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Commit message:
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/bigwig_outlier_bed commit 3cce4c76a60b9353298fdcf759e893b8fcdfaa77 |
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modified:
README.md bigwig_outlier_bed.py bigwig_outlier_bed.xml test-data/bedouthi2_sample test-data/bedouthi_qlo_notset_sample test-data/bedouthi_sample test-data/bedouthilo2_sample test-data/bedouthilo_sample test-data/bedoutlo2_sample test-data/table2_sample test-data/table3_sample test-data/table_qlo_notset_sample test-data/table_sample |
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test-data/table_only_sample |
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| diff -r 8377a6abb4da -r 61946b8bd43b README.md --- a/README.md Sun Jul 21 11:03:36 2024 +0000 +++ b/README.md Thu Jul 25 14:38:34 2024 +0000 |
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| @@ -2,9 +2,9 @@ ### July 30 2024 for the VGP -This code will soon become a Galaxy tool, for building some of the [NIH MARBL T2T assembly polishing](https://github.com/marbl/training) tools as Galaxy workflows. +This is a Galaxy tool, for building some of the [NIH MARBL T2T assembly polishing](https://github.com/marbl/training) tools as Galaxy workflows. -JBrowse2 2.12.3 update will include a plugin for optional colours to distinguish bed features, shown being tested in the screenshots below. +JBrowse2 now includes a plugin for optional colours to distinguish bed features, shown being tested in the screenshots below. ### Find and mark BigWig peaks to a bed file for display @@ -29,3 +29,69 @@ better to sample across all chromosomes so as not to lose any systematic differences between them - the current method will hide those differences unfortunately. Sampling might be possible. Looking at the actual quantile values across a couple of test bigwigs suggests that there is not much variation between chromosomes but there's now a tabular report to check them for each input bigwig. + +### Table reports + +The optional table output report gives a crude histogram and the top/bottom 10 values to help +understand what is likely to be informative. In this example, there are 26700 zero values so +using a lower cutoff quantile is likely to have a lot of them, although a large window requirement +will decease the overload... + +Descriptive measures +bigwig test +contig chr10_PATERNAL +n 135711693 +mean 12.178164 +std 7.997467 +min 0.000000 +max 365.000000 +qtop 364.00 +qbot noqlo +First/Last 10 value counts +Value Count +0.00 26700 +1.00 82900 +2.00 261400 +3.00 676993 +4.00 1665500 +5.00 3125700 +6.00 5078000 +7.00 7469000 +8.00 10191700 +9.00 12544600 +355.00 100 +356.00 100 +357.00 300 +358.00 100 +360.00 500 +361.00 300 +362.00 200 +363.00 600 +364.00 900 +365.00 700 +Histogram of bigwig values +chr10_PATERNAL 18.25 | 127,047,593 | ************************************************************************** +chr10_PATERNAL 36.50 | 7,510,000 | **** +chr10_PATERNAL 54.75 | 818,900 | +chr10_PATERNAL 73.00 | 117,200 | +chr10_PATERNAL 91.25 | 51,900 | +chr10_PATERNAL 109.50 | 44,200 | +chr10_PATERNAL 127.75 | 21,600 | +chr10_PATERNAL 146.00 | 17,900 | +chr10_PATERNAL 164.25 | 16,400 | +chr10_PATERNAL 182.50 | 18,600 | +chr10_PATERNAL 200.75 | 5,400 | +chr10_PATERNAL 219.00 | 6,600 | +chr10_PATERNAL 237.25 | 6,200 | +chr10_PATERNAL 255.50 | 3,900 | +chr10_PATERNAL 273.75 | 4,500 | +chr10_PATERNAL 292.00 | 7,100 | +chr10_PATERNAL 310.25 | 3,000 | +chr10_PATERNAL 328.50 | 2,700 | +chr10_PATERNAL 346.75 | 3,500 | +chr10_PATERNAL 365.00 | 4,500 | +chr10_PATERNAL ------------ |------------ | +chr10_PATERNAL N= | 135,711,693 | +chr10_PATERNAL ------------ |------------ | + + |
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| diff -r 8377a6abb4da -r 61946b8bd43b bigwig_outlier_bed.py --- a/bigwig_outlier_bed.py Sun Jul 21 11:03:36 2024 +0000 +++ b/bigwig_outlier_bed.py Thu Jul 25 14:38:34 2024 +0000 |
