# HG changeset patch # User iuc # Date 1450821807 18000 # Node ID 25cd59a002d9a9d425162f831040a24530cbdfb1 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/genetrack commit e96df94dba60050fa28aaf55b5bb095717a5f260 diff -r 000000000000 -r 25cd59a002d9 genetrack.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/genetrack.py Tue Dec 22 17:03:27 2015 -0500 @@ -0,0 +1,65 @@ +""" +genetrack.py + +Input: either scidx or gff format of reads +Output: Called peaks in gff format +""" +import optparse +import csv +import os +import genetrack_util + +CHUNK_SIZE = 10000000 + + +if __name__ == '__main__': + parser = optparse.OptionParser() + parser.add_option('-t', '--input_format', dest='input_format', type='string', help='Input format') + parser.add_option('-i', '--input', dest='inputs', type='string', action='append', nargs=2, help='Input datasets') + parser.add_option('-s', '--sigma', dest='sigma', type='int', default=5, help='Sigma.') + parser.add_option('-e', '--exclusion', dest='exclusion', type='int', default=20, help='Exclusion zone.') + parser.add_option('-u', '--up_width', dest='up_width', type='int', default=10, help='Upstream width of called peaks.') + parser.add_option('-d', '--down_width', dest='down_width', type='int', default=10, help='Downstream width of called peaks.') + parser.add_option('-f', '--filter', dest='filter', type='int', default=1, help='Absolute read filter.') + options, args = parser.parse_args() + + os.mkdir('output') + for (dataset_path, hid) in options.inputs: + if options.input_format == 'gff': + # Make sure the reads for each chromosome are sorted by index. + input_path = genetrack_util.sort_chromosome_reads_by_index(dataset_path) + else: + # We're processing scidx data. + input_path = dataset_path + output_name = 's%se%su%sd%sF%s_on_data_%s' % (options.sigma, + options.exclusion, + options.up_width, + options.down_width, + options.filter, + hid) + output_path = os.path.join('output', output_name) + reader = csv.reader(open(input_path, 'rU'), delimiter='\t') + writer = csv.writer(open(output_path, 'wt'), delimiter='\t') + width = options.sigma * 5 + manager = genetrack_util.ChromosomeManager(reader) + while not manager.done: + cname = manager.chromosome_name() + # Should we process this chromosome? + data = manager.load_chromosome() + if not data: + continue + keys = genetrack_util.make_keys(data) + lo, hi = genetrack_util.get_range(data) + for chunk in genetrack_util.get_chunks(lo, hi, size=CHUNK_SIZE, overlap=width): + (slice_start, slice_end), process_bounds = chunk + window = genetrack_util.get_window(data, slice_start, slice_end, keys) + genetrack_util.process_chromosome(cname, + window, + writer, + process_bounds, + width, + options.sigma, + options.up_width, + options.down_width, + options.exclusion, + options.filter) diff -r 000000000000 -r 25cd59a002d9 genetrack.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/genetrack.xml Tue Dec 22 17:03:27 2015 -0500 @@ -0,0 +1,173 @@ + + + peak predictor + + genetrack_macros.xml + + + + python $__tool_directory__/genetrack.py + --input_format $input_format_cond.input_format + #for $i in $input_format_cond.input: + --input "${i}" "${i.hid}" + #end for + --sigma $sigma + --exclusion $exclusion + --up_width $up_width + --down_width $down_width + --filter $filter + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +**What it does** + +GeneTrack separately identifies peaks on the forward "+” (W) and reverse “-” (C) strand. The way that GeneTrack +works is to replace each tag with a probabilistic distribution of occurrences for that tag at and around its mapped +genomic coordinate. The distance decay of the probabilistic distribution is set by adjusting the value of the +tool's **Sigma to use when smoothing reads** parameter. GeneTrack then sums the distribution over all mapped +tags. This results in a smooth continuous trace that can be globally broadened or tightened by adjusting the +sigma value. GeneTrack starts with the highest smoothed peak first, treating each strand separately if indicated +by the data, then sets up an exclusion zone (centered over the peak) defined by the value of the **Peak exclusion +zone** parameter (see figure). The exclusion zone prevents any secondary peaks from being called on the same strand +within that exclusion zone. In rare cases, it may be desirable to set different exclusion zones upstream (more 5’) +versus downstream (more 3’) of the peak. + +.. image:: $PATH_TO_IMAGES/genetrack.png + +GeneTrack continues through the data in order of peak height, until no other peaks are found, and in principle will +call a peak at a single isolated tag, if no filter is set using the tool's **Absolute read filter** parameter. A +filter value of 1 means that it will stop calling peaks when the tag count in the peak hits 1 (so single tag peaks +will be excluded in this case). GeneTrack outputs **chrom** (chromosome number), **strand** (+/W or -/C strand), +**start** (lower coordinate of exclusion zone), **end** (higher coordinate of exclusion zone), and **value** (peak +height). Genetrack's GFF output reports the start (lower coordinate) and end (higher coordinate) of the exclusion +zone. + +In principle, the width of the exclusion zone may be as large as the DNA region occupied by the native protein plus +a steric exclusion