Mercurial > repos > mheinzl > fsd
changeset 16:6bd9ef49d013 draft
planemo upload for repository https://github.com/monikaheinzl/duplexanalysis_galaxy/tree/master/tools/fsd commit dfaab79252a858e8df16bbea3607ebf1b6962e5a
| author | mheinzl |
|---|---|
| date | Mon, 08 Oct 2018 05:50:18 -0400 |
| parents | 32921a67437b |
| children | 2e517a54eedc |
| files | fsd.py fsd.xml test-data/Test_data2.tabular test-data/Test_data3.tabular test-data/Test_data4.tabular test-data/output_file.csv test-data/output_file.pdf test-data/output_file.tabular test-data/output_file2.pdf test-data/output_file2.tabular |
| diffstat | 10 files changed, 1040 insertions(+), 98 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/fsd.py Mon Oct 08 05:50:18 2018 -0400 @@ -0,0 +1,372 @@ +#!/usr/bin/env python + +# Family size distribution of SSCSs +# +# Author: Monika Heinzl, Johannes-Kepler University Linz (Austria) +# Contact: monika.heinzl@edumail.at +# +# Takes at least one TABULAR file with tags before the alignment to the SSCS, but up to 4 files can be provided, as input. +# The program produces a plot which shows the distribution of family sizes of the all SSCSs from the input files and +# a tabular file with the data of the plot, as well as a TXT file with all tags of the DCS and their family sizes. +# If only one file is provided, then a family size distribution, which is separated after SSCSs without a partner and DCSs, is produced. +# Whereas a family size distribution with multiple data in one plot is produced, when more than one file (up to 4) is given. + +# USAGE: python FSD_Galaxy_1.4_commandLine_FINAL.py --inputFile1 filename --inputName1 filename --inputFile2 filename2 --inputName2 filename2 --inputFile3 filename3 --inputName3 filename3 --inputFile4 filename4 --inputName4 filename4 --output_tabular outptufile_name_tabular --output_pdf outptufile_name_pdf + +import argparse +import sys + +import matplotlib.pyplot as plt +import numpy +from matplotlib.backends.backend_pdf import PdfPages + +plt.switch_backend('agg') + + +def readFileReferenceFree(file): + with open(file, 'r') as dest_f: + data_array = numpy.genfromtxt(dest_f, skip_header=0, delimiter='\t', comments='#', dtype='string') + return(data_array) + + +def make_argparser(): + parser = argparse.ArgumentParser(description='Family Size Distribution of duplex sequencing data') + parser.add_argument('--inputFile1', help='Tabular File with three columns: ab or ba, tag and family size.') + parser.add_argument('--inputName1') + parser.add_argument('--inputFile2', default=None, help='Tabular File with three columns: ab or ba, tag and family size.') + parser.add_argument('--inputName2') + parser.add_argument('--inputFile3', default=None, help='Tabular File with three columns: ab or ba, tag and family size.') + parser.add_argument('--inputName3') + parser.add_argument('--inputFile4', default=None, help='Tabular File with three columns: ab or ba, tag and family size.') + parser.add_argument('--inputName4') + parser.add_argument('--output_pdf', default="data.pdf", type=str, help='Name of the pdf file.') + parser.add_argument('--output_tabular', default="data.tabular", type=str, help='Name of the tabular file.') + return parser + + +def compare_read_families(argv): + parser = make_argparser() + args = parser.parse_args(argv[1:]) + + firstFile = args.inputFile1 + name1 = args.inputName1 + + secondFile = args.inputFile2 + name2 = args.inputName2 + thirdFile = args.inputFile3 + name3 = args.inputName3 + fourthFile = args.inputFile4 + name4 = args.inputName4 + + title_file = args.output_tabular + title_file2 = args.output_pdf + + sep = "\t" + + plt.rc('figure', figsize=(11.69, 8.27)) # A4 format + plt.rcParams['patch.edgecolor'] = "black" + plt.rcParams['axes.facecolor'] = "E0E0E0" # grey background color + plt.rcParams['xtick.labelsize'] = 14 + plt.rcParams['ytick.labelsize'] = 14 + + list_to_plot = [] + label = [] + data_array_list = [] + with open(title_file, "w") as output_file, PdfPages(title_file2) as pdf: + fig = plt.figure() + plt.subplots_adjust(bottom=0.25) + if firstFile != str(None): + file1 = readFileReferenceFree(firstFile) + integers = numpy.array(file1[:, 0]).astype(int) # keep original family sizes + + # for plot: replace all big family sizes by 22 + data1 = numpy.array(file1[:, 0]).astype(int) + bigFamilies = numpy.where(data1 > 20)[0] + data1[bigFamilies] = 22 + + name1 = name1.split(".tabular")[0] + list_to_plot.append(data1) + label.append(name1) + data_array_list.append(file1) + + legend = "\n\n\n{}".format(name1) + plt.text(0.1, 0.11, legend, size=12, transform=plt.gcf().transFigure) + legend1 = "singletons:\nabsolute nr.\n{:,}".format(numpy.bincount(data1)[1]) + plt.text(0.4, 0.11, legend1, size=12, transform=plt.gcf().transFigure) + + legend3 = "rel. freq\n{:.3f}".format(float(numpy.bincount(data1)[1]) / len(data1)) + plt.text(0.5, 0.11, legend3, size=12, transform=plt.gcf().transFigure) + + legend4 = "family size > 20:\nabsolute nr.