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| b'@@ -13,7 +13,6 @@\n """\n \n import argparse\n-import copy\n import os\n import sys\n from pathlib import Path\n@@ -22,6 +21,90 @@\n import pybigtools\n \n \n+class asciihist:\n+\n+ def __init__(\n+ self,\n+ data,\n+ bins=10,\n+ minmax=None,\n+ str_tag="",\n+ scale_output=80,\n+ generate_only=True,\n+ ):\n+ """\n+ https://gist.github.com/bgbg/608d9ef4fd75032731651257fe67fc81\n+ Create an ASCII histogram from an interable of numbers.\n+ Author: Boris Gorelik boris@gorelik.net. based on http://econpy.googlecode.com/svn/trunk/pytrix/pytrix.py\n+ License: MIT\n+ """\n+ self.data = data\n+ self.minmax = minmax\n+ self.str_tag = str_tag\n+ self.bins = bins\n+ self.generate_only = generate_only\n+ self.scale_output = scale_output\n+ self.itarray = np.asanyarray(self.data)\n+ if self.minmax == "auto":\n+ self.minmax = np.percentile(data, [5, 95])\n+ if self.minmax[0] == self.minmax[1]:\n+ # for very ugly distributions\n+ self.minmax = None\n+ if self.minmax is not None:\n+ # discard values that are outside minmax range\n+ mn = self.minmax[0]\n+ mx = self.minmax[1]\n+ self.itarray = self.itarray[self.itarray >= mn]\n+ self.itarray = self.itarray[self.itarray <= mx]\n+\n+ def draw(self):\n+ values, counts = np.unique(self.data, return_counts=True)\n+ if len(values) <= 20:\n+ self.bins = len(values)\n+ ret = []\n+ if self.itarray.size:\n+ total = len(self.itarray)\n+ counts, cutoffs = np.histogram(self.itarray, bins=self.bins)\n+ cutoffs = cutoffs[1:]\n+ if self.str_tag:\n+ self.str_tag = "%s " % self.str_tag\n+ else:\n+ self.str_tag = ""\n+ if self.scale_output is not None:\n+ scaled_counts = counts.astype(float) / counts.sum() * self.scale_output\n+ else:\n+ scaled_counts = counts\n+ footerbar = "{:s}{:s} |{:s} |".format(\n+ self.str_tag,\n+ "-" * 12,\n+ "-" * 12,\n+ )\n+ if self.minmax is not None:\n+ ret.append(\n+ "Trimmed to range (%s - %s)"\n+ % (str(self.minmax[0]), str(self.minmax[1]))\n+ )\n+ for cutoff, original_count, scaled_count in zip(\n+ cutoffs, counts, scaled_counts\n+ ):\n+ ret.append(\n+ "{:s}{:>12.2f} |{:>12,d} | {:s}".format(\n+ self.str_tag, cutoff, original_count, "*" * int(scaled_count)\n+ )\n+ )\n+ ret.append(footerbar)\n+ ret.append("{:s}{:>12s} |{:>12,d} |".format(self.str_tag, "N=", total))\n+ ret.append(footerbar)\n+ ret.append("")\n+ else:\n+ ret = []\n+ if not self.generate_only:\n+ for line in ret:\n+ print(line)\n+ ret = "\\n".join(ret)\n+ return ret\n+\n+\n class findOut:\n \n def __init__(self, args):\n@@ -34,14 +117,16 @@\n self.bedouthilo = args.bedouthilo\n self.tableoutfile = args.tableoutfile\n self.bedwin = args.minwin\n- self.qhi = args.qhi\n self.qlo = None\n- try:\n- f = float(args.qlo)\n- self.qlo = f\n- except Exception as e:\n- s = str(e)\n- print(s, \' qlo=\', args.qlo)\n+ self.qhi = None\n+ if args.outbeds != "outtab":\n+ self.qhi = args.qhi\n+ if args.qlo:\n+ try:\n+ f = float(args.qlo)\n+ self.qlo = f\n+ except Exception:\n+ print("qlo not provided")\n nbw = len(args.bigwig)\n nlab = len(args.bigwiglabels)\n if nlab < nbw:\n@@ -106,10 +191,11 @@\n d'..b' restab = ["bigwig\\tcontig\\tn\\tmean\\tstd\\tmin\\tmax\\tqtop\\tqbot"]\n+ bwnames.sort()\n+ reshead = "bigwig\\tcontig\\tn\\tmean\\tstd\\tmin\\tmax\\tqtop\\tqbot"\n for i, bwname in enumerate(bwnames):\n bwlabel = bwlabels[i].replace(" ", "")\n fakepath = "in%d.bw" % i\n@@ -120,16 +206,38 @@\n bwf = pybigtools.open(fakepath)\n chrlist = bwf.chroms()\n chrs = list(chrlist.keys())\n- chrs.sort()\n for chr in chrs:\n+ first_few = None\n bw = bwf.values(chr)\n+ values, counts = np.unique(bw, return_counts=True)\n+ nvalues = len(values)\n+ if nvalues <= 20:\n+ histo = "\\n".join(\n+ [\n+ "%s: %f occurs %d times" % (chr, values[x], counts[x])\n+ for x in range(len(values))\n+ ]\n+ )\n+ else:\n+ last10 = range(nvalues - 