zone between the protein and the exonuclease. On the other hand the site might be considerably +smaller if the protein is in a denatured state during exonuclease digestion (since it is pre-treated with SDS). + +In general, higher resolution data or smaller binding site size data should use smaller sigma values. Large binding +site size data such as 147 bp nucleosomal DNA use a larger sigma value like 20 (-s 20). For transcription factors +mapped by ChIP-exo, sigma may initially be set at 5, and the exclusion zone set at 20 (-s 5 –e 20). Sigma is typically +varied between ~3 and ~20. Too high of a sigma value may merge two independent nearby binding events. This may be +desirable if closely bound factors are not distinguishable. Too low of a sigma value will cause some tags that +contribute to a binding event to be excluded, because they may not be located sufficiently close to the main peak. +If alternative (mutually exclusive) binding is expected for two overlapping sites, and these sites are to be +independently recorded, then an empirically determined smaller exclusion zone width is set. Thus the value of sigma +is set empirically for each mapped factor, depending upon the resolution and binding site size of the binding event. + +It might make sense to exclude peaks that have only a single tag, where -F 1 is used, or have their tags located on +only a single coordinate (called Singletons, where stddev=0 in the output file). However, low coverage datasets might +be improved by including them, if additional analysis (e.g., motif discovery) validates them. In addition, idealized +action of the exonuclease in ChIP-exo might place all tags for a peak on a single coordinate. + +----- + +**Options** + + * **Sigma to use when smoothing reads** - Smooths clusters of tags via a Gaussian distribution. + * **Peak exclusion zone** - Exclusion zone around each peak, eliminating all other peaks on the same strand that are within a ± bp distance of the peak. + * **Exclusion zone of upstream called peaks** - Defines the exclusion zone centered over peaks upstream of a peak. + * **Exclusion zone of downstream called peaks** - Defines the exclusion zone centered over peaks downstream of a peak. + * **Filter** - Absolute read filter, restricts output to only peaks with larger peak height. + +----- + +**Output gff Columns** + +1. Chromosome +2. Script +3. Placeholder (no meaning) +4. Start of peak exclusion zone (-e 20) +5. End of peak exclusion zone +6. Tag sum (not peak height or area under curve, which LionDB provides) +7. Strand +8. Placeholder (no meaning) +9. Attributes (standard deviation of reads located within exclusion zone) = fuzziness of peak + +----- + +**Considerations** + +In principle, the width of the exclusion zone may be as large as the DNA region occupied by the native protein +plus a steric exclusion zone between the protein and the exonuclease. On the other hand the site might be considerably +smaller if the protein is in a denatured state during exonuclease digestion (since it is pre-treated with SDS). + +In general, higher resolution data or smaller binding site size data should use smaller sigma values. Large binding site +size data such as 147 bp nucleosomal DNA use a larger sigma value like 20 (-s 20). For transcription factors mapped by +ChIP-exo, sigma may initially be set at 5, and the exclusion zone set at 20 (-s 5 –e 20). Sigma is typically varied +between ~3 and ~20. Too high of a sigma value may merge two independent nearby binding events. This may be desirable if +closely bound factors are not distinguishable. Too low of a sigma value will cause some tags that contribute to a binding +event to be excluded, because they may not be located sufficiently close to the main peak. If alternative (mutually +exclusive) binding is expected for two overlapping sites, and these sites are to be independently recorded, then an +empirically determined smaller exclusion zone width is set. Thus, the value of sigma is set empirically for each mappedfactor depending upon the resolution and binding site size of the binding event. + +It might make sense to exclude peaks that have only a single tag, where -F 1 is used, or have their tags located on only +a single coordinate (called Singletons, where stddev=0 in the output file). However, low coverage datasets might be +improved by including them, if additional analysis (e.g., motif discovery) validates them. In addition, idealized action +of the exonuclease in ChIP-exo might place all tags for a peak on a single coordinate. + + + + diff -r 000000000000 -r 25cd59a002d9 genetrack_macros.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/genetrack_macros.xml Tue Dec 22 17:03:27 2015 -0500 @@ -0,0 +1,22 @@ + + + 1.0 + + + anaconda + + + + + + + + + + + + + 10.1093/bioinformatics/btn119 + + + diff -r 000000000000 -r 25cd59a002d9 genetrack_util.