\n{:,}".format(numpy.bincount(data1)[len(numpy.bincount(data1)) - 1].astype(int)) + plt.text(0.6, 0.11, legend4, size=12, transform=plt.gcf().transFigure) + + legend5 = "rel. freq\n{:.3f}".format(float(numpy.bincount(data1)[len(numpy.bincount(data1)) - 1]) / len(data1)) + plt.text(0.7, 0.11, legend5, size=12, transform=plt.gcf().transFigure) + + legend6 = "total length\n{:,}".format(len(data1)) + plt.text(0.8, 0.11, legend6, size=12, transform=plt.gcf().transFigure) + + if secondFile != str(None): + file2 = readFileReferenceFree(secondFile) + data2 = numpy.asarray(file2[:, 0]).astype(int) + bigFamilies2 = numpy.where(data2 > 20)[0] + data2[bigFamilies2] = 22 + + list_to_plot.append(data2) + name2 = name2.split(".tabular")[0] + label.append(name2) + data_array_list.append(file2) + + plt.text(0.1, 0.09, name2, size=12, transform=plt.gcf().transFigure) + + legend1 = "{:,}".format(numpy.bincount(data2)[1]) + plt.text(0.4, 0.09, legend1, size=12, transform=plt.gcf().transFigure) + + legend3 = "{:.3f}".format(float(numpy.bincount(data2)[1]) / len(data2)) + plt.text(0.5, 0.09, legend3, size=12, transform=plt.gcf().transFigure) + + legend4 = "{:,}".format(numpy.bincount(data2)[len(numpy.bincount(data2)) - 1].astype(int)) + plt.text(0.6, 0.09, legend4, size=12, transform=plt.gcf().transFigure) + + legend5 = "{:.3f}".format(float(numpy.bincount(data2)[len(numpy.bincount(data2)) - 1]) / len(data2)) + plt.text(0.7, 0.09, legend5, size=12, transform=plt.gcf().transFigure) + + legend6 = "{:,}".format(len(data2)) + plt.text(0.8, 0.09, legend6, size=12, transform=plt.gcf().transFigure) + + if thirdFile != str(None): + file3 = readFileReferenceFree(thirdFile) + + data3 = numpy.asarray(file3[:, 0]).astype(int) + bigFamilies3 = numpy.where(data3 > 20)[0] + data3[bigFamilies3] = 22 + + list_to_plot.append(data3) + name3 = name3.split(".tabular")[0] + label.append(name3) + data_array_list.append(file3) + + plt.text(0.1, 0.07, name3, size=12, transform=plt.gcf().transFigure) + + legend1 = "{:,}".format(numpy.bincount(data3)[1]) + plt.text(0.4, 0.07, legend1, size=12, transform=plt.gcf().transFigure) + + legend3 = "{:.3f}".format(float(numpy.bincount(data3)[1]) / len(data3)) + plt.text(0.5, 0.07, legend3, size=12, transform=plt.gcf().transFigure) + + legend4 = "{:,}".format(numpy.bincount(data3)[len(numpy.bincount(data3)) - 1].astype(int)) + plt.text(0.6, 0.07, legend4, size=12, transform=plt.gcf().transFigure) + + legend5 = "{:.3f}".format(float(numpy.bincount(data3)[len(numpy.bincount(data3)) - 1]) / len(data3)) + plt.text(0.7, 0.07, legend5, size=12, transform=plt.gcf().transFigure) + + legend6 = "{:,}".format(len(data3)) + plt.text(0.8, 0.07, legend6, size=12, transform=plt.gcf().transFigure) + + if fourthFile != str(None): + file4 = readFileReferenceFree(fourthFile) + + data4 = numpy.asarray(file4[:, 0]).astype(int) + + bigFamilies4 = numpy.where(data4 > 20)[0] + data4[bigFamilies4] = 22 + + list_to_plot.append(data4) + name4 = name4.split(".tabular")[0] + label.append(name4) + data_array_list.append(file4) + + plt.text(0.1, 0.05, name4, size=12, transform=plt.gcf().transFigure) + + legend1 = "{:,}".format(numpy.bincount(data4)[1]) + plt.text(0.4, 0.05, legend1, size=12, transform=plt.gcf().transFigure) + + legend4 = "{:.3f}".format(float(numpy.bincount(data4)[1]) / len(data4)) + plt.text(0.5, 0.05, legend4, size=12, transform=plt.gcf().transFigure) + + legend4 = "{:,}".format(numpy.bincount(data4)[len(numpy.bincount(data4)) - 1].astype(int)) + plt.text(0.6, 0.05, legend4, size=12, transform=plt.gcf().transFigure) + + legend5 = "{:.3f}".format(float(numpy.bincount(data4)[len(numpy.bincount(data4)) - 1]) / len(data4)) + plt.text(0.7, 0.05, legend5, size=12, transform=plt.gcf().transFigure) + + legend6 = "{:,}".format(len(data4)) + plt.text(0.8, 0.05, legend6, size=12, transform=plt.gcf().transFigure) + + maximumX = numpy.amax(numpy.concatenate(list_to_plot)) + minimumX = numpy.amin(numpy.concatenate(list_to_plot)) + + counts = plt.hist(list_to_plot, bins=range(minimumX, maximumX + 1), stacked=False, edgecolor="black", + linewidth=1, label=label, align="left", alpha=0.7, rwidth=0.8) + + ticks = numpy.arange(minimumX - 1, maximumX, 1) + ticks1 = map(str, ticks) + ticks1[len(ticks1) - 1] = ">20" + plt.xticks(numpy.array(ticks), ticks1) + + plt.legend(loc='upper right', fontsize=14, frameon=True, bbox_to_anchor=(0.9, 1)) + # plt.title("Family Size Distribution", fontsize=14) + plt.xlabel("Family size", fontsize=14) + plt.ylabel("Absolute Frequency", fontsize=14) + plt.margins(0.01, None) + plt.grid(b=True, which="major", color="#424242", linestyle=":") + pdf.savefig(fig) + plt.close() + + # write data to CSV file + output_file.write("Values from family size distribution with all datasets\n") + output_file.write("\nFamily size") + for i in label: + output_file.write("{}{}".format(sep, i)) + # output_file.write("{}sum".format(sep)) + output_file.write("\n") + j = 0 + for fs in counts[1][0:len(counts[1]) - 1]: + if fs == 21: + fs = ">20" + else: + fs = "={}".format(fs) + output_file.write("FS{}{}".format(fs, sep)) + if len(label) == 1: + output_file.write("{}{}".format(int(counts[0][j]), sep)) + else: + for n in range(len(label)): + output_file.write("{}{}".format(int(counts[0][n][j]), sep)) + output_file.write("\n") + j += 1 + output_file.write("sum{}".format(sep)) + if len(label) == 1: + output_file.write("{}{}".format(int(sum(counts[0])), sep)) + else: + for i in counts[0]: + output_file.write("{}{}".format(int(sum(i)), sep)) + + # Family size distribution after DCS and SSCS + for dataset, data, name_file in zip(list_to_plot, data_array_list, label): + maximumX = numpy.amax(dataset) + minimumX = numpy.amin(dataset) + + tags = numpy.array(data[:, 2]) + seq = numpy.array(data[:, 1]) + data = numpy.array(dataset) + + # find all unique tags and get the indices for ALL tags, but only once + u, index_unique, c = numpy.unique(numpy.array(seq), return_counts=True, return_index=True) + d = u[c > 1] + + # get family sizes, tag