10, nvalues)\n+ first_few = ["%.2f\\t%d" % (values[x], counts[x]) for x in range(10)]\n+ first_few += ["%.2f\\t%d" % (values[x], counts[x]) for x in last10]\n+ first_few.insert(0, "First/Last 10 value counts\\nValue\\tCount")\n+ ha = asciihist(data=bw, bins=20, str_tag="%s_%s" % (bwlabel, chr))\n+ histo = ha.draw()\n+ histo = (\n+ "\\n".join(first_few)\n+ + "\\nHistogram of %s bigwig values\\n" % bwlabel\n+ + histo\n+ )\n bw = bw[~np.isnan(bw)] # some have NaN if parts of a contig not covered\n if self.qhi is not None:\n self.bwtop = np.quantile(bw, self.qhi)\n bwhi = self.processVals(bw, isTop=True)\n for j, seg in enumerate(bwhi):\n- if seg[1] - seg[0] >= self.bedwin:\n- score = np.sum(bw[seg[0]:seg[1]])\n+ seglen = seg[1] - seg[0]\n+ if seglen >= self.bedwin:\n+ score = np.sum(bw[seg[0]:seg[1]]) / float(seglen)\n bedhi.append(\n (\n chr,\n@@ -144,7 +252,7 @@\n bwlo = self.processVals(bw, isTop=False)\n for j, seg in enumerate(bwlo):\n if seg[1] - seg[0] >= self.bedwin:\n- score = -1 * np.sum(bw[seg[0]:seg[1]])\n+ score = -1 * np.sum(bw[seg[0]:seg[1]]) / float(seglen)\n bedlo.append(\n (\n chr,\n@@ -156,7 +264,15 @@\n )\n if self.tableoutfile:\n row = self.makeTableRow(bw, bwlabel, chr)\n- restab.append(copy.copy(row))\n+ resheadl = reshead.split("\\t")\n+ rowl = row.split()\n+ desc = ["%s\\t%s" % (resheadl[x], rowl[x]) for x in range(len(rowl))]\n+ desc.insert(0, "Descriptive measures")\n+ descn = "\\n".join(desc)\n+ restab.append(descn)\n+ restab.append(histo)\n+ if os.path.isfile(fakepath):\n+ os.remove(fakepath)\n if self.tableoutfile:\n stable = "\\n".join(restab)\n with open(self.tableoutfile, "w") as t:\n@@ -175,7 +291,7 @@\n allbed = bedlo + bedhi\n self.writeBed(allbed, self.bedouthilo)\n some = True\n- if not some:\n+ if not ((self.outbeds == "outtab") or some):\n sys.stderr.write(\n "Invalid configuration - no output could be created. Was qlo missing and only low output requested for example?"\n )\n' |
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| diff -r 8377a6abb4da -r 61946b8bd43b bigwig_outlier_bed.xml --- a/bigwig_outlier_bed.xml Sun Jul 21 11:03:36 2024 +0000 +++ b/bigwig_outlier_bed.xml Thu Jul 25 14:38:34 2024 +0000 |
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| @@ -1,9 +1,9 @@ -<tool name="Bigwig extremes to bed features" id="bigwig_outlier_bed" version="@TOOL_VERSION@" profile="22.05"> +<tool name="Bigwig extremes to bed features" id="bigwig_outlier_bed" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="22.05"> <description>Writes high and low bigwig runs as features in a bed file</description> <macros> <token name="@TOOL_VERSION@">0.2.0</token> - <token name="@NUMPY_VERSION@">2.0.0</token> <token name="@PYTHON_VERSION@">3.12.3</token> + <token name="@VERSION_SUFFIX@">0</token> </macros> <edam_topics> <edam_topic>topic_0157</edam_topic> @@ -17,7 +17,7 @@ </xrefs> <requirements> <requirement type="package" version="@PYTHON_VERSION@">python</requirement> - <requirement type="package" version="@NUMPY_VERSION@">numpy</requirement> + <requirement type="package" version="2.0.0">numpy</requirement> <requirement type="package" version="@TOOL_VERSION@">pybigtools</requirement> </requirements> <required_files> @@ -50,7 +50,7 @@ #if $qlo: --qlo '$qlo' #end if -#if $tableout == "create": +#if $tableout == "create" or $outbeds == "outtab": --tableoutfile '$tableoutfile' #end if ]]></command> @@ -58,15 +58,18 @@ <param name="bigwig" type="data" optional="false" label="Choose one or more bigwig file(s) to return outlier regions as a bed file" help="If more than one, MUST all use the same reference sequence to be displayable. Feature names will include the bigwig label." format="bigwig" multiple="true"/> <param name="minwin" type="integer" value="10" label="Minimum continuous bases to count as a high or low bed feature" - help="Continuous features as long or longer than this window size will appear as bed