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/genetrack_util.py Tue Dec 22 17:03:27 2015 -0500 @@ -0,0 +1,390 @@ +import bisect +import math +import numpy +import re +import subprocess +import sys +import tempfile + +GFF_EXT = 'gff' +SCIDX_EXT = 'scidx' + + +def noop(data): + return data + + +def zeropad_to_numeric(data): + return re.sub(r'chr0(\d)', r'chr\1', data) + + +def numeric_to_zeropad(data): + return re.sub(r'chr(\d([^\d]|$))', r'chr0\1', data) + + +FORMATS = ['zeropad', 'numeric'] +IN_CONVERT = {'zeropad': zeropad_to_numeric, 'numeric': noop} +OUT_CONVERT = {'zeropad': numeric_to_zeropad, 'numeric': noop} + + +def conversion_functions(in_fmt, out_fmt): + """ + Returns the proper list of functions to apply to perform a conversion + """ + return [IN_CONVERT[in_fmt], OUT_CONVERT[out_fmt]] + + +def convert_data(data, in_fmt, out_fmt): + for fn in conversion_functions(in_fmt, out_fmt): + data = fn(data) + return data + + +class ChromosomeManager(object): + """ + Manages a CSV reader of an index file to only load one chrom at a time + """ + + def __init__(self, reader): + self.done = False + self.reader = reader + self.processed_chromosomes = [] + self.current_index = 0 + self.next_valid() + + def next(self): + self.line = self.reader.next() + + def is_valid(self, line): + if len(line) not in [4, 5, 9]: + return False + try: + [int(i) for i in line[1:]] + self.format = SCIDX_EXT + return True + except ValueError: + try: + if len(line) < 6: + return False + [int(line[4]), int(line[5])] + self.format = GFF_EXT + return True + except ValueError: + return False + + def next_valid(self): + """ + Advance to the next valid line in the reader + """ + self.line = self.reader.next() + s = 0 + while not self.is_valid(self.line): + self.line = self.reader.next() + s += 1 + if s > 0: + # Skip initial line(s) of file + pass + + def parse_line(self, line): + if self.format == SCIDX_EXT: + return [int(line[1]), int(line[2]), int(line[3])] + else: + return [int(line[3]), line[6], line[5]] + + def chromosome_name(self): + """ + Return the name of the chromosome about to be loaded + """ + return self.line[0] + + def load_chromosome(self, collect_data=True): + """ + Load the current chromosome into an array and return it + """ + cname = self.chromosome_name() + if cname in self.processed_chromosomes: + stop_err('File is not grouped by chromosome') + self.data = [] + while self.line[0] == cname: + if collect_data: + read = self.parse_line(self.line) + if read[0] < self.current_index: + msg = 'Reads in chromosome %s are not sorted by index. (At index %d)' % (cname, self.current_index) + stop_err(msg) + self.current_index = read[0] + self.add_read(read) + try: + self.next() + except StopIteration: + self.done = True + break + self.processed_chromosomes.append(cname) + self.current_index = 0 + data = self.data + # Don't retain reference anymore to save memory + del self.data + return data + + def add_read(self, read): + if self.format == SCIDX_EXT: + self.data.append(read) + else: + index, strand, value = read + if value == '' or value == '.': + value = 1 + else: + value = int(value) + if not self.data: + self.data.append([index, 0, 0]) + current_read = self.data[-1] + if self.data[-1][0] == index: + current_read = self.data[-1] + elif self.data[-1][0] < index: + self.data.append([index, 0, 0]) + current_read = self.data[-1] + else: + msg = 'Reads in chromosome %s are not sorted by index. (At index %d)' % (self.chromosome_name(), index) + stop_err(msg) + if strand == '+': + current_read[1] += value + elif strand == '-': + current_read[2] += value + else: + msg = 'Strand "%s" at chromosome "%s" index %d is not valid.' % (strand, self.chromosome_name(), index) + stop_err(msg) + + def skip_chromosome(self): + """ + Skip the current chromosome, discarding data + """ + self.load_chromosome(collect_data=False) + + +class Peak(object): + def __init__(self, index, pos_width, neg_width): + self.index = index + self.start = index - neg_width + self.end = index + pos_width + self.value = 0 + self.deleted = False + self.safe = False + + def __repr__(self): + return '[%d] %d' % (self.index, self.value) + + +def gff_row(cname, start, end, score, source, type='.', strand='.', phase='.', attrs={}): + return (cname, source, type, start, end, score, strand, phase, gff_attrs(attrs)) + + +def gff_attrs(d): + if not d: + return '.' + return ';'.join('%s=%s' % item for item in d.items()) + + +def stop_err(msg): + sys.stderr.write(msg) + sys.exit(1) + + +def is_int(i): + try: + int(i) + return True + except ValueError: + return False + + +def make_keys(data): + return [read[0] for read in data] + + +def make_peak_keys(peaks): + return [peak.index for peak in peaks] + + +def get_window(data, start, end, keys): + """ + Returns all reads from the data set with index between the two indexes + """ + start_index = bisect.bisect_left(keys, start) + end_index = bisect.bisect_right(keys, end) + return data[start_index:end_index] + + +def get_index(value, keys): + """ + Returns the index of the value in the keys using bisect + """ + return bisect.bisect_left(keys, value) + + +def get_range(data): + lo = min([item[0] for item in data]) + hi = max([item[0] for item in data]) + return lo, hi + + +def get_chunks(lo, hi, size, overlap=500): + """ + Divides a range into chunks of maximum size size. Returns a list of + 2-tuples (slice_range, process_range), each a 2-tuple (start, end). + process_range has zero overlap and should be given to process_chromosome + as-is, and slice_range is overlapped and should be used to slice the + data (using get_window) to be given to process_chromosome. + """ + chunks = [] + for start_index in range(lo, hi, size): + process_start = start_index + # Don't go over upper