for duplicates + duplTags_double = data[numpy.in1d(seq, d)] + duplTags = duplTags_double[0::2] # ab of DCS + duplTagsBA = duplTags_double[1::2] # ba of DCS + + # duplTags_double_tag = tags[numpy.in1d(seq, d)] + # duplTags_double_seq = seq[numpy.in1d(seq, d)] + + # get family sizes for SSCS with no partner + ab = numpy.where(tags == "ab")[0] + abSeq = seq[ab] + ab = data[ab] + ba = numpy.where(tags == "ba")[0] + baSeq = seq[ba] + ba = data[ba] + + dataAB = ab[numpy.in1d(abSeq, d, invert=True)] + dataBA = ba[numpy.in1d(baSeq, d, invert=True)] + + list1 = [duplTags_double, dataAB, dataBA] # list for plotting + + # information for family size >= 3 + dataAB_FS3 = dataAB[dataAB >= 3] + dataBA_FS3 = dataBA[dataBA >= 3] + ab_FS3 = ab[ab >= 3] + ba_FS3 = ba[ba >= 3] + + duplTags_FS3 = duplTags[(duplTags >= 3) & (duplTagsBA >= 3)] # ab+ba with FS>=3 + duplTags_FS3_BA = duplTagsBA[(duplTags >= 3) & (duplTagsBA >= 3)] # ba+ab with FS>=3 + duplTags_double_FS3 = len(duplTags_FS3) + len(duplTags_FS3_BA) # both ab and ba strands with FS>=3 + + fig = plt.figure() + + plt.subplots_adjust(bottom=0.3) + counts = plt.hist(list1, bins=range(minimumX, maximumX + 1), stacked=True, label=["duplex", "ab", "ba"], edgecolor="black", linewidth=1, align="left", color=["#FF0000", "#5FB404", "#FFBF00"]) + # tick labels of x axis + ticks = numpy.arange(minimumX - 1, maximumX, 1) + ticks1 = map(str, ticks) + ticks1[len(ticks1) - 1] = ">20" + plt.xticks(numpy.array(ticks), ticks1) + singl = counts[0][2][0] # singletons + last = counts[0][2][len(counts[0][0]) - 1] # large families + + plt.legend(loc='upper right', fontsize=14, bbox_to_anchor=(0.9, 1), frameon=True) + # plt.title(name1, fontsize=14) + plt.xlabel("Family size", fontsize=14) + plt.ylabel("Absolute Frequency", fontsize=14) + plt.margins(0.01, None) + plt.grid(b=True, which="major", color="#424242", linestyle=":") + + # extra information beneath the plot + legend = "SSCS ab= \nSSCS ba= \nDCS (total)= \nlength of dataset=" + plt.text(0.1, 0.09, legend, size=12, transform=plt.gcf().transFigure) + + legend = "absolute numbers\n\n{:,}\n{:,}\n{:,} ({:,})\n{:,}".format(len(dataAB), len(dataBA), len(duplTags), len(duplTags_double), (len(dataAB) + len(dataBA) + len(duplTags))) + plt.text(0.35, 0.09, legend, size=12, transform=plt.gcf().transFigure) + + legend = "relative frequencies\nunique\n{:.3f}\n{:.3f}\n{:.3f}\n{:,}".format(float(len(dataAB)) / (len(dataAB) + len(dataBA) + len(duplTags)), float(len(dataBA)) / (len(dataAB) + len(dataBA) + len(duplTags)), float(len(duplTags)) / (len(dataAB) + len(dataBA) + len(duplTags)), (len(dataAB) + len(dataBA) + len(duplTags))) + plt.text(0.54, 0.09, legend, size=12, transform=plt.gcf().transFigure) + + legend = "total\n{:.3f}\n{:.3f}\n{:.3f} ({:.3f})\n{:,}".format(float(len(dataAB)) / (len(ab) + len(ba)), float(len(dataBA)) / (len(ab) + len(ba)), float(len(duplTags)) / (len(ab) + len(ba)), float(len(duplTags_double)) / (len(ab) + len(ba)), (len(ab) + len(ba))) + plt.text(0.64, 0.09, legend, size=12, transform=plt.gcf().transFigure) + + legend1 = "\nsingletons:\nfamily size > 20:" + plt.text(0.1, 0.03, legend1, size=12, transform=plt.gcf().transFigure) + + legend4 = "{:,}\n{:,}".format(singl.astype(int), last.astype(int)) + plt.text(0.35, 0.03, legend4, size=12, transform=plt.gcf().transFigure) + + legend3 = "{:.3f}\n{:.3f}".format(singl / len(data), last / len(data)) + plt.text(0.54, 0.03, legend3, size=12, transform=plt.gcf().transFigure) + + pdf.savefig(fig) + plt.close() + + # write same information to a csv file + count = numpy.bincount(integers) # original counts of family sizes + output_file.write("\nDataset:{}{}\n".format(sep, name_file)) + output_file.write("max. family size:{}{}\n".format(sep, max(integers))) + output_file.write("absolute frequency:{}{}\n".format(sep, count[len(count) - 1])) + output_file.write("relative frequency:{}{:.3f}\n\n".format(sep, float(count[len(count) - 1]) / sum(count))) + + output_file.write("{}singletons:{}{}family size > 20:\n".format(sep, sep, sep)) + output_file.write("{}absolute nr.{}rel. freq{}absolute nr.{}rel. freq{}total length\n".format(sep, sep, sep, sep, sep)) + output_file.write("{}{}{}{}{:.3f}{}{}{}{:.3f}{}{}\n\n".format(name_file, sep, singl.astype(int), sep, singl / len(data), sep, last.astype(int), sep, last / len(data), sep, len(data))) + + # information for FS >= 1 + output_file.write("The unique frequencies were calculated from the dataset where the tags occured only once (=ab without DCS, ba without DCS)\nWhereas the total frequencies were calculated from the whole dataset (=including the DCS).\n\n") + output_file.write("FS >= 1{}{}unique:{}total:\n".format(sep, sep, sep)) + output_file.write("nr./rel. freq of ab={}{}{}{:.3f}{}{:.3f}\n".format(sep, len(dataAB), sep, float(len(dataAB)) / (len(dataAB) + len(dataBA) + len( duplTags)), sep, float(len(dataAB)) / (len(ab) + len(ba)))) + output_file.write("nr./rel. freq of ba={}{}{}{:.3f}{}{:.3f}\n".format(sep, len(dataBA), sep, float(len(dataBA)) / (len(dataBA) + len(dataBA) + len(duplTags)), sep, float(len(dataBA)) / (len(ba) + len(ba)))) + output_file.write("nr./rel. freq of DCS (total)={}{} ({}){}{:.3f}{}{:.3f} ({:.3f})\n".format(sep, len(duplTags), len(duplTags_double), sep, float(len(duplTags)) / (len(dataAB) + len(dataBA) + len(duplTags)), sep, float(len(duplTags)) / ( len(ab) + len(ba)), float(len(duplTags_double)) / (len(ab) + len(ba)))) + output_file.write("length of