features"/> - <param name="qhi" type="float" value="0.99" label="Quantile cutoff for a high region - 0.99 will cut off at or above the 99th percentile" help="Required" optional="false"/> - <param name="qlo" type="float" value="0.01" label="Quantile cutoff for a low region - 0.01 will cut off at or below the 1st percentile." help="Optional" optional="true"/> - <param name="outbeds" type="select" label="Select the required bed file outputs" help="Any combination of the 3 different kinds of bed file output can be made"> + help="Minimum continuous length to count as a bed feature. If windowed bigwig, must be bigger than window size to have any effect"/> + <param name="qhi" type="float" value="0.99999" label="Quantile cutoff for a high region - 0.99999 will cut off at about 1 in 100,000" + help="1 per 100k might be a few thousand features in a 200M chromosome - depends on the distribution - see the table output" optional="false"/> + <param name="qlo" type="float" value="0.00001" label="Quantile cutoff for a low region - 0.01 will cut off at or below the 1st percentile." help="Optional" optional="true"/> + <param name="outbeds" type="select" label="Select the required bed file outputs or none for a bigwig value distribution report" + help="Any combination of the 3 different kinds of bed file output can be made"> <option value="outhilo" selected="true">Make 1 bed output with both low and high regions</option> <option value="outhi">Make 1 bed output with high regions only</option> <option value="outlo">Make 1 bed output with low regions only</option> <option value="outall">Make 3 bed outputs with low and high together in one, high in one and low in the other</option> <option value="outlohi">Make 2 bed outputs with high in one and low in the other</option> + <option value="outtab">NO bed outputs. Report bigwig value distribution only</option> </param> <param name="tableout" type="select" label="Write a table showing contig statistics for each bigwig input" help=""> <option value="donotmake">Do not create this report</option> @@ -74,17 +77,17 @@ </param> </inputs> <outputs> - <data name="bedouthilo" format="bed" label="High_and_low_bed" hidden="false"> + <data name="bedouthilo" format="bed" label="High_and_low_bed"> <filter>outbeds in ["outall", "outhilo"]</filter> </data> - <data name="bedouthi" format="bed" label="High bed" hidden="false"> + <data name="bedouthi" format="bed" label="High bed"> <filter>outbeds in ["outall", "outlohi", "outhi"]</filter> </data> - <data name="bedoutlo" format="bed" label="Low bed" hidden="false"> + <data name="bedoutlo" format="bed" label="Low bed"> <filter>outbeds in ["outall", "outlohi", "outlo"]</filter> </data> - <data name="tableoutfile" format="tabular" label="Contig statistics" hidden="false"> - <filter>tableout == "create"</filter> + <data name="tableoutfile" format="txt" label="Contig statistics"> + <filter>tableout == "create" or outbeds == "outtab"</filter> </data> </outputs> <tests> @@ -97,6 +100,15 @@ <param name="qlo" value="0.01"/> <param name="tableout" value="donotmake"/> </test> + <test expect_num_outputs="1"> + <output name="tableoutfile" value="table_only_sample" compare="diff" lines_diff="0"/> + <param name="outbeds" value="outtab"/> + <param name="bigwig" value="bigwig_sample,1.bigwig"/> + <param name="minwin" value="10"/> + <param name="qhi" value="0.99"/> + <param name="qlo" value="0.01"/> + <param name="tableout" value="create"/> + </test> <test expect_num_outputs="2"> <output name="bedouthilo" value="bedouthilo_sample" compare="diff" lines_diff="0"/> <output name="tableoutfile" value="table_sample" compare="diff" lines_diff="0"/> |
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| diff -r 8377a6abb4da -r 61946b8bd43b test-data/bedouthi2_sample --- a/test-data/bedouthi2_sample Sun Jul 21 11:03:36 2024 +0000 +++ b/test-data/bedouthi2_sample Thu Jul 25 14:38:34 2024 +0000 |
