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changeset 0:e11314245c2a draft

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Imported from capsule None
author devteam
date Tue, 01 Apr 2014 09:11:55 -0400
parents
children 68a40b074399
files WeightedAverage.py WeightedAverage.xml test-data/interpolate_result.bed test-data/interval_interpolate.bed test-data/value_interpolate.bed
diffstat 5 files changed, 3397 insertions(+), 0 deletions(-) [+]
line wrap: on
line diff
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/WeightedAverage.py	Tue Apr 01 09:11:55 2014 -0400
@@ -0,0 +1,94 @@
+#!/usr/bin/env python
+"""
+usage: %prog bed_file_1 bed_file_2 out_file
+    -1, --cols1=N,N,N,N: Columns for chr, start, end, strand in first file
+    -2, --cols2=N,N,N,N,N: Columns for chr, start, end, strand, name/value in second file
+"""
+
+import collections
+import sys
+#import numpy
+from galaxy import eggs
+import pkg_resources
+pkg_resources.require( "bx-python" )
+from galaxy.tools.util.galaxyops import *
+from bx.cookbook import doc_optparse
+
+
+#export PYTHONPATH=~/galaxy/lib/
+#running command python WeightedAverage.py interval_interpolate.bed value_interpolate.bed interpolate_result.bed
+
+def stop_err(msg):
+    sys.stderr.write(msg)
+    sys.exit()
+
+
+def FindRate(chromosome, start_stop, dictType):
+    OverlapList = []
+    for tempO in dictType[chromosome]:
+        DatabaseInterval = [tempO[0], tempO[1]]
+        Overlap = GetOverlap( start_stop, DatabaseInterval )
+        if Overlap > 0:
+            OverlapList.append([Overlap, tempO[2]])
+    
+    if len(OverlapList) > 0:
+        SumRecomb = 0
+        SumOverlap = 0
+        for member in OverlapList:
+            SumRecomb += member[0]*member[1]
+            SumOverlap += member[0]
+        averageRate = SumRecomb/SumOverlap
+        return averageRate
+    else:
+        return 'NA'
+
+
+def GetOverlap(a, b):
+    return min(a[1], b[1])-max(a[0], b[0])
+
+
+options, args = doc_optparse.parse( __doc__ )
+
+try:
+    chr_col_1, start_col_1, end_col_1, strand_col1 = parse_cols_arg( options.cols1 )
+    chr_col_2, start_col_2, end_col_2, strand_col2, name_col_2 = parse_cols_arg( options.cols2 )
+    input1, input2, input3 = args
+except Exception, eee:
+    print eee
+    stop_err( "Data issue: click the pencil icon in the history item to correct the metadata attributes." )
+
+fd2 = open(input2)
+lines2 = fd2.readlines()
+RecombChrDict = collections.defaultdict(list)
+
+skipped = 0
+for line in lines2:
+    temp = line.strip().split()
+    try:
+        assert float(temp[int(name_col_2)])
+    except:
+        skipped += 1
+        continue
+    tempIndex = [int(temp[int(start_col_2)]), int(temp[int(end_col_2)]), float(temp[int(name_col_2)])]
+    RecombChrDict[temp[int(chr_col_2)]].append(tempIndex)
+
+print "Skipped %d features with invalid values" % (skipped)
+
+fd1 = open(input1)
+lines = fd1.readlines()
+finalProduct = ''
+for line in lines:
+    temp = line.strip().split('\t')
+    chromosome = temp[int(chr_col_1)]
+    start = int(temp[int(start_col_1)])
+    stop = int(temp[int(end_col_1)])
+    start_stop = [start, stop]
+    RecombRate = FindRate( chromosome, start_stop, RecombChrDict )
+    try:
+        RecombRate = "%.4f" % (float(RecombRate))
+    except:
+        RecombRate = RecombRate
+    finalProduct += line.strip()+'\t'+str(RecombRate)+'\n'
+fdd = open(input3, 'w')
+fdd.writelines(finalProduct)
+fdd.close()
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/WeightedAverage.xml	Tue Apr 01 09:11:55 2014 -0400
@@ -0,0 +1,71 @@
+<tool id="wtavg" name="Assign weighted-average" version="1.0.0">
+  <description> of the values of features overlapping an interval </description>