bound + process_end = min(start_index + size, hi) + # Don't go under lower bound + slice_start = max(process_start - overlap, lo) + # Don't go over upper bound + slice_end = min(process_end + overlap, hi) + chunks.append(((slice_start, slice_end), (process_start, process_end))) + return chunks + + +def allocate_array(data, width): + """ + Allocates a new array with the dimensions required to fit all reads in + the argument. The new array is totally empty. Returns the array and the + shift (number to add to a read index to get the position in the array it + should be at). + """ + lo, hi = get_range(data) + rng = hi - lo + shift = width - lo + return numpy.zeros(rng+width*2, numpy.float), shift + + +def normal_array(width, sigma, normalize=True): + """ + Returns an array of the normal distribution of the specified width + """ + sigma2 = float(sigma)**2 + + def normal_func(x): + return math.exp(-x * x / (2 * sigma2)) + + # width is the half of the distribution + values = map(normal_func, range(-width, width)) + values = numpy.array(values, numpy.float) + # normalization + if normalize: + values = 1.0/math.sqrt(2 * numpy.pi * sigma2) * values + return values + + +def call_peaks(array, shift, data, keys, direction, down_width, up_width, exclusion): + peaks = [] + + def find_peaks(): + # Go through the array and call each peak + results = (array > numpy.roll(array, 1)) & (array > numpy.roll(array, -1)) + indexes = numpy.where(results) + for index in indexes[0]: + pos = down_width or exclusion // 2 + neg = up_width or exclusion // 2 + # Reverse strand + if direction == 2: + # Swap positive and negative widths + pos, neg = neg, pos + peaks.append(Peak(int(index)-shift, pos, neg)) + find_peaks() + + def calculate_reads(): + # Calculate the number of reads in each peak + for peak in peaks: + reads = get_window(data, peak.start, peak.end, keys) + peak.value = sum([read[direction] for read in reads]) + # Flat list of indexes with frequency + indexes = [r for read in reads for r in [read[0]] * read[direction]] + peak.stddev = numpy.std(indexes) + calculate_reads() + + def perform_exclusion(): + # Process the exclusion zone + peak_keys = make_peak_keys(peaks) + peaks_by_value = peaks[:] + peaks_by_value.sort(key=lambda peak: -peak.value) + for peak in peaks_by_value: + peak.safe = True + window = get_window(peaks, + peak.index-exclusion//2, + peak.index+exclusion//2, + peak_keys) + for excluded in window: + if excluded.safe: + continue + i = get_index(excluded.index, peak_keys) + del peak_keys[i] + del peaks[i] + perform_exclusion() + return peaks + + +def process_chromosome(cname, data, writer, process_bounds, width, sigma, down_width, up_width, exclusion, filter): + """ + Process a chromosome. Takes the chromosome name, list of reads, a CSV + writer to write processes results to, the bounds (2-tuple) to write + results in, and options. + """ + if not data: + return + keys = make_keys(data) + # Create the arrays that hold the sum of the normals + forward_array, forward_shift = allocate_array(data, width) + reverse_array, reverse_shift = allocate_array(data, width) + normal = normal_array(width, sigma) + + def populate_array(): + # Add each read's normal to the array + for read in data: + index, forward, reverse = read + # Add the normals to the appropriate regions + if forward: + forward_array[index+forward_shift-width:index+forward_shift+width] += normal * forward + if reverse: + reverse_array[index+reverse_shift-width:index+reverse_shift+width] += normal * reverse + populate_array() + forward_peaks = call_peaks(forward_array, forward_shift, data, keys, 1, down_width, up_width, exclusion) + reverse_peaks = call_peaks(reverse_array, reverse_shift, data, keys, 2, down_width, up_width, exclusion) + # Convert chromosome name in preparation for writing output + cname = convert_data(cname, 'zeropad', 'numeric') + + def write(cname, strand, peak): + start = max(peak.start, 1) + end = peak.end + value = peak.value + stddev = peak.stddev + if value > filter: + # This version of genetrack outputs only gff files. + writer.writerow(gff_row(cname=cname, + source='genetrack', + start=start, + end=end, + score=value, + strand=strand, + attrs={'stddev': stddev})) + + for peak in forward_peaks: + if process_bounds[0] < peak.index < process_bounds[1]: + write(cname, '+', peak) + for peak in reverse_peaks: + if process_bounds[0] < peak.index < process_bounds[1]: + write(cname, '-', peak) + + +def sort_chromosome_reads_by_index(input_path): + """ + Return a gff file with chromosome reads sorted by index. + """ + # Will this sort produce different results across platforms? + output_path = tempfile.NamedTemporaryFile(delete=False).name + command = 'sort -k 1,1 -k 4,4n "%s" > "%s"' % (input_path, output_path) + p = subprocess.Popen(command, shell=True) + p.wait() + return output_path diff -r 000000000000 -r 25cd59a002d9 static/images/genetrack.png Binary file static/images/genetrack.png has changed diff -r 000000000000 -r 25cd59a002d9 test-data/genetrack_input2.gff --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/genetrack_input2.gff Tue Dec 22 17:03:27 2015 -0500 @@ -0,0 +1,100 @@ +chr1 genetrack . 17 37 918 + . stddev=5.96715849116 +chr1 genetrack . 31 51 245 - . stddev=2.66582799529 +chr1 genetrack . 40 60 2060 + . stddev=2.7859667372 +chr1 genetrack . 