dataset={}{}{}{}{}{}\n".format(sep, (len(dataAB) + len(dataBA) + len(duplTags)), sep, (len(dataAB) + len(dataBA) + len(duplTags)), sep, (len(ab) + len(ba)))) + # information for FS >= 3 + output_file.write("FS >= 3{}{}unique:{}total:\n".format(sep, sep, sep)) + output_file.write("nr./rel. freq of ab={}{}{}{:.3f}{}{:.3f}\n".format(sep, len(dataAB_FS3), sep, float(len(dataAB_FS3)) / (len(dataAB_FS3) + len(dataBA_FS3) + len(duplTags_FS3)), sep, float(len(dataAB_FS3)) / (len(ab_FS3) + len(ba_FS3)))) + output_file.write("nr./rel. freq of ba={}{}{}{:.3f}{}{:.3f}\n".format(sep, len(dataBA_FS3), sep, float(len(dataBA_FS3)) / (len(dataBA_FS3) + len(dataBA_FS3) + len(duplTags_FS3)), sep, float(len(dataBA_FS3)) / (len(ba_FS3) + len(ba_FS3)))) + output_file.write("nr./rel. freq of DCS (total)={}{} ({}){}{:.3f}{}{:.3f} ({:.3f})\n".format(sep, len(duplTags_FS3), duplTags_double_FS3, sep, float(len( duplTags_FS3)) / (len(dataBA_FS3) + len(duplTags_FS3)), sep, float(len(duplTags_FS3)) / (len(ab_FS3) + len(ba_FS3)), float(duplTags_double_FS3) / (len(ab_FS3) + len(ba_FS3)))) + output_file.write("length of dataset={}{}{}{}{}{}\n".format(sep, (len(dataAB_FS3) + len(dataBA_FS3) + len(duplTags_FS3)), sep, (len(dataAB_FS3) + len(dataBA_FS3) + len(duplTags_FS3)), sep, (len(ab_FS3) + len(ba_FS3)))) + + output_file.write("\nValues from family size distribution\n") + output_file.write("{}duplex{}ab{}ba{}sum\n".format(sep, sep, sep, sep)) + for dx, ab, ba, fs in zip(counts[0][0], counts[0][1], counts[0][2], counts[1]): + if fs == 21: + fs = ">20" + else: + fs = "={}".format(fs) + ab1 = ab - dx + ba1 = ba - ab + output_file.write("FS{}{}{}{}{}{}{}{}{}\n".format(fs, sep, int(dx), sep, int(ab1), sep, int(ba1), sep, int(ba))) + + print("Files successfully created!") + + +if __name__ == '__main__': + sys.exit(compare_read_families(sys.argv))
--- a/fsd.xml Tue Jul 17 07:09:21 2018 -0400 +++ b/fsd.xml Mon Oct 08 05:50:18 2018 -0400 @@ -1,80 +1,72 @@ <?xml version="1.0" encoding="UTF-8"?> <!-- galaxy version 16.04 --> -<tool id="fsd" name="Duplex Sequencing Analysis: fsd" version="0.0.16"> - <description>Family size distribution (FSD) of tags</description> +<tool id="fsd" name="FSD" version="1.0.0"> + <description>: Family Size Distribution of duplex sequencing tags</description> <requirements> <requirement type="package" version="2.7">python</requirement> - <requirement type="package" version="1.4">matplotlib</requirement> - <requirement type="package" version="0.0.2">duplexanalysis</requirement> - + <requirement type="package" version="1.4.0">matplotlib</requirement> </requirements> <command> - fsd.py --inputFile1 "$file1" --inputName1 "$file1.name" --inputFile2 "$file2" --inputName2 "$file2.name" --inputFile3 "$file3" --inputName3 "$file3.name" --inputFile4 "$file4" --inputName4 "$file4.name" --sep $separator --output_pdf $output_pdf --output_csv $output_csv + python2 '$__tool_directory__/fsd.py' --inputFile1 '${file1}' --inputName1 '${file1.name}' +--inputFile2 '${file2}' --inputName2 '${file2.name}' --inputFile3 '${file3}' --inputName3 '${file3.name}' +--inputFile4 '${file4}' --inputName4 '${file4.name}' --output_pdf $output_pdf --output_tabular $output_tabular </command> <inputs> <param name="file1" type="data" format="tabular" label="Dataset 1: input tags" optional="false"/> <param name="file2" type="data" format="tabular" label="Dataset 2: input tags" optional="true" /> <param name="file3" type="data" format="tabular" label="Dataset 3: input tags" optional="true" /> <param name="file4" type="data" format="tabular" label="Dataset 4: input tags" optional="true" help="Input in tabular format with the family size, tags and the direction of the strand ('ab' or 'ba') for each family. Name of the files can have max. 34 charcters!"/> - <param name="separator" type="text" label="Separator of the CSV file." help="can be a single character" value=","/> </inputs> <outputs> <data name="output_pdf" format="pdf" /> - <data name="output_csv" format="csv"/> + <data name="output_tabular" format="tabular"/> </outputs> - <!-- <tests> + <tests> <test> <param name="file1" value="Test_data.tabular"/> - <param name="file2" value="None"/> - <param name="file3" value="None"/> - <param name="file4" value="None"/> - <output name="output_pdf" file="output_file.pdf"/> - <output name="output_csv" file="output_file.csv"/> + <param name="file2" value="Test_data2.tabular"/> + <param name="file3" value="Test_data3.tabular"/> + <param name="file4" value="Test_data4.tabular"/> + <output name="output_pdf" file="output_file.pdf" lines_diff="285"/> + <output name="output_tabular" file="output_file.tabular"/> + </test> + <test> + <param name="file1" value="Test_data.tabular"/> + <param name="file2" value="Test_data2.tabular"/> + <param name="file3" value="Test_data3.tabular"/> + <output name="output_pdf" file="output_file2.pdf" lines_diff="285"/> + <output name="output_tabular" file="output_file2.tabular"/> </test> </tests> - --> - <help> <![CDATA[ + <help><![CDATA[ **What it does** - This tool will create a distribution of family sizes of each tag, which is separated after families tags that have only the forward (ab) strand, the reverse (ba) strand or both strands (ab+ba) of the DCS and a family size distribution without separation is created. If multiple files are provided as input, the family size distribution without separation contains all datasets in one plot and for each dataset a distribution with separation after single ab, ba strands and DCSs is produced. - +This tool will create a distribution of family sizes of each tag, which is separated after tags that have only the forward (ab) strand, the reverse (ba) strand or both strands (ab+ba) of the DCS and a family size distribution without separation is created. + +------ **Input** - This tools expects a tabular file with the tags of all families, their sizes and information about forward (ab) and reverse (ba) strands. - - **!!! Name of the files can have max. 34 charcters !!!