+  <command interpreter="python">WeightedAverage.py  $genomic_interval $genomic_feature $out_file1 -1 ${genomic_interval.metadata.chromCol},${genomic_interval.metadata.startCol},${genomic_interval.metadata.endCol},${genomic_interval.metadata.strandCol} -2 ${genomic_feature.metadata.chromCol},${genomic_feature.metadata.startCol},${genomic_feature.metadata.endCol},${genomic_feature.metadata.strandCol},${genomic_feature.metadata.nameCol}</command>
+
+  <inputs>
+    <param format="interval" name="genomic_interval" type="data" label="Genomic intervals (first dataset)" help="Dataset missing? See Note below."/>
+    <param format="interval" name="genomic_feature" label="Genomic features (second dataset)" type="data" help="Make sure the value column is specified. See Note below." />
+  </inputs>
+  <outputs>
+    <data format="input" name="out_file1" metadata_source="genomic_interval" />
+  </outputs>
+  <tests>
+    <!-- Test data with valid values -->
+    <test>
+      <param name="genomic_interval" value="interval_interpolate.bed"/>
+      <param name="genomic_feature" value="value_interpolate.bed"/>
+      <output name="out_file1" file="interpolate_result.bed"/>
+    </test>
+    
+  </tests>
+  <help>
+
+
+.. class:: infomark
+
+**What it does**
+
+For each interval in your first dataset, this tool calculates the weighted average value of the overlapping features in your second dataset.
+
+- When a genomic interval partially or totally overlaps a single genomic feature, the value of that genomic feature is assigned to the genomic interval.
+- When a genomic interval partially or totally overlaps with more than one genomic features, the average of the values of the overlapping genomic features weighted by the corresponding number of overlapping bases is assigned to the genomic interval.
+- When a genomic interval does not overlap with any genomic feature, 'NA' will be assigned as it's value.
+
+-----
+
+.. class:: warningmark
+
+**Note**
+
+The input datasets should be in **bed** or **interval** format. Please use "edit attributes"/pencil icon to specify the column containing the values for the features in the second dataset as **name/identifier** column.
+
+The output will contain all the columns in the first input plus a new column containing the assigned value for each interval.
+
+-----
+
+**Example**
+
+- Suppose our first dataset contains the following **genomic intervals**::
+    
+    chr  start stop
+    chr1 1000  2000
+    chr1 3000  5000
+    chr1 8000  9000
+  
+- and our second dataset contains the following **genomic features** each having an associated value (in fourth column) ::
+
+    chr  start stop name
+    chr1 900   1200 0.5
+    chr1 2900  3100 0.2
+    chr1 4800  5100 0.8
+  
+- For each **genomic interval** in our first dataset, this tool calculates the weighted average value of the overlapping **genomic features** in our second dataset ::
+
+    chr1 1000  2000 0.5
+    chr1 3000  5000 0.6
+    chr1 8000  9000 NA
+  
+
+
+</help>
+</tool>
\ No newline at end of file
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/interpolate_result.bed	Tue Apr 01 09:11:55 2014 -0400
@@ -0,0 +1,219 @@
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+chr1	103686494	103843838	5000000	0	NA
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+chr1	120548679	120700000	3100000	0	NA
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+chr10	45896970	46849175	11200000	0	NA
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+chr10	47412482	47575713	11200000	0	NA
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+chrY	0	34821	11200000	0	NA
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\ No newline at end of file
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/interval_interpolate.bed	Tue Apr 01 09:11:55 2014 -0400
@@ -0,0 +1,219 @@
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/value_interpolate.bed	Tue Apr 01 09:11:55 2014 -0400
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\ No newline at end of file