62 82 1300 - . stddev=4.13061337623 +chr1 genetrack . 73 93 397 + . stddev=0.0 +chr1 genetrack . 89 109 521 + . stddev=0.747112137937 +chr1 genetrack . 123 143 5129 + . stddev=3.01025384354 +chr1 genetrack . 125 145 4659 - . stddev=3.8642622228 +chr1 genetrack . 155 175 897 - . stddev=3.22709952671 +chr1 genetrack . 171 191 956 - . stddev=4.95899971687 +chr1 genetrack . 180 200 1527 + . stddev=4.62574275346 +chr1 genetrack . 185 205 494 - . stddev=1.4255957 +chr1 genetrack . 192 212 2538 + . stddev=5.04731591122 +chr1 genetrack . 206 226 2087 - . stddev=3.6160253713 +chr1 genetrack . 238 258 2496 + . stddev=2.11105291581 +chr1 genetrack . 242 262 5047 - . stddev=3.62629343395 +chr1 genetrack . 254 274 1525 + . stddev=4.46082441647 +chr1 genetrack . 281 301 15 + . stddev=1.74610678049 +chr1 genetrack . 302 322 626 - . stddev=0.0 +chr1 genetrack . 308 328 1544 + . stddev=4.43066151722 +chr1 genetrack . 334 354 533 + . stddev=1.34355443899 +chr1 genetrack . 344 364 726 - . stddev=1.36767079956 +chr1 genetrack . 347 367 286 + . stddev=0.0 +chr1 genetrack . 358 378 792 - . stddev=1.47737416556 +chr1 genetrack . 374 394 608 + . stddev=1.44652711793 +chr1 genetrack . 389 409 126 - . stddev=0.471404520791 +chr1 genetrack . 439 459 618 - . stddev=5.47536569145 +chr1 genetrack . 441 461 1393 + . stddev=4.75587332865 +chr1 genetrack . 461 481 754 - . stddev=3.28891288785 +chr1 genetrack . 483 503 58 + . stddev=0.0 +chr1 genetrack . 538 558 1015 - . stddev=0.0 +chr1 genetrack . 728 748 39 - . stddev=0.0 +chr1 genetrack . 757 777 23 + . stddev=0.0 +chr1 genetrack . 799 819 607 + . stddev=0.0 +chr1 genetrack . 844 864 665 + . stddev=0.0 +chr1 genetrack . 877 897 468 + . stddev=0.0 +chr1 genetrack . 903 923 107 - . stddev=0.0 +chr1 genetrack . 944 964 2 - . stddev=0.0 +chr1 genetrack . 1092 1112 740 + . stddev=0.0 +chr1 genetrack . 1127 1147 940 - . stddev=3.96036497305 +chr1 genetrack . 1183 1203 25 + . stddev=0.0 +chr1 genetrack . 1291 1311 454 - . stddev=0.0 +chr1 genetrack . 1329 1349 207 - . stddev=0.0 +chr1 genetrack . 1484 1504 584 + . stddev=0.0 +chr1 genetrack . 2075 2095 1181 + . stddev=0.0 +chr1 genetrack . 2102 2122 481 + . stddev=0.0455486534308 +chr1 genetrack . 2125 2145 199 - . stddev=0.0 +chr1 genetrack . 2452 2472 1246 + . stddev=0.0 +chr1 genetrack . 2602 2622 34 + . stddev=0.0 +chr1 genetrack . 2833 2853 1062 + . stddev=1.01561431542 +chr1 genetrack . 2838 2858 1144 - . stddev=1.09438744148 +chr1 genetrack . 3011 3031 1212 - . stddev=0.0 +chr1 genetrack . 3116 3136 555 - . stddev=0.0 +chr1 genetrack . 3130 3150 17 + . stddev=0.0 +chr1 genetrack . 3378 3398 525 - . stddev=0.0 +chr1 genetrack . 3669 3689 845 + . stddev=0.0 +chr1 genetrack . 3785 3805 23 - . stddev=0.0 +chr1 genetrack . 3847 3867 316 - . stddev=0.0 +chr1 genetrack . 3868 3888 491 + . stddev=0.0 +chr1 genetrack . 4097 4117 536 - . stddev=0.0 +chr1 genetrack . 4326 4346 482 + . stddev=0.0 +chr1 genetrack . 4395 4415 3 + . stddev=0.0 +chr1 genetrack . 4461 4481 1110 + . stddev=0.0 +chr1 genetrack . 4500 4520 125 - . stddev=0.0 +chr1 genetrack . 4620 4640 147 + . stddev=0.0 +chr1 genetrack . 4826 4846 1761 + . stddev=4.82408982772 +chr1 genetrack . 4902 4922 710 + . stddev=0.0 +chr1 genetrack . 5110 5130 828 + . stddev=0.0 +chr1 genetrack . 5402 5422 282 - . stddev=0.0 +chr1 genetrack . 5501 5521 75 + . stddev=0.0 +chr1 genetrack . 5707 5727 2 + . stddev=0.0 +chr1 genetrack . 5717 5737 737 - . stddev=0.36608362591 +chr1 genetrack . 6086 6106 646 + . stddev=0.039314009595 +chr1 genetrack . 6098 6118 230 - . stddev=0.0657945476105 +chr1 genetrack . 6187 6207 329 - . stddev=0.0 +chr1 genetrack . 6290 6310 5 + . stddev=0.0 +chr1 genetrack . 6356 6376 285 + . stddev=0.0 +chr1 genetrack . 6380 6400 34 - . stddev=0.0 +chr1 genetrack . 6401 6421 1587 + . stddev=5.61831543503 +chr1 genetrack . 6415 6435 953 - . stddev=3.52372902021 +chr1 genetrack . 6432 6452 742 + . stddev=0.0 +chr1 genetrack . 6496 6516 691 + . stddev=0.0 +chr1 genetrack . 6506 6526 61 - . stddev=1.5137105198 +chr1 genetrack . 6843 6863 28 + . stddev=0.0 +chr1 genetrack . 7058 7078 518 - . stddev=0.0 +chr1 genetrack . 7124 7144 654 + . stddev=0.0 +chr1 genetrack . 7765 7785 714 + . stddev=0.0 +chr1 genetrack . 7847 7867 3 + . stddev=0.0 +chr1 genetrack . 8209 8229 17 + . stddev=0.0 +chr1 genetrack . 8272 8292 2 - . stddev=0.0 +chr1 genetrack . 8459 8479 10 + . stddev=0.0 +chr1 genetrack . 8471 8491 5 - . stddev=0.0 +chr1 genetrack . 8715 8735 5 + . stddev=0.0 +chr1 genetrack . 8834 8854 332 + . stddev=0.0 +chr1 genetrack . 8839 8859 593 - . stddev=0.0 +chr1 genetrack . 9034 9054 24 + . stddev=0.0 +chr1 genetrack . 9058 9078 4 + . stddev=0.0 +chr1 genetrack . 9485 9505 36 + . stddev=0.0 +chr1 genetrack . 9710 9730 480 + . stddev=0.0 +chr1 genetrack . 