** - - +-----+----------------------------+----+ - | 1 | AAAAAAAAAAAATGTTGGAATCTT | ba | - +-----+----------------------------+----+ - | 10 | AAAAAAAAAAAGGCGGTCCACCCC | ab | - +-----+----------------------------+----+ - | 28 | AAAAAAAAAAATGGTATGGACCGA | ab | - +-----+----------------------------+----+ - - - - - +This tools expects a tabular file with the tags of all families, their sizes and information about forward (ab) and reverse (ba) strands:: + + 1 AAAAAAAAAAAATGTTGGAATCTT ba + 10 AAAAAAAAAAAGGCGGTCCACCCC ab + 28 AAAAAAAAAAATGGTATGGACCGA ab + **Output** - The output is a PDF file with the plot and a CSV with the data of the plot. - +The output is a PDF file with the plot and a tabular file with the data of the plot. **About Author** - Author: Monika Heinzl - - Department: Institute of Bioinformatics, Johannes Kepler University Linz, Austria - - Contact: monika.heinzl@edumail.at +Author: Monika Heinzl +Department: Institute of Bioinformatics, Johannes Kepler University Linz, Austria +Contact: monika.heinzl@edumail.at - ]]> - - </help> +]]> +</help> <citations> <citation type="bibtex"> @misc{duplex,
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/Test_data2.tabular Mon Oct 08 05:50:18 2018 -0400 @@ -0,0 +1,112 @@ +1 AAAAAAAAAAAAAACCAAAACTTC ba +1 AAAAAAAAAAAAACCAGGCGTCGA ba +1 AAAAAAAAAAAAAGCTCCACGTTG ba +1 AAAAAAAAAAAAATCGTGGTTTGT ba +1 AAAAAAAAAAAAATTCACCCTTGT ba +7 AAAAAAAAAAAACACACTTAACTT ba +1 AAAAAAAAAAAACAGTGTTGAGAC ba +4 AAAAAAAAAAAACCGCTCCTCACA ba +1 AAAAAAAAAAAAGGCAACACAGAA ab +2 AAAAAAAAAAAATCTTTCTTTGAG ab +1 AAAAAAAAAAAATTGGGTTCCTTA ab +1 AAAAAAAAAAAGAGTCGCACCCAG ba +4 AAAAAAAAAAAGATCGTGGTTTGT ba +1 AAAAAAAAAAAGCGCAACACAGAA ab +3 AAAAAAAAAAAGGGCAACACAGAA ab +1 AAAAAAAAAAAGTAGCCCTAAACG ab +1 AAAAAAAAAAAGTCTTTCTTTGAG ab +1 AAAAAAAAAAATATCATAGACTCT ab +6 AAAAAAAAAAATATTCACCCTTGT ba +1 AAAAAAAAAAATATTCGAAAGTTA ba +3 AAAAAAAAAAATCACACTTAACTT ba +1 AAAAAAAAAAATCCGCTCCTCACA ba +1 AAAAAAAAAAATTAACTAAACTTA ab +1 AAAAAAAAAACAAATTCTATTATT ab +1 AAAAAAAAAACTCCCAGATTTTTT ab +1 AAAAAAAAAACTTCTGCTTGGCGG ba +11 AAAAAAAAAAGAATCGTGGTTTGT ba +5 AAAAAAAAAAGATAGCCCTAAACG ab +1 AAAAAAAAAAGCAATAATGCCAGT ab +2 AAAAAAAAAAGTACCGCACTCTCA ba +1 AAAAAAAAAAGTTCTTTCTTTGAG ab +1 AAAAAAAAAATAACTTCAATAATG ba +2 AAAAAAAAAATAATCATAGACTCT ab +1 AAAAAAAAAATAGTCTCACATTTA ab +1 AAAAAAAAAATATAACCTTTGGCG ab +3 AAAAAAAAACAAAATTCTATTATT ab +1 AAAAAAAAACAAGTACGCGGCATT ab +1 AAAAAAAAACAAGTACGCGGTATT ab +1 AAAAAAAAACAATATCGAATTAAC ab +3 AAAAAAAAACACGGTGAGACAAGG ba +1 AAAAAAAAACACGTTTCTCCCCTT ba +1 AAAAAAAAACATATCGTCCCGAGC ba +1 AAAAAAAAACCTACCTGAGGCCCC ab +3 AAAAAAAAACCTTATTACAGCGGA ab +1 AAAAAAAAACGATTCTCTGTATCT ba +1 AAAAAAAAACGTACCGCACTCTCA ba +4 AAAAAAAAACTACCCAGATTTTTT ba +1 AAAAAAAAACTAGATGAGACGACC ba +4 AAAAAAAAACTGTCTGCTTGGCGG ba +1 AAAAAAAAAGAAGTTTAATTTTAA ab +1 AAAAAAAAAGAATGCCTAAGACGA ba +6 AAAAAAAAAGACCGGCCTTAGACA ba +1 AAAAAAAAAGATATCGTGGTTTGT ba +1 AAAAAAAAAGCAATACTCAAGCTG ba +6 AAAAAAAAAGCAATGTCTAAGCCT ba +1 AAAAAAAAAGCACTGTCTAAGCCT ab +2 AAAAAAAAAGCTAATAATGCCAGT ab +1 AAAAAAAAAGTTTCGTGAAGGTCC ba +1 AAAAAAAAATAAAGGTCCGAATCT ab +1 AAAAAAAAATAAATGAGAGTGTAA ba +8 AAAAAAAAATAAGTCTCACATTTA ab +1 AAAAAAAAATAATAACCTCTGGCG ab +10 AAAAAAAAATAATAACCTTTGGCG ab +1 AAAAAAAAATAATCCCCTTTGTCG ab +6 AAAAAAAAATACGCAAACGCTGAG ab +4 AAAAAAAAATAGATCATAGACTCT ab +10 AAAAAAAAATAGATCATAGACTCT ba +10 AAAAAAAAATAGTAGGATTTCATG ba +7 AAAAAAAAATATGAATACCCTCGT ba +1 AAAAAAAAATATGCCACTTGATCC ba +1 AAAAAAAAATATTCTGCCACTTGA ba +3 AAAAAAAAATCAAACCAAGAGGAC ba +1 AAAAAAAAATCAGTACCCCTAAAC ab +12 AAAAAAAAATCCTAGTTAATGAAG ba +1 AAAAAAAAATCGATTCTTTATGCG ab +1 AAAAAAAAATGTCTGAAAATATCT ab +4 AAAAAAAAATGTCTGAAAATATCT ba +1 AAAAAAAAATTTCCGCAGACCGTT ba +8 AAAAAAAAATTTGGGCTACTACAA ba +1 AAAAAAAACAAAATTAGAACCCTT ab +1 AAAAAAAACAAACCGCTCCTCACA ba +5 AAAAAAAACAACGTACGCGGTATT ab +4 AAAAAAAACAATATCGTTGATATG ba +4 AAAAAAAACAATCACGTTAATAGG ab +1 AAAAAAAACAGAATCGTGGTTTGT ba +1 AAAAAAAACCAAATCGTTGATATG ba +9 AAAAAAAACCAAGTCCAGGCATCT ba +2 AAAAAAAACCACGGTGAGACAAGG ba +1 AAAAAAAACCGCCCAACTGCCGGT ab +5 AAAAAAAACCTCTCAACCCCAAAT ba +7 AAAAAAAACCTCTTGCGATGTTGT ab +1 AAAAAAAACCTCTTGCGCTGTTGT ab +1 AAAAAAAACCTCTTGTGATGTTGT ab +12 AAAAAAAACCTGAGCAATGGTTCC ab +3 AAAAAAAACCTTGACCCTCACATG ba +6 AAAAAAAACCTTGCACTCGTCCTA ba +9 AAAAAAAACGAAATAAAAAAACCT ba +1 AAAAAAAACGACCGGCCTTAGACA ba +4 AAAAAAAACGCCACCACCCCCTTT ab +12 AAAAAAAACGCCACGGGCACTATT ba +13 AAAAAAAACGTATCAGTAGATCCT ab +1 AAAAAAAACTAGTAGGATTTCATG ba +3 AAAAAAAACTATAGAAAATCCATT ba +1 AAAAAAAACTATTCTATTTCCGAT ba +13 AAAAAAAACTGATCTGCTTGGCGG ba +8 AAAAAAAACTTGCGAATAGCATCG ba +4 AAAAAAAACTTGTTATCAAAACGT ab +1 AAAAAAAAGAAAAGTTCAACACGC ba +1 AAAAAAAAGAAGTTCGCCCTCCGA ab +13 AAAAAAAAGAGAGTTTAGTCATGG ab +1 AAAAAAAAGAGAGTTTAGTCATGG ba +1 AAAAAAAAGAGAGTTTAGTCCTGG ab \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/Test_data3.tabular Mon Oct 08 05:50:18 2018 -0400 @@ -0,0 +1,112 @@ +1 AAAAAAAAAAAAAACCAAAACTTC ba +1 AAAAAAAAAAAAACCAGGCGTCGA ba +1 AAAAAAAAAAAAAGCTCCACGTTG ba +1 AAAAAAAAAAAAATCGTGGTTTGT ba +1 AAAAAAAAAAAAATTCACCCTTGT ba +7 AAAAAAAAAAAACACACTTAACTT ba +1 