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| b'@@ -1,1347 +1,1347 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|
| b |
| diff -r 8377a6abb4da -r 61946b8bd43b test-data/bedouthi_qlo_notset_sample --- a/test-data/bedouthi_qlo_notset_sample Sun Jul 21 11:03:36 2024 +0000 +++ b/test-data/bedouthi_qlo_notset_sample Thu Jul 25 14:38:34 2024 +0000 |
| b |
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|
| b |
| diff -r 8377a6abb4da -r 61946b8bd43b test-data/bedouthi_sample --- a/test-data/bedouthi_sample Sun Jul 21 11:03:36 2024 +0000 +++ b/test-data/bedouthi_sample Thu Jul 25 14:38:34 2024 +0000 |
| b |
| b'@@ -1,1346 +1,1346 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|
| b |
| diff -r 8377a6abb4da -r 61946b8bd43b test-data/bedouthilo2_sample --- a/test-data/bedouthilo2_sample Sun Jul 21 11:03:36 2024 +0000 +++ b/test-data/bedouthilo2_sample Thu Jul 25 14:38:34 2024 +0000 |
| b |
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|
| b |
| diff -r 8377a6abb4da -r 61946b8bd43b test-data/bedouthilo_sample --- a/test-data/bedouthilo_sample Sun Jul 21 11:03:36 2024 +0000 +++ b/test-data/bedouthilo_sample Thu Jul 25 14:38:34 2024 +0000 |
| b |
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Merlin\t70049\t180929\tbigwig_sample_0\t0\n' |
| b |
| diff -r 8377a6abb4da -r 61946b8bd43b test-data/bedoutlo2_sample --- a/test-data/bedoutlo2_sample Sun Jul 21 11:03:36 2024 +0000 +++ b/test-data/bedoutlo2_sample Thu Jul 25 14:38:34 2024 +0000 |
| b |
| b'@@ -1,110 +1,110 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12415\tbigwig_sample_0\t0\n+chr21\t9412440\t9412455\tbigwig_sample_0\t0\n+chr21\t9412460\t9412465\tbigwig_sample_0\t0\n+chr21\t9412470\t9412480\tbigwig_sample_0\t0\n+chr21\t9412485\t9412490\tbigwig_sample_0\t0\n+chr21\t9412510\t9412515\tbigwig_sample_0\t0\n+chr21\t9412565\t9412570\tbigwig_sample_0\t0\n+chr21\t9412590\t9412595\tbigwig_sample_0\t0\n+chr21\t9412640\t9412650\tbigwig_sample_0\t0\n+chr21\t9412670\t9412675\tbigwig_sample_0\t0\n+chr21\t9412690\t9412700\tbigwig_sample_0\t0\n+chr21\t9412770\t9412775\tbigwig_sample_0\t0\n+chr21\t9412815\t9412820\tbigwig_sample_0\t0\n+chr21\t9412835\t9412840\tbigwig_sample_0\t0\n+chr21\t9412845\t9412850\tbigwig_sample_0\t0\n+chr21\t9412900\t9412905\tbigwig_sample_0\t0\n+chr21\t9412970\t9412975\tbigwig_sample_0\t0\n+chr21\t9412990\t9412995\tbigwig_sample_0\t0\n+chr21\t9413040\t9413045\tbigwig_sample_0\t0\n+chr21\t9413055\t9413065\tbigwig_sample_0\t0\n+chr21\t9413095\t9413100\tbigwig_sample_0\t0\n+chr21\t9413130\t9413135\tbigwig_sample_0\t0\n+chr21\t9413155\t9413160\tbigwig_sample_0\t0\n+chr21\t9413170\t9413180\tbigwig_sample_0\t0\n+chr21\t9413205\t9413210\tbigwig_sample_0\t0\n+chr21\t9413250\t9413255\tbigwig_sample_0\t0\n+chr21\t9413280\t9413285\tbigwig_sample_0\t0\n+chr21\t9413310\t9413315\tbigwig_sample_0\t0\n+chr21\t9413345\t9413350\tbigwig_sample_0\t0\n+chr21\t9413400\t9413405\tbigwig_sample_0\t0\n+chr21\t9413510\t9413515\tbigwig_sample_0\t0\n+chr21\t9413665\t9413670\tbigwig_sample_0\t0\n+chr21\t9414040\t9414045\tbigwig_sample_0\t0\n+chr21\t9414055\t9414060\tbigwig_sample_0\t0\n+chr21\t9414100\t9414105\tbigwig_sample_0\t0\n+chr21\t9414150\t9414160\tbigwig_sample_0\t0\n+chr21\t9414175\t9414180\tbigwig_sample_0\t0\n+chr21\t9414215\t9414225\tbigwig_sample_0\t0\n+chr21\t9414255\t9414260\tbigwig_sample_0\t0\n+chr21\t9414265\t9414270\tbigwig_sample_0\t0\n+chr21\t9414280\t9414285\tbigwig_sample_0\t0\n+chr21\t9414305\t9414310\tbigwig_sample_0\t0\n+chr21\t9414435\t9414440\tbigwig_sample_0\t0\n+chr21\t9414525\t9414530\tbigwig_sample_0\t0\n+chr21\t9414585\t9414590\tbigwig_sample_0\t0\n+chr21\t9414595\t9414600\tbigwig_sample_0\t0\n+chr21\t9414655\t9414665\tbigwig_sample_0\t0\n+chr21\t9414680\t9414690\tbigwig_sample_0\t0\n+chr21\t9414695\t9414700\tbigwig_sample_0\t0\n+chr21\t9414705\t9414710\tbigwig_sample_0\t0\n+chr21\t9414720\t9414725\tbigwig_sample_0\t0\n+chr21\t9414755