 25.0 +1015 10 12 1.4054 140.53 148328472 2.0 9.0 2.0 6.0 28.0 +1016 10 12 1.4254 142.53 148735664 2.0 19.0 3.0 12.0 29.0 +1017 10 12 1.4454 144.53 149142856 2.0 52.0 4.0 40.0 5.0 +1018 10 12 1.4654 146.53 149550049 0.95 125.0 9.0 88.0 9.0 +1019 10 13 1.4749 147.48 149743465 0 0 0 0 0
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/frequency_sliding/test-data/input/frequency_summary.txt Fri Mar 18 05:22:30 2016 -0400 @@ -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
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/frequency_sliding/test-data/output/sliding_frequency.txt Fri Mar 18 05:22:30 2016 -0400 @@ -0,0 +1,844 @@ +sliding.id chr sliding.cM sliding.all.eQTL sliding.cis.eQTL sliding.trans.eQTL sliding.genes sliding.all.eQTL/cM sliding.cis.eQTL/cM sliding.trans.eQTL/cM sliding.genes/cM +1 1 4.0 50.0 8.0 33.0 46.0 12.5 2.0 8.25 11.5 +2 1 4.0 17.0 5.0 10.0 63.0 4.25 1.25 2.5 15.75 +3 1 5.53 51.0 17.0 29.0 57.0 9.22 3.07 5.24 10.31 +4 1 4.0 44.0 14.0 24.0 30.0 11.0 3.5 6.0 7.5 +5 1 4.0 12.0 4.0 7.0 29.0 3.0 1.0 1.75 7.25 +6 1 4.0 12.0 5.0 6.0 36.0 3.0 1.25 1.5 9.0 +7 1 4.0 13.0 6.0 4.0 34.0 3.25 1.5 1.0 8.5 +8 1 5.24 41.0 7.0 29.0 41.0 7.82 1.34 5.53 7.82 +9 1 4.0 29.0 5.0 21.0 53.0 7.25 1.25 5.25 13.25 +10 1 4.0 9.0 3.0 6.0 58.0 2.25 0.75 1.5 14.5 +11 1 4.0 8.0 2.0 5.0 54.0 2.0 0.5 1.25 13.5 +12 1 4.0 6.0 3.0 1.0 35.0 1.5 0.75 0.25 8.75 +13 1 4.0 6.0 3.0 1.0 22.0 1.5 0.75 0.25 5.5 +14 1 4.0 5.0 1.0 3.0 26.0 1.25 0.25 0.75 6.5 +15 1 4.0 9.0 3.0 4.0 26.0 2.25 0.75 1.0 6.5 +16 1 4.0 20.0 5.0 8.0 25.0 5.0 1.25 2.0 6.25 +17 1 5.94 124.0 15.0 86.0 59.0 20.88 2.53 14.48 9.93 +18 1 4.0 98.0 11.0 71.0 28.0 24.5 2.75 17.75 7.0 +19 1 5.91 31.0 5.0 19.0 55.0 5.25 0.85 3.21 9.31 +20 1 4.0 19.0 4.0 9.0 64.0 4.75 1.0 2.25 16.0 +21 1 4.11 20.0 5.0 9.0 61.0 4.87 1.22 2.19 14.84 +22 1 4.0 21.0 7.0 9.0 57.0 5.25 1.75 2.25 14.25 +23 1 4.48 30.0 14.0 13.0 76.0 6.7 3.12 2.9 16.96 +24 1 4.0 20.0 10.0 8.0 96.0 5.0 2.5 2.0 24.0 +25 1 4.0 14.0 10.0 3.0 93.0 3.5 2.5 0.75 23.25 +26 1 4.0 12.0 8.0 4.0 93.0 3.0 2.0 1.0 23.25 +27 1 4.0 6.0 3.0 3.0 103.0 1.5 0.75 0.75 25.75 +28 1 4.0 6.0 3.0 3.0 69.0 1.5 0.75 0.75 17.25 +29 1 4.0 11.0 7.0 2.0 72.0 2.75 1.75 0.5 18.0 +30 1 4.0 20.0 14.0 3.0 91.0 5.0 3.5 0.75 22.75 +31 1 4.76 41.0 22.0 14.0 93.0 8.61 4.62 2.94 19.54 +32 1 4.0 32.0 12.0 14.0 58.0 8.0 3.0 3.5 14.5 +33 1 4.0 13.0 5.0 5.0 76.0 3.25 1.25 1.25 19.0 +34 1 4.0 9.0 4.0 2.0 81.0 2.25 1.0 0.5 20.25 +35 1 4.0 8.0 4.0 2.0 70.0 2.0 1.0 0.5 17.5 +36 1 5.9 47.0 13.0 25.0 94.0 7.97 2.2 4.24 15.93 +37 1 4.0 42.0 10.0 22.0 70.0 10.5 2.5 5.5 17.5 +38 1 4.0 10.0 4.0 5.0 71.0 2.5 1.0 1.25 17.75 +39 1 4.0 10.0 5.0 3.0 57.0 2.5 1.25 0.75 14.25 +40 1 4.0 12.0 9.0 1.0 60.0 3.0 2.25 0.25 15.0 +41 1 4.0 11.0 8.0 3.0 69.0 2.75 2.0 0.75 17.25 +42 1 4.0 23.0 15.0 6.0 78.0 5.75 3.75 1.5 19.5 +43 1 4.23 91.0 42.0 35.0 90.0 21.51 9.93 8.27 21.28 +44 1 4.0 81.0 38.0 34.0 73.0 20.25 9.5 8.5 18.25 +45 1 4.0 27.0 14.0 8.0 64.0 6.75 3.5 2.0 16.0 +46 1 4.0 14.0 6.0 4.0 87.0 3.5 1.5 1.0 21.75 +47 1 4.0 11.0 4.0 3.0 75.0 2.75 1.0 0.75 18.75 +48 1 4.0 11.0 5.0 3.0 48.0 2.75 1.25 0.75 12.0 +49 1 4.0 10.0 7.0 3.0 54.0 2.5 1.75 0.75 13.5 +50 1 4.0 12.0 5.0 5.0 61.0 3.0 1.25 1.25 15.25 +51 1 4.6 48.0 8.0 33.0 65.0 10.43 1.74 7.17 14.13 +52 1 4.0 41.0 7.0 28.0 50.0 10.25 1.75 7.0 12.5 +53 1 4.0 7.0 0.0 4.0 47.0 1.75 0.0 1.0 11.75 +54 1 4.0 4.0 0.0 2.0 50.0 1.0 0.0 0.5 12.5 +55 1 4.0 7.0 1.0 3.0 44.0 1.75 0.25 0.75 11.0 +56 1 4.0 15.0 3.0 8.0 44.0 3.75 0.75 2.0 11.0 +57 1 4.0 13.0 4.0 7.0 51.0 3.25 1.0 1.75 12.75 +58 1 4.13 65.0 24.0 25.0 156.0 15.74 5.81 6.05 37.77 +59 1 4.0 63.0 26.0 22.0 245.0 15.75 6.5 5.5 61.25 +60 1 4.0 27.0 15.0 9.0 188.0 6.75 3.75 2.25 47.0 +61 1 4.0 21.0 11.0 7.0 116.0 5.25 2.75 1.75 29.0 +62 1 4.0 19.0 9.0 5.0 105.0 4.75 2.25 1.25 26.25 +63 1 4.0 20.0 9.0 5.0 172.0 5.0 2.25 1.25 43.0 +64 1 4.0 26.0 12.0 8.0 216.0 6.5 3.0 2.0 54.0 +65 1 5.86 93.0 36.0 38.0 318.0 15.87 6.14 6.48 54.27 +66 1 4.0 82.0 31.0 36.0 52.0 20.5 7.75 9.0 13.0 +67 1 4.0 36.0 17.0 16.0 25.0 9.0 4.25 4.0 6.25 +68 1 4.28 53.0 20.0 27.0 62.0 12.38 4.67 6.31 14.49 +69 1 4.0 37.0 13.0 20.0 76.0 9.25 3.25 5.0 19.0 +70 1 4.0 37.0 19.0 11.0 62.0 9.25 4.75 2.75 15.5 +71 1 4.0 44.0 20.0 17.0 72.0 11.0 5.0 4.25 18.0 +72 1 4.0 31.0 6.0 22.0 87.0 7.75 1.5 5.5 21.75 +73 1 4.0 50.0 5.0 36.0 75.0 12.5 1.25 9.0 18.75 +74 1 4.0 109.0 13.0 79.0 63.0 27.25 3.25 19.75 15.75 +75 1 5.31 232.0 17.0 186.0 92.0 43.69 3.2 35.03 17.33 +76 1 4.0 96.0 7.0 74.0 60.0 24.0 1.75 18.5 15.0 +77 1 4.0 19.0 3.0 14.0 66.0 4.75 0.75 3.5 16.5 +78 1 4.0 11.0 1.0 9.0 65.0 2.75 0.25 2.25 16.25 +79 1 4.0 12.0 3.0 7.0 56.0 3.0 0.75 1.75 14.0 +80 1 4.0 17.0 3.0 10.0 56.0 4.25 0.75 2.5 14.0 +81 1 4.0 32.0 15.0 13.0 59.0 8.0 3.75 3.25 14.75 +82 1 4.84 117.0 33.0 66.0 84.0 24.17 6.82 13.64 17.36 +83 1 4.0 99.0 19.0 64.0 89.0 24.75 4.75 16.0 22.25 +84 1 4.0 21.0 7.0 12.0 100.0 5.25 1.75 3.0 25.0 +85 1 4.0 15.0 4.0 10.0 109.0 3.75 1.0 2.5 27.25 +86 1 4.12 42.0 6.0 31.0 110.0 10.19 1.46 7.52 26.7 +87 1 4.0 43.0 10.0 26.0 117.0 10.75 2.5 6.5 29.25 +88 1 4.0 46.0 17.0 25.0 113.0 11.5 4.25 6.25 28.25 +89 1 4.18 80.0 21.0 53.0 83.0 19.14 5.02 12.68 19.86 +90 