9923 9943 606 - . stddev=0.0 diff -r 000000000000 -r 25cd59a002d9 test-data/genetrack_input3.scidx --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/genetrack_input3.scidx Tue Dec 22 17:03:27 2015 -0500 @@ -0,0 +1,100 @@ +chrom index forward reverse value +chr01 7 2 0 2 +chr01 8 3 0 3 +chr01 10 2 0 2 +chr01 14 1 0 1 +chr01 15 1 0 1 +chr01 16 1 0 1 +chr01 31 1 0 1 +chr01 32 1 0 1 +chr01 35 1 0 1 +chr01 37 2 0 2 +chr01 38 65 0 65 +chr01 39 8 4 12 +chr01 40 3 0 3 +chr01 41 3 2 5 +chr01 42 3 1 4 +chr01 43 2 2 4 +chr01 44 0 1 1 +chr01 46 3 0 3 +chr01 52 0 1 1 +chr01 54 7 0 7 +chr01 55 2 0 2 +chr01 56 1 0 1 +chr01 58 0 1 1 +chr01 61 0 1 1 +chr01 62 1 3 4 +chr01 63 0 1 1 +chr01 64 2 4 6 +chr01 66 0 13 13 +chr01 67 0 4 4 +chr01 72 0 5 5 +chr01 75 4 0 4 +chr01 77 0 6 6 +chr01 81 13 0 13 +chr01 83 1 0 1 +chr01 85 0 4 4 +chr01 86 0 1 1 +chr01 89 4 0 4 +chr01 90 1 0 1 +chr01 91 2 0 2 +chr01 92 4 1 5 +chr01 93 4 0 4 +chr01 96 1 0 1 +chr01 97 1 0 1 +chr01 98 4 0 4 +chr01 99 8 0 8 +chr01 102 1 1 2 +chr01 105 0 1 1 +chr01 107 0 3 3 +chr01 109 0 4 4 +chr01 110 2 1 3 +chr01 111 6 0 6 +chr01 112 0 3 3 +chr01 113 24 0 24 +chr01 114 0 32 32 +chr01 115 5 4 9 +chr01 116 36 5 41 +chr01 117 194 5 199 +chr01 118 100 2 102 +chr01 119 98 19 117 +chr01 120 92 7 99 +chr01 121 112 11 123 +chr01 122 36 3 39 +chr01 123 18 16 34 +chr01 124 9 14 23 +chr01 125 14 12 26 +chr01 126 20 1 21 +chr01 127 4 2 6 +chr01 128 66 6 72 +chr01 129 3 6 9 +chr01 130 2 10 12 +chr01 131 62 0 62 +chr01 132 20 1 21 +chr01 133 64 1 65 +chr01 134 58 0 58 +chr01 135 83 4 87 +chr01 136 92 1 93 +chr01 137 12 0 12 +chr01 138 0 3 3 +chr01 139 0 2 2 +chr01 142 0 48 48 +chr01 143 0 15 15 +chr01 144 0 74 74 +chr01 145 23 11 34 +chr01 146 1 120 121 +chr01 147 0 574 574 +chr01 148 0 11 11 +chr01 150 1 0 1 +chr01 151 3 4 7 +chr01 152 0 2 2 +chr01 153 1 3 4 +chr01 155 8 11 19 +chr01 156 0 14 14 +chr01 158 0 3 3 +chr01 159 0 1 1 +chr01 160 0 1 1 +chr01 161 0 5 5 +chr01 163 0 2 2 +chr01 164 0 29 29 +chr01 165 0 1 1 diff -r 000000000000 -r 25cd59a002d9 test-data/genetrack_input_unsorted4.gff --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/genetrack_input_unsorted4.gff Tue Dec 22 17:03:27 2015 -0500 @@ -0,0 +1,100 @@ +chr1 genetrack . 1 19 450 + . stddev=4.77582440689 +chr1 genetrack . 31 51 583 + . stddev=5.04887975977 +chr1 genetrack . 34 54 88 - . stddev=2.896077962 +chr1 genetrack . 55 75 689 - . stddev=4.30660216862 +chr1 genetrack . 65 85 688 + . stddev=5.42600427981 +chr1 genetrack . 85 105 676 - . stddev=4.49818285888 +chr1 genetrack . 111 131 5134 + . stddev=6.21477198515 +chr1 genetrack . 135 155 4059 - . stddev=4.75030601387 +chr1 genetrack . 142 162 818 + . stddev=4.61530674023 +chr1 genetrack . 162 182 509 + . stddev=5.54002911575 +chr1 genetrack . 173 193 1844 - . stddev=4.57155440482 +chr1 genetrack . 197 217 513 + . stddev=6.03335915224 +chr1 genetrack . 201 221 889 - . stddev=4.25878183562 +chr1 genetrack . 218 238 1213 - . stddev=4.50854580513 +chr1 genetrack . 237 257 585 + . stddev=4.99399478661 +chr1 genetrack . 245 265 1605 - . stddev=5.11855734302 +chr1 genetrack . 263 283 1914 - . stddev=5.30293908946 +chr1 genetrack . 281 301 144 + . stddev=5.80110142799 +chr1 genetrack . 292 312 919 - . stddev=4.83235586146 +chr1 genetrack . 317 337 227 + . stddev=5.39529430562 +chr1 genetrack . 341 361 399 - . stddev=4.78763133608 +chr1 genetrack . 363 383 494 + . stddev=5.06265712248 +chr1 genetrack . 369 389 643 - . stddev=5.18741859391 +chr1 genetrack . 394 414 548 - . stddev=5.35724250762 +chr1 genetrack . 395 415 286 + . stddev=6.40676329916 +chr1 genetrack . 423 443 462 - . stddev=4.14819371578 +chr1 genetrack . 424 444 225 + . stddev=5.43077649451 +chr1 genetrack . 442 462 325 + . stddev=4.88036859603 +chr1 genetrack . 452 472 446 - . stddev=5.2172377816 +chr1 genetrack . 464 484 288 + . stddev=5.3671065623 +chr1 genetrack . 467 487 899 - . stddev=3.96802149366 +chr1 genetrack . 486 506 216 - . stddev=4.58116999076 +chr1 genetrack . 489 509 14 + . stddev=2.56845065662 +chr1 genetrack . 521 541 212 - . stddev=1.41926272859 +chr1 genetrack . 531 551 22 + . stddev=4.29226673437 +chr1 genetrack . 561 581 15 + . stddev=2.31516738056 +chr1 genetrack . 563 583 9 - . stddev=3.97523196 +chr1 genetrack . 579 599 18 + . stddev=4.21819983838 +chr1 genetrack . 602 622 35 - . stddev=3.0751140679 +chr1 genetrack . 603 623 38 + . stddev=0.0 +chr1 genetrack . 634 654 5 - . stddev=0.4 +chr1 genetrack . 638 658 26 + . stddev=3.92251127144 +chr1 genetrack . 650 670 63 - . stddev=1.3232803175 +chr1 genetrack . 669 689 4 + . stddev=1.73205080757 +chr1 genetrack . 689 709 29 - . stddev=2.02716392506 +chr1 genetrack . 761 781 10 + . stddev=1.6 +chr1 genetrack . 813 833 6 + . stddev=0.0 +chr1 genetrack . 856 876 3 - . stddev=0.0 +chr1 genetrack . 881 901 9 + . stddev=0.0 +chr1 genetrack . 908 928 10 + . stddev=3.4292856399 +chr1 genetrack . 923 943 13 + . stddev=2.30769230769 +chr1 genetrack . 928 948 6 - . stddev=4.71404520791 +chr1 genetrack . 948 968 14 + . stddev=0.0 +chr1 genetrack . 956 976 2 - . stddev=0.0 +chr1 genetrack . 986 1006 2 + . stddev=3.0 +chr1 genetrack . 986 1006 5 - . stddev=0.0 +chr1 genetrack . 1009 1029 11 + . stddev=0.0 +chr1 genetrack . 1050 1070 2 - . stddev=0.0 +chr1 genetrack . 1051 1071 6 + . stddev=0.0 +chr1 genetrack . 1065 1085 5 - . stddev=0.0 +chr1 genetrack . 1092 1112 7 - . stddev=0.0 +chr1 genetrack . 1115 1135 9 - . stddev=0.99380799 +chr1 genetrack . 1118 1138 3 + . stddev=0.0 +chr1 genetrack . 1128 1148 10 - . stddev=0.0 +chr1 genetrack . 1149 1169 5 + . stddev=0.0 +chr1 genetrack . 1224 1244 4 - . stddev=0.0 +chr1 genetrack . 1231 1251 2 + . stddev=0.0 +chr1 genetrack . 1256 1276 7 + . stddev=0.0 +chr1 genetrack . 1297 1317 8 + . stddev=0.0 +chr1 genetrack . 1298 1318 4 - . stddev=0.866025403784 +chr1 genetrack . 1323 1343 55 - . stddev=1.36980423286 +chr1 genetrack . 