\t9414760\tbigwig_sample_0\t0\n+chr21\t9414775\t9414780\tbigwig_sample_0\t0\n+chr21\t9414785\t9414790\tbigwig_sample_0\t0\n+chr21\t9414820\t9414825\tbigwig_sample_0\t0\n+chr21\t9414835\t9414840\tbigwig_sample_0\t0\n+chr21\t9414850\t9414855\tbigwig_sample_0\t0\n+chr21\t9414860\t9414870\tbigwig_sample_0\t0\n+chr21\t9414905\t9414910\tbigwig_sample_0\t0\n+chr21\t9414925\t9414930\tbigwig_sample_0\t0\n+chr21\t9414955\t9414960\tbigwig_sample_0\t0\n+chr21\t9414975\t9414980\tbigwig_sample_0\t0\n+chr21\t9414995\t9415000\tbigwig_sample_0\t0\n+chr21\t9415040\t9415055\tbigwig_sample_0\t0\n+chr21\t9415065\t9415075\tbigwig_sample_0\t0\n+chr21\t9415095\t9415100\tbigwig_sample_0\t0\n+chr21\t9415105\t9415115\tbigwig_sample_0\t0\n+chr21\t9415135\t9415140\tbigwig_sample_0\t0\n+chr21\t9415150\t9415155\tbigwig_sample_0\t0\n+chr21\t9415170\t9415175\tbigwig_sample_0\t0\n+chr21\t9415270\t9415275\tbigwig_sample_0\t0\n+chr21\t9415320\t9415325\tbigwig_sample_0\t0\n+chr21\t9415385\t9415390\tbigwig_sample_0\t0\n+chr21\t9415470\t9415475\tbigwig_sample_0\t0\n+chr21\t9415535\t9415540\tbigwig_sample_0\t0\n+chr21\t9415595\t9415600\tbigwig_sample_0\t0\n+chr21\t9415665\t9415670\tbigwig_sample_0\t0\n+chr21\t9415685\t9415700\tbigwig_sample_0\t0\n+chr21\t9415710\t9415715\tbigwig_sample_0\t0\n+chr21\t9415820\t9415830\tbigwig_sample_0\t0\n+chr21\t9415880\t9415885\tbigwig_sample_0\t0\n+chr21\t9416020\t9416025\tbigwig_sample_0\t0\n+chr21\t9416080\t9416085\tbigwig_sample_0\t0\n+chr21\t9416095\t9416100\tbigwig_sample_0\t0\n+chr21\t9416130\t9416135\tbigwig_sample_0\t0\n+chr21\t9416150\t9416155\tbigwig_sample_0\t0\n+chr21\t9416165\t9416175\tbigwig_sample_0\t0\n+chr21\t9416185\t48129895\tbigwig_sample_0\t0\n' |
| b |
| diff -r 8377a6abb4da -r 61946b8bd43b test-data/table2_sample --- a/test-data/table2_sample Sun Jul 21 11:03:36 2024 +0000 +++ b/test-data/table2_sample Thu Jul 25 14:38:34 2024 +0000 |
| b |
| @@ -1,3 +1,74 @@ -bigwig contig n mean std min max qtop qbot -bigwig_sample Merlin 180929 6354.313736 9951.749936 0.000000 32767.000000 24359.00 0.00 -1.bigwig chr21 48129895 0.003446 0.400601 0.000000 100.000000 0.00 0.00 +Descriptive measures +bigwig bigwig_sample +contig chr21 +n 48129895 +mean 0.003446 +std 0.400601 +min 0.000000 +max 100.000000 +qtop 0.00 +qbot 0.00 +chr21: 0.000000 occurs 48125565 times +chr21: 20.000000 occurs 1660 times +chr21: 40.000000 occurs 1610 times +chr21: 50.000000 occurs 5 times +chr21: 60.000000 occurs 840 times +chr21: 80.000000 occurs 195 times +chr21: 100.000000 occurs 20 times +Descriptive measures +bigwig 1.bigwig +contig Merlin +n 180929 +mean 6354.313736 +std 9951.749936 +min 0.000000 +max 32767.000000 +qtop 24359.00 +qbot 0.00 +First/Last 10 value counts +Value Count +0.00 110889 +13.00 30 +22.00 10 +26.00 10 +29.00 10 +40.00 10 +43.00 10 +53.00 10 +57.00 10 +60.00 20 +32721.00 10 +32724.00 10 +32726.00 10 +32728.00 10 +32730.00 10 +32731.00 20 +32737.00 10 +32745.00 10 +32766.00 10 +32767.00 10 +Histogram of 1.bigwig bigwig values +1.bigwig_Merlin 1638.35 | 114,349 | ************************************************** +1.bigwig_Merlin 3276.70 | 3,650 | * +1.bigwig_Merlin 4915.05 | 3,620 | * +1.bigwig_Merlin 6553.40 | 3,570 | * +1.bigwig_Merlin 8191.75 | 3,570 | * +1.bigwig_Merlin 9830.10 | 3,410 | * +1.bigwig_Merlin 11468.45 | 3,610 | * +1.bigwig_Merlin 13106.80 | 3,170 | * +1.bigwig_Merlin 14745.15 | 3,310 | * +1.bigwig_Merlin 16383.50 | 3,390 | * +1.bigwig_Merlin 18021.85 | 3,270 | * +1.bigwig_Merlin 19660.20 | 3,680 | * +1.bigwig_Merlin 21298.55 | 3,560 | * +1.bigwig_Merlin 22936.90 | 3,490 | * +1.bigwig_Merlin 24575.25 | 3,530 | * +1.bigwig_Merlin 26213.60 | 3,460 | * +1.bigwig_Merlin 27851.95 | 3,470 | * +1.bigwig_Merlin 29490.30 | 3,500 | * +1.bigwig_Merlin 31128.65 | 3,920 | * +1.bigwig_Merlin 32767.00 | 3,400 | * +1.bigwig_Merlin ------------ |------------ | +1.bigwig_Merlin N= | 180,929 | +1.bigwig_Merlin ------------ |------------ | + |