AAAAAAAAAAAACAGTGTTGAGAC ba +4 AAAAAAAAAAAACCGCTCCTCACA ba +1 AAAAAAAAAAAAGGCAACACAGAA ab +2 AAAAAAAAAAAATCTTTCTTTGAG ab +1 AAAAAAAAAAAATTGGGTTCCTTA ab +1 AAAAAAAAAAAGAGTCGCACCCAG ba +4 AAAAAAAAAAAGATCGTGGTTTGT ba +1 AAAAAAAAAAAGCGCAACACAGAA ab +3 AAAAAAAAAAAGGGCAACACAGAA ab +1 AAAAAAAAAAAGTAGCCCTAAACG ab +1 AAAAAAAAAAAGTCTTTCTTTGAG ab +1 AAAAAAAAAAATATCATAGACTCT ab +6 AAAAAAAAAAATATTCACCCTTGT ba +1 AAAAAAAAAAATATTCGAAAGTTA ba +3 AAAAAAAAAAATCACACTTAACTT ba +1 AAAAAAAAAAATCCGCTCCTCACA ba +1 AAAAAAAAAAATTAACTAAACTTA ab +1 AAAAAAAAAACAAATTCTATTATT ab +1 AAAAAAAAAACTCCCAGATTTTTT ab +1 AAAAAAAAAACTTCTGCTTGGCGG ba +11 AAAAAAAAAAGAATCGTGGTTTGT ba +5 AAAAAAAAAAGATAGCCCTAAACG ab +1 AAAAAAAAAAGCAATAATGCCAGT ab +2 AAAAAAAAAAGTACCGCACTCTCA ba +1 AAAAAAAAAAGTTCTTTCTTTGAG ab +1 AAAAAAAAAATAACTTCAATAATG ba +2 AAAAAAAAAATAATCATAGACTCT ab +1 AAAAAAAAAATAGTCTCACATTTA ab +1 AAAAAAAAAATATAACCTTTGGCG ab +3 AAAAAAAAACAAAATTCTATTATT ab +1 AAAAAAAAACAAGTACGCGGCATT ab +1 AAAAAAAAACAAGTACGCGGTATT ab +1 AAAAAAAAACAATATCGAATTAAC ab +3 AAAAAAAAACACGGTGAGACAAGG ba +1 AAAAAAAAACACGTTTCTCCCCTT ba +1 AAAAAAAAACATATCGTCCCGAGC ba +1 AAAAAAAAACCTACCTGAGGCCCC ab +3 AAAAAAAAACCTTATTACAGCGGA ab +1 AAAAAAAAACGATTCTCTGTATCT ba +1 AAAAAAAAACGTACCGCACTCTCA ba +4 AAAAAAAAACTACCCAGATTTTTT ba +1 AAAAAAAAACTAGATGAGACGACC ba +4 AAAAAAAAACTGTCTGCTTGGCGG ba +1 AAAAAAAAAGAAGTTTAATTTTAA ab +1 AAAAAAAAAGAATGCCTAAGACGA ba +6 AAAAAAAAAGACCGGCCTTAGACA ba +1 AAAAAAAAAGATATCGTGGTTTGT ba +1 AAAAAAAAAGCAATACTCAAGCTG ba +6 AAAAAAAAAGCAATGTCTAAGCCT ba +1 AAAAAAAAAGCACTGTCTAAGCCT ab +2 AAAAAAAAAGCTAATAATGCCAGT ab +1 AAAAAAAAAGTTTCGTGAAGGTCC ba +1 AAAAAAAAATAAAGGTCCGAATCT ab +1 AAAAAAAAATAAATGAGAGTGTAA ba +8 AAAAAAAAATAAGTCTCACATTTA ab +1 AAAAAAAAATAATAACCTCTGGCG ab +10 AAAAAAAAATAATAACCTTTGGCG ab +1 AAAAAAAAATAATCCCCTTTGTCG ab +6 AAAAAAAAATACGCAAACGCTGAG ab +4 AAAAAAAAATAGATCATAGACTCT ab +10 AAAAAAAAATAGATCATAGACTCT ba +10 AAAAAAAAATAGTAGGATTTCATG ba +7 AAAAAAAAATATGAATACCCTCGT ba +1 AAAAAAAAATATGCCACTTGATCC ba +1 AAAAAAAAATATTCTGCCACTTGA ba +3 AAAAAAAAATCAAACCAAGAGGAC ba +1 AAAAAAAAATCAGTACCCCTAAAC ab +12 AAAAAAAAATCCTAGTTAATGAAG ba +1 AAAAAAAAATCGATTCTTTATGCG ab +1 AAAAAAAAATGTCTGAAAATATCT ab +4 AAAAAAAAATGTCTGAAAATATCT ba +1 AAAAAAAAATTTCCGCAGACCGTT ba +8 AAAAAAAAATTTGGGCTACTACAA ba +1 AAAAAAAACAAAATTAGAACCCTT ab +1 AAAAAAAACAAACCGCTCCTCACA ba +5 AAAAAAAACAACGTACGCGGTATT ab +4 AAAAAAAACAATATCGTTGATATG ba +4 AAAAAAAACAATCACGTTAATAGG ab +1 AAAAAAAACAGAATCGTGGTTTGT ba +1 AAAAAAAACCAAATCGTTGATATG ba +9 AAAAAAAACCAAGTCCAGGCATCT ba +2 AAAAAAAACCACGGTGAGACAAGG ba +1 AAAAAAAACCGCCCAACTGCCGGT ab +5 AAAAAAAACCTCTCAACCCCAAAT ba +7 AAAAAAAACCTCTTGCGATGTTGT ab +1 AAAAAAAACCTCTTGCGCTGTTGT ab +1 AAAAAAAACCTCTTGTGATGTTGT ab +12 AAAAAAAACCTGAGCAATGGTTCC ab +3 AAAAAAAACCTTGACCCTCACATG ba +6 AAAAAAAACCTTGCACTCGTCCTA ba +9 AAAAAAAACGAAATAAAAAAACCT ba +1 AAAAAAAACGACCGGCCTTAGACA ba +4 AAAAAAAACGCCACCACCCCCTTT ab +12 AAAAAAAACGCCACGGGCACTATT ba +13 AAAAAAAACGTATCAGTAGATCCT ab +1 AAAAAAAACTAGTAGGATTTCATG ba +3 AAAAAAAACTATAGAAAATCCATT ba +1 AAAAAAAACTATTCTATTTCCGAT ba +13 AAAAAAAACTGATCTGCTTGGCGG ba +8 AAAAAAAACTTGCGAATAGCATCG ba +4 AAAAAAAACTTGTTATCAAAACGT ab +1 AAAAAAAAGAAAAGTTCAACACGC ba +1 AAAAAAAAGAAGTTCGCCCTCCGA ab +13 AAAAAAAAGAGAGTTTAGTCATGG ab +1 AAAAAAAAGAGAGTTTAGTCATGG ba +1 AAAAAAAAGAGAGTTTAGTCCTGG ab \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/Test_data4.tabular Mon Oct 08 05:50:18 2018 -0400 @@ -0,0 +1,112 @@ +1 AAAAAAAAAAAAAACCAAAACTTC ba +1 AAAAAAAAAAAAACCAGGCGTCGA ba +1 AAAAAAAAAAAAAGCTCCACGTTG ba +1 AAAAAAAAAAAAATCGTGGTTTGT ba +1 AAAAAAAAAAAAATTCACCCTTGT ba +7 AAAAAAAAAAAACACACTTAACTT ba +1 AAAAAAAAAAAACAGTGTTGAGAC ba +4 AAAAAAAAAAAACCGCTCCTCACA ba +1 AAAAAAAAAAAAGGCAACACAGAA ab +2 AAAAAAAAAAAATCTTTCTTTGAG ab +1 AAAAAAAAAAAATTGGGTTCCTTA ab +1 AAAAAAAAAAAGAGTCGCACCCAG ba +4 AAAAAAAAAAAGATCGTGGTTTGT ba +1 AAAAAAAAAAAGCGCAACACAGAA ab +3 AAAAAAAAAAAGGGCAACACAGAA ab +1 AAAAAAAAAAAGTAGCCCTAAACG ab +1 AAAAAAAAAAAGTCTTTCTTTGAG ab +1 AAAAAAAAAAATATCATAGACTCT ab +6 AAAAAAAAAAATATTCACCCTTGT ba +1 AAAAAAAAAAATATTCGAAAGTTA ba +3 AAAAAAAAAAATCACACTTAACTT ba +1 AAAAAAAAAAATCCGCTCCTCACA ba +1 AAAAAAAAAAATTAACTAAACTTA ab +1 AAAAAAAAAACAAATTCTATTATT ab +1 AAAAAAAAAACTCCCAGATTTTTT ab +1 AAAAAAAAAACTTCTGCTTGGCGG ba +11 AAAAAAAAAAGAATCGTGGTTTGT ba +5 AAAAAAAAAAGATAGCCCTAAACG ab +1 AAAAAAAAAAGCAATAATGCCAGT ab +2 AAAAAAAAAAGTACCGCACTCTCA ba +1 AAAAAAAAAAGTTCTTTCTTTGAG ab +1 AAAAAAAAAATAACTTCAATAATG ba +2 AAAAAAAAAATAATCATAGACTCT ab +1 AAAAAAAAAATAGTCTCACATTTA ab +1 AAAAAAAAAATATAACCTTTGGCG ab +3 AAAAAAAAACAAAATTCTATTATT ab +1 AAAAAAAAACAAGTACGCGGCATT ab +1 AAAAAAAAACAAGTACGCGGTATT ab +1 AAAAAAAAACAATATCGAATTAAC ab +3 AAAAAAAAACACGGTGAGACAAGG ba +1 AAAAAAAAACACGTTTCTCCCCTT ba +1 AAAAAAAAACATATCGTCCCGAGC ba +1 AAAAAAAAACCTACCTGAGGCCCC ab +3 AAAAAAAAACCTTATTACAGCGGA ab +1 AAAAAAAAACGATTCTCTGTATCT ba +1 AAAAAAAAACGTACCGCACTCTCA ba +4 AAAAAAAAACTACCCAGATTTTTT ba +1 AAAAAAAAACTAGATGAGACGACC ba +4 AAAAAAAAACTGTCTGCTTGGCGG ba +1 AAAAAAAAAGAAGTTTAATTTTAA ab +1 AAAAAAAAAGAATGCCTAAGACGA ba +6 AAAAAAAAAGACCGGCCTTAGACA ba +1 AAAAAAAAAGATATCGTGGTTTGT ba +1 AAAAAAAAAGCAATACTCAAGCTG ba +6 AAAAAAAAAGCAATGTCTAAGCCT ba +1 AAAAAAAAAGCACTGTCTAAGCCT ab +2 AAAAAAAAAGCTAATAATGCCAGT ab +1 AAAAAAAAAGTTTCGTGAAGGTCC ba +1 AAAAAAAAATAAAGGTCCGAATCT ab +1 AAAAAAAAATAAATGAGAGTGTAA ba +8 AAAAAAAAATAAGTCTCACATTTA ab +1 AAAAAAAAATAATAACCTCTGGCG ab +10 AAAAAAAAATAATAACCTTTGGCG ab +1 AAAAAAAAATAATCCCCTTTGTCG ab +6 AAAAAAAAATACGCAAACGCTGAG ab +4 AAAAAAAAATAGATCATAGACTCT ab +10 AAAAAAAAATAGATCATAGACTCT ba +10 