1382 1402 5 - . stddev=0.0 +chr1 genetrack . 1442 1462 4 - . stddev=0.433012701892 +chr1 genetrack . 1460 1480 2 + . stddev=0.0 +chr1 genetrack . 1522 1542 6 - . stddev=0.0 +chr1 genetrack . 1547 1567 8 - . stddev=3.30718913883 +chr1 genetrack . 1557 1577 7 + . stddev=0.451753951453 +chr1 genetrack . 1604 1624 11 - . stddev=0.0 +chr1 genetrack . 1690 1710 2 + . stddev=0.0 +chr1 genetrack . 1714 1734 3 - . stddev=0.0 +chr1 genetrack . 1747 1767 2 - . stddev=0.0 +chr1 genetrack . 1765 1785 5 - . stddev=0.0 +chr1 genetrack . 1834 1854 5 - . stddev=0.0 +chr1 genetrack . 1859 1879 8 - . stddev=0.0 +chr1 genetrack . 1870 1890 2 + . stddev=0.0 +chr1 genetrack . 1915 1935 5 - . stddev=0.4 +chr1 genetrack . 1935 1955 4 - . stddev=0.0 +chr1 genetrack . 2005 2025 6 + . stddev=0.0 +chr1 genetrack . 2056 2076 5 - . stddev=0.0 +chr1 genetrack . 2079 2099 5 + . stddev=4.0 +chr1 genetrack . 2088 2108 2 - . stddev=0.0 +chr1 genetrack . 2120 2140 31 - . stddev=0.706738783878 +chr1 genetrack . 2131 2151 16 + . stddev=0.7806247498 +chr1 genetrack . 2191 2211 4 + . stddev=0.0 +chr1 genetrack . 2227 2247 6 + . stddev=0.0 +chr1 genetrack . 2235 2255 5 - . stddev=1.46969384567 +chr1 genetrack . 2260 2280 6 + . stddev=0.0 +chr1 genetrack . 2278 2298 2 - . stddev=0.0 +chr1 genetrack . 2421 2441 23 - . stddev=3.58583645226 +chr1 genetrack . 2446 2466 6 - . stddev=0.0 diff -r 000000000000 -r 25cd59a002d9 test-data/genetrack_output2.gff --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/genetrack_output2.gff Tue Dec 22 17:03:27 2015 -0500 @@ -0,0 +1,92 @@ +chr1 genetrack . 30 50 2060 + . stddev=0.0 +chr1 genetrack . 63 83 397 + . stddev=0.0 +chr1 genetrack . 79 99 521 + . stddev=0.0 +chr1 genetrack . 113 133 5129 + . stddev=0.0 +chr1 genetrack . 182 202 2538 + . stddev=0.0 +chr1 genetrack . 228 248 2496 + . stddev=0.0 +chr1 genetrack . 244 264 1525 + . stddev=0.0 +chr1 genetrack . 271 291 15 + . stddev=0.0 +chr1 genetrack . 298 318 1544 + . stddev=0.0 +chr1 genetrack . 324 344 533 + . stddev=0.0 +chr1 genetrack . 335 355 286 + . stddev=0.0 +chr1 genetrack . 364 384 608 + . stddev=0.0 +chr1 genetrack . 431 451 1393 + . stddev=0.0 +chr1 genetrack . 473 493 58 + . stddev=0.0 +chr1 genetrack . 747 767 23 + . stddev=0.0 +chr1 genetrack . 789 809 607 + . stddev=0.0 +chr1 genetrack . 834 854 665 + . stddev=0.0 +chr1 genetrack . 867 887 468 + . stddev=0.0 +chr1 genetrack . 1082 1102 740 + . stddev=0.0 +chr1 genetrack . 1173 1193 25 + . stddev=0.0 +chr1 genetrack . 1474 1494 584 + . stddev=0.0 +chr1 genetrack . 2065 2085 1181 + . stddev=0.0 +chr1 genetrack . 2092 2112 481 + . stddev=0.0 +chr1 genetrack . 2442 2462 1246 + . stddev=0.0 +chr1 genetrack . 2592 2612 34 + . stddev=0.0 +chr1 genetrack . 2823 2843 1062 + . stddev=0.0 +chr1 genetrack . 3120 3140 17 + . stddev=0.0 +chr1 genetrack . 3659 3679 845 + . stddev=0.0 +chr1 genetrack . 3858 3878 491 + . stddev=0.0 +chr1 genetrack . 4316 4336 482 + . stddev=0.0 +chr1 genetrack . 4451 4471 1110 + . stddev=0.0 +chr1 genetrack . 4610 4630 147 + . stddev=0.0 +chr1 genetrack . 4816 4836 1761 + . stddev=0.0 +chr1 genetrack . 4892 4912 710 + . stddev=0.0 +chr1 genetrack . 5100 5120 828 + . stddev=0.0 +chr1 genetrack . 5491 5511 75 + . stddev=0.0 +chr1 genetrack . 6076 6096 646 + . stddev=0.0 +chr1 genetrack . 6280 6300 5 + . stddev=0.0 +chr1 genetrack . 6346 6366 285 + . stddev=0.0 +chr1 genetrack . 6391 6411 1587 + . stddev=0.0 +chr1 genetrack . 6422 6442 742 + . stddev=0.0 +chr1 genetrack . 6486 6506 691 + . stddev=0.0 +chr1 genetrack . 6833 6853 28 + . stddev=0.0 +chr1 genetrack . 7114 7134 654 + . stddev=0.0 +chr1 genetrack . 7755 7775 714 + . stddev=0.0 +chr1 genetrack . 8199 8219 17 + . stddev=0.0 +chr1 genetrack . 8449 8469 10 + . stddev=0.0 +chr1 genetrack . 8705 8725 5 + . stddev=0.0 +chr1 genetrack . 8824 8844 332 + . stddev=0.0 +chr1 genetrack . 9024 9044 24 + . stddev=0.0 +chr1 genetrack . 9048 9068 4 + . stddev=0.0 +chr1 genetrack . 9475 9495 36 + . stddev=0.0 +chr1 genetrack . 9700 9720 480 + . stddev=0.0 +chr1 genetrack . 21 41 245 - . stddev=0.0 +chr1 genetrack . 52 72 1300 - . stddev=0.0 +chr1 genetrack . 115 135 4659 - . stddev=0.0 +chr1 genetrack . 145 165 897 - . stddev=0.0 +chr1 genetrack . 161 181 956 - . stddev=0.0 +chr1 genetrack . 174 194 494 - . stddev=0.0 +chr1 genetrack . 196 216 2087 - . stddev=0.0 +chr1 genetrack . 232 252 5047 - . stddev=0.0 +chr1 genetrack . 292 312 626 - . stddev=0.0 +chr1 genetrack . 334 354 726 - . stddev=0.0 +chr1 genetrack . 348 368 792 - . stddev=0.0 +chr1 genetrack . 379 399 126 - . stddev=0.0 +chr1 genetrack . 429 449 618 - . stddev=0.0 +chr1 genetrack . 451 471 754 - . stddev=0.0 +chr1 genetrack . 528 548 1015 - . stddev=0.0 +chr1 genetrack . 718 738 39 - . stddev=0.0 +chr1 genetrack . 893 913 107 - . stddev=0.0 +chr1 genetrack . 1117 1137 940 - . stddev=0.0 +chr1 genetrack . 1281 1301 454 - . stddev=0.0 +chr1 genetrack . 1319 1339 207 - . stddev=0.0 +chr1 genetrack . 2115 2135 199 - . stddev=0.0 +chr1 genetrack . 2828 2848 1144 - . stddev=0.0 +chr1 genetrack . 3001 3021 1212 - . stddev=0.0 +chr1 genetrack . 3106 3126 555 - . stddev=0.0 +chr1 genetrack . 3368 3388 525 - . stddev=0.0 +chr1 genetrack . 3775 3795 23 - . stddev=0.0 +chr1 genetrack . 3837 3857 316 - . stddev=0.0 +chr1 genetrack . 4087 4107 536 - . stddev=0.0 +chr1 genetrack . 4490 4510 125 - . stddev=0.0 +chr1 genetrack . 