| b |
| diff -r 8377a6abb4da -r 61946b8bd43b test-data/table3_sample --- a/test-data/table3_sample Sun Jul 21 11:03:36 2024 +0000 +++ b/test-data/table3_sample Thu Jul 25 14:38:34 2024 +0000 |
| b |
| @@ -1,2 +1,57 @@ -bigwig contig n mean std min max qtop qbot -bigwig_sample Merlin 180929 6354.313736 9951.749936 0.000000 32767.000000 24359.00 0.00 +Descriptive measures +bigwig bigwig_sample +contig Merlin +n 180929 +mean 6354.313736 +std 9951.749936 +min 0.000000 +max 32767.000000 +qtop 24359.00 +qbot 0.00 +First/Last 10 value counts +Value Count +0.00 110889 +13.00 30 +22.00 10 +26.00 10 +29.00 10 +40.00 10 +43.00 10 +53.00 10 +57.00 10 +60.00 20 +32721.00 10 +32724.00 10 +32726.00 10 +32728.00 10 +32730.00 10 +32731.00 20 +32737.00 10 +32745.00 10 +32766.00 10 +32767.00 10 +Histogram of bigwig_sample bigwig values +bigwig_sample_Merlin 1638.35 | 114,349 | ************************************************** +bigwig_sample_Merlin 3276.70 | 3,650 | * +bigwig_sample_Merlin 4915.05 | 3,620 | * +bigwig_sample_Merlin 6553.40 | 3,570 | * +bigwig_sample_Merlin 8191.75 | 3,570 | * +bigwig_sample_Merlin 9830.10 | 3,410 | * +bigwig_sample_Merlin 11468.45 | 3,610 | * +bigwig_sample_Merlin 13106.80 | 3,170 | * +bigwig_sample_Merlin 14745.15 | 3,310 | * +bigwig_sample_Merlin 16383.50 | 3,390 | * +bigwig_sample_Merlin 18021.85 | 3,270 | * +bigwig_sample_Merlin 19660.20 | 3,680 | * +bigwig_sample_Merlin 21298.55 | 3,560 | * +bigwig_sample_Merlin 22936.90 | 3,490 | * +bigwig_sample_Merlin 24575.25 | 3,530 | * +bigwig_sample_Merlin 26213.60 | 3,460 | * +bigwig_sample_Merlin 27851.95 | 3,470 | * +bigwig_sample_Merlin 29490.30 | 3,500 | * +bigwig_sample_Merlin 31128.65 | 3,920 | * +bigwig_sample_Merlin 32767.00 | 3,400 | * +bigwig_sample_Merlin ------------ |------------ | +bigwig_sample_Merlin N= | 180,929 | +bigwig_sample_Merlin ------------ |------------ | + |
| b |
| diff -r 8377a6abb4da -r 61946b8bd43b test-data/table_only_sample --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/table_only_sample Thu Jul 25 14:38:34 2024 +0000 |
| b |
| @@ -0,0 +1,74 @@ +Descriptive measures +bigwig bigwig_sample +contig Merlin +n 180929 +mean 6354.313736 +std 9951.749936 +min 0.000000 +max 32767.000000 +qtop noqhi +qbot noqlo +First/Last 10 value counts +Value Count +0.00 110889 +13.00 30 +22.00 10 +26.00 10 +29.00 10 +40.00 10 +43.00 10 +53.00 10 +57.00 10 +60.00 20 +32721.00 10 +32724.00 10 +32726.00 10 +32728.00 10 +32730.00 10 +32731.00 20 +32737.00 10 +32745.00 10 +32766.00 10 +32767.00 10 +Histogram of bigwig_sample bigwig values +bigwig_sample_Merlin 1638.35 | 114,349 | ************************************************** +bigwig_sample_Merlin 3276.70 | 3,650 | * +bigwig_sample_Merlin 4915.05 | 3,620 | * +bigwig_sample_Merlin 6553.40 | 3,570 | * +bigwig_sample_Merlin 8191.75 | 3,570 | * +bigwig_sample_Merlin 9830.10 | 3,410 | * +bigwig_sample_Merlin 11468.45 | 3,610 | * +bigwig_sample_Merlin 13106.80 | 3,170 | * +bigwig_sample_Merlin 14745.15 | 3,310 | * +bigwig_sample_Merlin 16383.50 | 3,390 | * +bigwig_sample_Merlin 18021.85 | 3,270 | * +bigwig_sample_Merlin 19660.20 | 3,680 | * +bigwig_sample_Merlin 21298.55 | 3,560 | * +bigwig_sample_Merlin 22936.90 | 3,490 | * +bigwig_sample_Merlin 24575.25 | 3,530 | * +bigwig_sample_Merlin 26213.60 | 3,460 | * +bigwig_sample_Merlin 27851.95 | 3,470 | * +bigwig_sample_Merlin 29490.30 | 3,500 | * +bigwig_sample_Merlin 31128.65 | 3,920 | * +bigwig_sample_Merlin 32767.00 | 3,400 | * +bigwig_sample_Merlin ------------ |------------ | +bigwig_sample_Merlin N= | 180,929 | +bigwig_sample_Merlin ------------ |------------ | + +Descriptive measures +bigwig 1.bigwig +contig chr21 +n 48129895 +mean 0.003446 +std 0.400601 +min 0.000000 +max 100.000000 +qtop noqhi +qbot noqlo +chr21: 0.000000 occurs 48125565 times +chr21: 20.000000 occurs 1660 times +chr21: 40.000000 occurs 1610 times +chr21: 50.000000 occurs 5 times +chr21: 60.000000 occurs 840 times +chr21: 80.000000 occurs 195 times +chr21: 100.000000 occurs 20 times |