AAAAAAAAATAGTAGGATTTCATG ba +7 AAAAAAAAATATGAATACCCTCGT ba +1 AAAAAAAAATATGCCACTTGATCC ba +1 AAAAAAAAATATTCTGCCACTTGA ba +3 AAAAAAAAATCAAACCAAGAGGAC ba +1 AAAAAAAAATCAGTACCCCTAAAC ab +12 AAAAAAAAATCCTAGTTAATGAAG ba +1 AAAAAAAAATCGATTCTTTATGCG ab +1 AAAAAAAAATGTCTGAAAATATCT ab +4 AAAAAAAAATGTCTGAAAATATCT ba +1 AAAAAAAAATTTCCGCAGACCGTT ba +8 AAAAAAAAATTTGGGCTACTACAA ba +1 AAAAAAAACAAAATTAGAACCCTT ab +1 AAAAAAAACAAACCGCTCCTCACA ba +5 AAAAAAAACAACGTACGCGGTATT ab +4 AAAAAAAACAATATCGTTGATATG ba +4 AAAAAAAACAATCACGTTAATAGG ab +1 AAAAAAAACAGAATCGTGGTTTGT ba +1 AAAAAAAACCAAATCGTTGATATG ba +9 AAAAAAAACCAAGTCCAGGCATCT ba +2 AAAAAAAACCACGGTGAGACAAGG ba +1 AAAAAAAACCGCCCAACTGCCGGT ab +5 AAAAAAAACCTCTCAACCCCAAAT ba +7 AAAAAAAACCTCTTGCGATGTTGT ab +1 AAAAAAAACCTCTTGCGCTGTTGT ab +1 AAAAAAAACCTCTTGTGATGTTGT ab +12 AAAAAAAACCTGAGCAATGGTTCC ab +3 AAAAAAAACCTTGACCCTCACATG ba +6 AAAAAAAACCTTGCACTCGTCCTA ba +9 AAAAAAAACGAAATAAAAAAACCT ba +1 AAAAAAAACGACCGGCCTTAGACA ba +4 AAAAAAAACGCCACCACCCCCTTT ab +12 AAAAAAAACGCCACGGGCACTATT ba +13 AAAAAAAACGTATCAGTAGATCCT ab +1 AAAAAAAACTAGTAGGATTTCATG ba +3 AAAAAAAACTATAGAAAATCCATT ba +1 AAAAAAAACTATTCTATTTCCGAT ba +13 AAAAAAAACTGATCTGCTTGGCGG ba +8 AAAAAAAACTTGCGAATAGCATCG ba +4 AAAAAAAACTTGTTATCAAAACGT ab +1 AAAAAAAAGAAAAGTTCAACACGC ba +1 AAAAAAAAGAAGTTCGCCCTCCGA ab +13 AAAAAAAAGAGAGTTTAGTCATGG ab +1 AAAAAAAAGAGAGTTTAGTCATGG ba +1 AAAAAAAAGAGAGTTTAGTCCTGG ab \ No newline at end of file
--- a/test-data/output_file.csv Tue Jul 17 07:09:21 2018 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,54 +0,0 @@ -Values from family size distribution with all datasets - -Family size,Test_data,sum -FS=1,63,63 -FS=2,5,5 -FS=3,8,8 -FS=4,10,10 -FS=5,3,3 -FS=6,5,5 -FS=7,3,3 -FS=8,3,3 -FS=9,2,2 -FS=10,3,3 -FS=11,1,1 -FS=12,6,6 -sum,112,112 - -Dataset:,Test_data -max. family size:,13 -absolute frequency:,3 -relative frequency:,0.027 - -,singletons:,,family size > 20: -,absolute nr.,rel. freq,absolute nr.,rel. freq,total length -Test_data,63,0.562,6,0.054,112 - -The unique frequencies were calculated from the dataset where the tags occured only once (=ab without DCS, ba without DCS) -Whereas the total frequencies were calculated from the whole dataset (=including the DCS). - -FS >= 1,,unique:,total: -nr./rel. freq of ab=,47,0.431,0.420 -nr./rel. freq of ba=,59,0.488,0.476 -nr./rel. freq of DCS (total)=,3 (6),0.028,0.027 (0.054) -length of dataset=,109,109,112 -FS >= 3,,unique:,total: -nr./rel. freq of ab=,14,0.341,0.318 -nr./rel. freq of ba=,26,0.491,0.464 -nr./rel. freq of DCS (total)=,1 (2),0.037,0.023 (0.045) -length of dataset=,41,41,44 - -Values from family size distribution -,duplex,ab,ba,sum -FS=1,2,30,31,63 -FS=2,0,3,2,5 -FS=3,0,3,5,8 -FS=4,2,3,5,10 -FS=5,0,2,1,3 -FS=6,0,1,4,5 -FS=7,0,1,2,3 -FS=8,0,1,2,3 -FS=9,0,0,2,2 -FS=10,1,1,1,3 -FS=11,0,0,1,1 -FS=12,1,2,3,6
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/output_file.tabular Mon Oct 08 05:50:18 2018 -0400 @@ -0,0 +1,167 @@ +Values from family size distribution with all datasets + +Family size Test_data Test_data2 Test_data3 Test_data4 +FS=1 63 63 63 63 +FS=2 5 5 5 5 +FS=3 8 8 8 8 +FS=4 10 10 10 10 +FS=5 3 3 3 3 +FS=6 5 5 5 5 +FS=7 3 3 3 3 +FS=8 3 3 3 3 +FS=9 2 2 2 2 +FS=10 3 3 3 3 +FS=11 1 1 1 1 +FS=12 6 6 6 6 +sum 112 112 112 112 +Dataset: Test_data +max. family size: 13 +absolute frequency: 3 +relative frequency: 0.027 + + singletons: family size > 20: + absolute nr. rel. freq absolute nr. rel. freq total length +Test_data 63 0.562 6 0.054 112 + +The unique frequencies were calculated from the dataset where the tags occured only once (=ab without DCS, ba without DCS) +Whereas the total frequencies were calculated from the whole dataset (=including the DCS). + +FS >= 1 unique: total: +nr./rel. freq of ab= 47 0.431 0.420 +nr./rel. freq of ba= 59 0.488 0.476 +nr./rel. freq of DCS (total)= 3 (6) 0.028 0.027 (0.054) +length of dataset= 109 109 112 +FS >= 3 unique: total: +nr./rel. freq of ab= 14 0.341 0.318 +nr./rel. freq of ba= 26 0.491 0.464 +nr./rel. freq of DCS (total)= 1 (2) 0.037 0.023 (0.045) +length of dataset= 41 41 44 + +Values from family size distribution + duplex ab ba sum +FS=1 2 30 31 63 +FS=2 0 3 2 5 +FS=3 0 3 5 8 +FS=4 2 3 5 10 +FS=5 0 2 1 3 +FS=6 0 1 4 5 +FS=7 0 1 2 3 +FS=8 0 1 2 3 +FS=9 0 0 2 2 +FS=10 1 1 1 3 +FS=11 0 0 1 1 +FS=12 1 2 3 6 + +Dataset: Test_data2 +max. family size: 13 +absolute frequency: 3 +relative frequency: 0.027 + + singletons: family size > 20: + absolute nr. rel. freq absolute nr. rel. freq total length +Test_data2 63 0.562 6 0.054 112 + +The unique frequencies were calculated from the dataset where the tags occured only once (=ab without DCS, ba without DCS) +Whereas the total frequencies were calculated from the whole dataset (=including the DCS). + +FS >= 1 unique: total: +nr./rel. freq of ab= 47 0.431 0.420 +nr./rel. freq of ba= 59 0.488 0.476 +nr./rel. freq of DCS (total)= 3 (6) 0.028 0.027 (0.054) +length of dataset= 109 109 112 +FS >= 3 unique: total: +nr./rel. freq of ab= 14 0.341 0.318 +nr./rel. freq of ba= 26 0.491 0.464 +nr./rel. freq of DCS (total)= 1 (2) 0.037 0.023 (0.045) +length of dataset= 41 41 44 + +Values from family size distribution + duplex ab ba sum +FS=1 2 30 31 63 +FS=2 0 3 2 5 +FS=3 0 3 5 8 +FS=4 2 3 5 10 +FS=5 0 2 1 3 +FS=6 0 1 4 5 +FS=7 0 1 2 3 +FS=8 0 1 2 3 +FS=9 0 0 2 2 +FS=10 1 1 1 3 +FS=11 0 0 1 1 +FS=12 1 2 3 6 + +Dataset: Test_data3 +max. family size: 13 +absolute frequency: 3 +relative frequency: 0.027 + + singletons: family size > 20: + absolute