5392 5412 282 - . stddev=0.0 +chr1 genetrack . 5707 5727 737 - . stddev=0.0 +chr1 genetrack . 6088 6108 230 - . stddev=0.0 +chr1 genetrack . 6177 6197 329 - . stddev=0.0 +chr1 genetrack . 6370 6390 34 - . stddev=0.0 +chr1 genetrack . 6405 6425 953 - . stddev=0.0 +chr1 genetrack . 6496 6516 61 - . stddev=0.0 +chr1 genetrack . 7048 7068 518 - . stddev=0.0 +chr1 genetrack . 8461 8481 5 - . stddev=0.0 +chr1 genetrack . 8829 8849 593 - . stddev=0.0 diff -r 000000000000 -r 25cd59a002d9 test-data/genetrack_output3.gff --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/genetrack_output3.gff Tue Dec 22 17:03:27 2015 -0500 @@ -0,0 +1,10 @@ +chr1 genetrack . 1 20 10 + . stddev=3.25729949498 +chr1 genetrack . 28 48 92 + . stddev=2.09743181697 +chr1 genetrack . 73 93 33 + . stddev=6.09264259969 +chr1 genetrack . 85 105 30 + . stddev=3.96106046407 +chr1 genetrack . 109 129 839 + . stddev=3.6259952943 +chr1 genetrack . 121 141 675 + . stddev=5.59352633853 +chr1 genetrack . 31 51 10 - . stddev=1.84390889146 +chr1 genetrack . 56 76 32 - . stddev=3.28764258246 +chr1 genetrack . 110 130 159 - . stddev=5.21810978727 +chr1 genetrack . 136 156 893 - . stddev=2.27140632107 diff -r 000000000000 -r 25cd59a002d9 test-data/genetrack_output4.gff --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/genetrack_output4.gff Tue Dec 22 17:03:27 2015 -0500 @@ -0,0 +1,84 @@ +chr1 genetrack . 21 41 583 + . stddev=0.0 +chr1 genetrack . 55 75 688 + . stddev=0.0 +chr1 genetrack . 101 121 5134 + . stddev=0.0 +chr1 genetrack . 132 152 818 + . stddev=0.0 +chr1 genetrack . 152 172 509 + . stddev=0.0 +chr1 genetrack . 187 207 513 + . stddev=0.0 +chr1 genetrack . 227 247 585 + . stddev=0.0 +chr1 genetrack . 271 291 144 + . stddev=0.0 +chr1 genetrack . 307 327 227 + . stddev=0.0 +chr1 genetrack . 353 373 494 + . stddev=0.0 +chr1 genetrack . 385 405 286 + . stddev=0.0 +chr1 genetrack . 414 434 225 + . stddev=0.0 +chr1 genetrack . 432 452 325 + . stddev=0.0 +chr1 genetrack . 454 474 288 + . stddev=0.0 +chr1 genetrack . 479 499 14 + . stddev=0.0 +chr1 genetrack . 521 541 22 + . stddev=0.0 +chr1 genetrack . 551 571 15 + . stddev=0.0 +chr1 genetrack . 569 589 18 + . stddev=0.0 +chr1 genetrack . 593 613 38 + . stddev=0.0 +chr1 genetrack . 628 648 26 + . stddev=0.0 +chr1 genetrack . 659 679 4 + . stddev=0.0 +chr1 genetrack . 751 771 10 + . stddev=0.0 +chr1 genetrack . 803 823 6 + . stddev=0.0 +chr1 genetrack . 871 891 9 + . stddev=0.0 +chr1 genetrack . 898 918 10 + . stddev=0.0 +chr1 genetrack . 913 933 13 + . stddev=0.0 +chr1 genetrack . 938 958 14 + . stddev=0.0 +chr1 genetrack . 999 1019 11 + . stddev=0.0 +chr1 genetrack . 1041 1061 6 + . stddev=0.0 +chr1 genetrack . 1139 1159 5 + . stddev=0.0 +chr1 genetrack . 1246 1266 7 + . stddev=0.0 +chr1 genetrack . 1287 1307 8 + . stddev=0.0 +chr1 genetrack . 1547 1567 7 + . stddev=0.0 +chr1 genetrack . 1995 2015 6 + . stddev=0.0 +chr1 genetrack . 2069 2089 5 + . stddev=0.0 +chr1 genetrack . 2121 2141 16 + . stddev=0.0 +chr1 genetrack . 2181 2201 4 + . stddev=0.0 +chr1 genetrack . 2217 2237 6 + . stddev=0.0 +chr1 genetrack . 2250 2270 6 + . stddev=0.0 +chr1 genetrack . 24 44 88 - . stddev=0.0 +chr1 genetrack . 45 65 689 - . stddev=0.0 +chr1 genetrack . 75 95 676 - . stddev=0.0 +chr1 genetrack . 125 145 4059 - . stddev=0.0 +chr1 genetrack . 163 183 1844 - . stddev=0.0 +chr1 genetrack . 191 211 889 - . stddev=0.0 +chr1 genetrack . 208 228 1213 - . stddev=0.0 +chr1 genetrack . 235 255 1605 - . stddev=0.0 +chr1 genetrack . 253 273 1914 - . stddev=0.0 +chr1 genetrack . 282 302 919 - . stddev=0.0 +chr1 genetrack . 331 351 399 - . stddev=0.0 +chr1 genetrack . 359 379 643 - . stddev=0.0 +chr1 genetrack . 384 404 548 - . stddev=0.0 +chr1 genetrack . 413 433 462 - . stddev=0.0 +chr1 genetrack . 442 462 446 - . stddev=0.0 +chr1 genetrack . 457 477 899 - . stddev=0.0 +chr1 genetrack . 476 496 216 - . stddev=0.0 +chr1 genetrack . 511 531 212 - . stddev=0.0 +chr1 genetrack . 553 573 9 - . stddev=0.0 +chr1 genetrack . 592 612 35 - . stddev=0.0 +chr1 genetrack . 640 660 63 - . stddev=0.0 +chr1 genetrack . 679 699 29 - . stddev=0.0 +chr1 genetrack . 918 938 6 - . stddev=0.0 +chr1 genetrack . 976 996 5 - . stddev=0.0 +chr1 genetrack . 1055 1075 5 - . stddev=0.0 +chr1 genetrack . 1082 1102 7 - . stddev=0.0 +chr1 genetrack . 1106 1126 9 - . stddev=0.0 +chr1 genetrack . 1117 1137 10 - . stddev=0.0 +chr1 genetrack . 1214 1234 4 - . stddev=0.0 +chr1 genetrack . 1288 1308 4 - . stddev=0.0 +chr1 genetrack . 1313 1333 55 - . stddev=0.0 +chr1 genetrack . 1372 1392 5 - . stddev=0.0 +chr1 genetrack . 1432 1452 4 - . stddev=0.0 +chr1 genetrack . 1512 1532 6 - . stddev=0.0 +chr1 genetrack . 1537 1557 8 - . stddev=0.0 +chr1 genetrack . 1594 1614 11 - . stddev=0.0 +chr1 genetrack . 1755 1775 5 - . stddev=0.0 +chr1 genetrack . 1824 1844 5 - . stddev=0.0 +chr1 genetrack . 1849 1869 8 - . stddev=0.0 +chr1 genetrack . 1905 1925 5 - . stddev=0.0 +chr1 genetrack . 1925 1945 4 - . stddev=0.0 +chr1 genetrack . 2046 2066 5 - . stddev=0.0 +chr1 genetrack . 2110 2130 31 - . stddev=0.0 +chr1 genetrack . 2225 2245 5 - . stddev=0.0 +chr1 genetrack . 2411 2431 23 - . stddev=0.0 diff -r 000000000000 -r 25cd59a002d9 tool_dependencies.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/tool_dependencies.xml Tue Dec 22 17:03:27 2015 -0500 @@ -0,0 +1,6 @@ + + + + + +