| b |
| diff -r 8377a6abb4da -r 61946b8bd43b test-data/table_qlo_notset_sample --- a/test-data/table_qlo_notset_sample Sun Jul 21 11:03:36 2024 +0000 +++ b/test-data/table_qlo_notset_sample Thu Jul 25 14:38:34 2024 +0000 |
| b |
| @@ -1,2 +1,57 @@ -bigwig contig n mean std min max qtop qbot -bigwig_sample Merlin 180929 6354.313736 9951.749936 0.000000 32767.000000 31906.72 noqlo +Descriptive measures +bigwig bigwig_sample +contig Merlin +n 180929 +mean 6354.313736 +std 9951.749936 +min 0.000000 +max 32767.000000 +qtop 31906.72 +qbot noqlo +First/Last 10 value counts +Value Count +0.00 110889 +13.00 30 +22.00 10 +26.00 10 +29.00 10 +40.00 10 +43.00 10 +53.00 10 +57.00 10 +60.00 20 +32721.00 10 +32724.00 10 +32726.00 10 +32728.00 10 +32730.00 10 +32731.00 20 +32737.00 10 +32745.00 10 +32766.00 10 +32767.00 10 +Histogram of bigwig_sample bigwig values +bigwig_sample_Merlin 1638.35 | 114,349 | ************************************************** +bigwig_sample_Merlin 3276.70 | 3,650 | * +bigwig_sample_Merlin 4915.05 | 3,620 | * +bigwig_sample_Merlin 6553.40 | 3,570 | * +bigwig_sample_Merlin 8191.75 | 3,570 | * +bigwig_sample_Merlin 9830.10 | 3,410 | * +bigwig_sample_Merlin 11468.45 | 3,610 | * +bigwig_sample_Merlin 13106.80 | 3,170 | * +bigwig_sample_Merlin 14745.15 | 3,310 | * +bigwig_sample_Merlin 16383.50 | 3,390 | * +bigwig_sample_Merlin 18021.85 | 3,270 | * +bigwig_sample_Merlin 19660.20 | 3,680 | * +bigwig_sample_Merlin 21298.55 | 3,560 | * +bigwig_sample_Merlin 22936.90 | 3,490 | * +bigwig_sample_Merlin 24575.25 | 3,530 | * +bigwig_sample_Merlin 26213.60 | 3,460 | * +bigwig_sample_Merlin 27851.95 | 3,470 | * +bigwig_sample_Merlin 29490.30 | 3,500 | * +bigwig_sample_Merlin 31128.65 | 3,920 | * +bigwig_sample_Merlin 32767.00 | 3,400 | * +bigwig_sample_Merlin ------------ |------------ | +bigwig_sample_Merlin N= | 180,929 | +bigwig_sample_Merlin ------------ |------------ | + |
| b |
| diff -r 8377a6abb4da -r 61946b8bd43b test-data/table_sample --- a/test-data/table_sample Sun Jul 21 11:03:36 2024 +0000 +++ b/test-data/table_sample Thu Jul 25 14:38:34 2024 +0000 |
| b |
| @@ -1,2 +1,57 @@ -bigwig contig n mean std min max qtop qbot -bigwig_sample Merlin 180929 6354.313736 9951.749936 0.000000 32767.000000 31906.72 0.00 +Descriptive measures +bigwig bigwig_sample +contig Merlin +n 180929 +mean 6354.313736 +std 9951.749936 +min 0.000000 +max 32767.000000 +qtop 31906.72 +qbot 0.00 +First/Last 10 value counts +Value Count +0.00 110889 +13.00 30 +22.00 10 +26.00 10 +29.00 10 +40.00 10 +43.00 10 +53.00 10 +57.00 10 +60.00 20 +32721.00 10 +32724.00 10 +32726.00 10 +32728.00 10 +32730.00 10 +32731.00 20 +32737.00 10 +32745.00 10 +32766.00 10 +32767.00 10 +Histogram of bigwig_sample bigwig values +bigwig_sample_Merlin 1638.35 | 114,349 | ************************************************** +bigwig_sample_Merlin 3276.70 | 3,650 | * +bigwig_sample_Merlin 4915.05 | 3,620 | * +bigwig_sample_Merlin 6553.40 | 3,570 | * +bigwig_sample_Merlin 8191.75 | 3,570 | * +bigwig_sample_Merlin 9830.10 | 3,410 | * +bigwig_sample_Merlin 11468.45 | 3,610 | * +bigwig_sample_Merlin 13106.80 | 3,170 | * +bigwig_sample_Merlin 14745.15 | 3,310 | * +bigwig_sample_Merlin 16383.50 | 3,390 | * +bigwig_sample_Merlin 18021.85 | 3,270 | * +bigwig_sample_Merlin 19660.20 | 3,680 | * +bigwig_sample_Merlin 21298.55 | 3,560 | * +bigwig_sample_Merlin 22936.90 | 3,490 | * +bigwig_sample_Merlin 24575.25 | 3,530 | * +bigwig_sample_Merlin 26213.60 | 3,460 | * +bigwig_sample_Merlin 27851.95 | 3,470 | * +bigwig_sample_Merlin 29490.30 | 3,500 | * +bigwig_sample_Merlin 31128.65 | 3,920 | * +bigwig_sample_Merlin 32767.00 | 3,400 | * +bigwig_sample_Merlin ------------ |------------ | +bigwig_sample_Merlin N= | 180,929 | +bigwig_sample_Merlin ------------ |------------ | + |