1 4.0 56.0 13.0 38.0 67.0 14.0 3.25 9.5 16.75 +91 1 4.0 31.0 8.0 18.0 58.0 7.75 2.0 4.5 14.5 +92 1 4.0 48.0 5.0 34.0 39.0 12.0 1.25 8.5 9.75 +93 1 4.71 338.0 26.0 261.0 49.0 71.76 5.52 55.41 10.4 +94 1 4.0 281.0 23.0 213.0 44.0 70.25 5.75 53.25 11.0 +95 1 4.0 47.0 8.0 28.0 40.0 11.75 2.0 7.0 10.0 +96 1 4.0 45.0 8.0 32.0 29.0 11.25 2.0 8.0 7.25 +97 1 4.0 34.0 8.0 25.0 29.0 8.5 2.0 6.25 7.25 +98 1 4.0 25.0 6.0 17.0 27.0 6.25 1.5 4.25 6.75 +99 1 4.0 27.0 4.0 17.0 44.0 6.75 1.0 4.25 11.0 +100 1 4.0 24.0 2.0 17.0 54.0 6.0 0.5 4.25 13.5 +101 1 4.0 12.0 1.0 11.0 51.0 3.0 0.25 2.75 12.75 +102 1 4.0 5.0 1.0 4.0 48.0 1.25 0.25 1.0 12.0 +103 1 4.0 10.0 0.0 8.0 37.0 2.5 0.0 2.0 9.25 +104 1 4.0 15.0 0.0 10.0 28.0 3.75 0.0 2.5 7.0 +105 1 4.0 23.0 3.0 17.0 39.0 5.75 0.75 4.25 9.75 +106 1 4.0 29.0 3.0 26.0 50.0 7.25 0.75 6.5 12.5 +107 1 4.0 31.0 1.0 26.0 34.0 7.75 0.25 6.5 8.5 +108 1 4.0 31.0 3.0 22.0 46.0 7.75 0.75 5.5 11.5 +109 1 5.95 145.0 16.0 105.0 82.0 24.37 2.69 17.65 13.78 +110 1 4.0 135.0 19.0 96.0 45.0 33.75 4.75 24.0 11.25 +111 1 4.0 42.0 10.0 28.0 35.0 10.5 2.5 7.0 8.75 +112 1 4.0 30.0 7.0 20.0 24.0 7.5 1.75 5.0 6.0 +113 1 4.0 15.0 5.0 9.0 22.0 3.75 1.25 2.25 5.5 +114 1 4.0 7.0 2.0 4.0 34.0 1.75 0.5 1.0 8.5 +115 1 4.0 6.0 0.0 5.0 37.0 1.5 0.0 1.25 9.25 +116 1 4.0 7.0 3.0 4.0 32.0 1.75 0.75 1.0 8.0 +117 1 4.0 9.0 5.0 2.0 43.0 2.25 1.25 0.5 10.75 +118 1 5.78 92.0 20.0 54.0 65.0 15.92 3.46 9.34 11.25 +119 1 4.0 83.0 15.0 53.0 85.0 20.75 3.75 13.25 21.25 +120 1 4.0 26.0 15.0 8.0 105.0 6.5 3.75 2.0 26.25 +121 1 4.0 23.0 15.0 4.0 91.0 5.75 3.75 1.0 22.75 +122 1 4.94 35.0 10.0 19.0 108.0 7.09 2.02 3.85 21.86 +123 1 4.0 30.0 8.0 20.0 66.0 7.5 2.0 5.0 16.5 +124 1 4.0 16.0 8.0 7.0 60.0 4.0 2.0 1.75 15.0 +125 1 4.0 28.0 9.0 16.0 48.0 7.0 2.25 4.0 12.0 +126 1 4.0 39.0 13.0 23.0 41.0 9.75 3.25 5.75 10.25 +127 1 4.23 73.0 21.0 46.0 40.0 17.26 4.96 10.87 9.46 +128 1 4.0 71.0 16.0 48.0 38.0 17.75 4.0 12.0 9.5 +129 1 4.0 45.0 5.0 35.0 39.0 11.25 1.25 8.75 9.75 +130 1 4.0 38.0 3.0 32.0 39.0 9.5 0.75 8.0 9.75 +131 1 4.0 21.0 4.0 15.0 45.0 5.25 1.0 3.75 11.25 +132 1 4.0 21.0 4.0 13.0 40.0 5.25 1.0 3.25 10.0 +133 1 4.0 21.0 3.0 15.0 33.0 5.25 0.75 3.75 8.25 +134 1 4.0 9.0 1.0 7.0 36.0 2.25 0.25 1.75 9.0 +135 1 4.0 9.0 0.0 7.0 37.0 2.25 0.0 1.75 9.25 +136 1 4.0 18.0 1.0 14.0 50.0 4.5 0.25 3.5 12.5 +137 1 4.0 21.0 5.0 13.0 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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/frequency_sliding/tool_dependencies.xml Fri Mar 18 05:22:30 2016 -0400 @@ -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> +