nr. rel. freq absolute nr. rel. freq total length +Test_data3 63 0.562 6 0.054 112 + +The unique frequencies were calculated from the dataset where the tags occured only once (=ab without DCS, ba without DCS) +Whereas the total frequencies were calculated from the whole dataset (=including the DCS). + +FS >= 1 unique: total: +nr./rel. freq of ab= 47 0.431 0.420 +nr./rel. freq of ba= 59 0.488 0.476 +nr./rel. freq of DCS (total)= 3 (6) 0.028 0.027 (0.054) +length of dataset= 109 109 112 +FS >= 3 unique: total: +nr./rel. freq of ab= 14 0.341 0.318 +nr./rel. freq of ba= 26 0.491 0.464 +nr./rel. freq of DCS (total)= 1 (2) 0.037 0.023 (0.045) +length of dataset= 41 41 44 + +Values from family size distribution + duplex ab ba sum +FS=1 2 30 31 63 +FS=2 0 3 2 5 +FS=3 0 3 5 8 +FS=4 2 3 5 10 +FS=5 0 2 1 3 +FS=6 0 1 4 5 +FS=7 0 1 2 3 +FS=8 0 1 2 3 +FS=9 0 0 2 2 +FS=10 1 1 1 3 +FS=11 0 0 1 1 +FS=12 1 2 3 6 + +Dataset: Test_data4 +max. family size: 13 +absolute frequency: 3 +relative frequency: 0.027 + + singletons: family size > 20: + absolute nr. rel. freq absolute nr. rel. freq total length +Test_data4 63 0.562 6 0.054 112 + +The unique frequencies were calculated from the dataset where the tags occured only once (=ab without DCS, ba without DCS) +Whereas the total frequencies were calculated from the whole dataset (=including the DCS). + +FS >= 1 unique: total: +nr./rel. freq of ab= 47 0.431 0.420 +nr./rel. freq of ba= 59 0.488 0.476 +nr./rel. freq of DCS (total)= 3 (6) 0.028 0.027 (0.054) +length of dataset= 109 109 112 +FS >= 3 unique: total: +nr./rel. freq of ab= 14 0.341 0.318 +nr./rel. freq of ba= 26 0.491 0.464 +nr./rel. freq of DCS (total)= 1 (2) 0.037 0.023 (0.045) +length of dataset= 41 41 44 + +Values from family size distribution + duplex ab ba sum +FS=1 2 30 31 63 +FS=2 0 3 2 5 +FS=3 0 3 5 8 +FS=4 2 3 5 10 +FS=5 0 2 1 3 +FS=6 0 1 4 5 +FS=7 0 1 2 3 +FS=8 0 1 2 3 +FS=9 0 0 2 2 +FS=10 1 1 1 3 +FS=11 0 0 1 1 +FS=12 1 2 3 6
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/output_file2.tabular Mon Oct 08 05:50:18 2018 -0400 @@ -0,0 +1,129 @@ +Values from family size distribution with all datasets + +Family size Test_data Test_data2 Test_data3 +FS=1 63 63 63 +FS=2 5 5 5 +FS=3 8 8 8 +FS=4 10 10 10 +FS=5 3 3 3 +FS=6 5 5 5 +FS=7 3 3 3 +FS=8 3 3 3 +FS=9 2 2 2 +FS=10 3 3 3 +FS=11 1 1 1 +FS=12 6 6 6 +sum 112 112 112 +Dataset: Test_data +max. family size: 13 +absolute frequency: 3 +relative frequency: 0.027 + + singletons: family size > 20: + absolute nr. rel. freq absolute nr. rel. freq total length +Test_data 63 0.562 6 0.054 112 + +The unique frequencies were calculated from the dataset where the tags occured only once (=ab without DCS, ba without DCS) +Whereas the total frequencies were calculated from the whole dataset (=including the DCS). + +FS >= 1 unique: total: +nr./rel. freq of ab= 47 0.431 0.420 +nr./rel. freq of ba= 59 0.488 0.476 +nr./rel. freq of DCS (total)= 3 (6) 0.028 0.027 (0.054) +length of dataset= 109 109 112 +FS >= 3 unique: total: +nr./rel. freq of ab= 14 0.341 0.318 +nr./rel. freq of ba= 26 0.491 0.464 +nr./rel. freq of DCS (total)= 1 (2) 0.037 0.023 (0.045) +length of dataset= 41 41 44 + +Values from family size distribution + duplex ab ba sum +FS=1 2 30 31 63 +FS=2 0 3 2 5 +FS=3 0 3 5 8 +FS=4 2 3 5 10 +FS=5 0 2 1 3 +FS=6 0 1 4 5 +FS=7 0 1 2 3 +FS=8 0 1 2 3 +FS=9 0 0 2 2 +FS=10 1 1 1 3 +FS=11 0 0 1 1 +FS=12 1 2 3 6 + +Dataset: Test_data2 +max. family size: 13 +absolute frequency: 3 +relative frequency: 0.027 + + singletons: family size > 20: + absolute nr. rel. freq absolute nr. rel. freq total length +Test_data2 63 0.562 6 0.054 112 + +The unique frequencies were calculated from the dataset where the tags occured only once (=ab without DCS, ba without DCS) +Whereas the total frequencies were calculated from the whole dataset (=including the DCS). + +FS >= 1 unique: total: +nr./rel. freq of ab= 47 0.431 0.420 +nr./rel. freq of ba= 59 0.488 0.476 +nr./rel. freq of DCS (total)= 3 (6) 0.028 0.027 (0.054) +length of dataset= 109 109 112 +FS >= 3 unique: total: +nr./rel. freq of ab= 14 0.341 0.318 +nr./rel. freq of ba= 26 0.491 0.464 +nr./rel. freq of DCS (total)= 1 (2) 0.037 0.023 (0.045) +length of dataset= 41 41 44 + +Values from family size distribution + duplex ab ba sum +FS=1 2 30 31 63 +FS=2 0 3 2 5 +FS=3 0 3 5 8 +FS=4 2 3 5 10 +FS=5 0 2 1 3 +FS=6 0 1 4 5 +FS=7 0 1 2 3 +FS=8 0 1 2 3 +FS=9 0 0 2 2 +FS=10 1 1 1 3 +FS=11 0 0 1 1 +FS=12 1 2 3 6 + +Dataset: Test_data3 +max. family size: 13 +absolute frequency: 3 +relative frequency: 0.027 + + singletons: family size > 20: + absolute nr. rel. freq absolute nr. rel. freq total length +Test_data3 63 0.562 6 0.054 112 + +The unique frequencies were calculated from the dataset where the tags occured only once (=ab without DCS, ba without DCS) +Whereas the total frequencies were calculated from the whole dataset (=including the DCS). + +FS >= 1 unique: total: +nr./rel. freq of ab= 47 0.431 0.420 +nr./rel. freq of ba= 59 0.488 0.476 +nr./rel. freq of DCS (total)= 3 (6) 0.028 0.027 (0.054) +length of dataset= 109 109 112 +FS >= 3 unique: total: +nr./rel. freq of ab= 14 0.341 0.318 +nr./rel. freq of ba= 26 0.491 0.464 +nr./rel. freq of DCS (total)= 1 (2) 0.037 0.023 (0.045) +length of dataset= 41 41 44 + +Values from family size distribution + duplex ab ba sum +FS=1 2 30 31 63 +FS=2 0 3 2 5 +FS=3 0 3 5 8 +FS=4 2 3 5 10 +FS=5 0 2 1 3 +FS=6 0 1 4 5 +FS=7 0 1 2 3 +FS=8 0 1 2 3 +FS=9 0 0 2 2 +FS=10 1 1 1 3 +FS=11 0 0 1 1 +FS=12 1 2 3 6