Merge pull request #943 from deeptools/develop

changed iteritmes() in estimateEscaleFactor to its python3 compatible items()

CHANGES.txt

@@ -1,3 +1,8 @@
+3.4.3
+
+ * Changed iteritems() in estimateEscaleFactor to its python3 compatible items().
+ * Added the missing argument (--clusterUsingSamples) to plotProfile.
+
 3.4.2
 
  * Programmed around a bug in matplotlib that prevented the plotCorrelation scatter plot from working. See https://bioinformatics.stackexchange.com/questions/12830/plot-correlation-between-several-bam-files/12831
@@ -325,7 +330,7 @@
  * bamPEFragmentSize now has -bs and -n options to allow adjusting the number of alignments sampled. Note that the default value is auto-adjusted if the sampling is too sparse.
  * bamPEFragmentSize now accepts single-end files.
  * The --hclust option to plotProfile and plotHeatmap continues even if one of the groups is too small for plotting (matplotlib will produce a warning that you can ignore). This was issue #280.
- 
+
 2.0.1
 
  * A critical bug that prevented plotPCA from running was fixed.

bin/estimateScaleFactor

@@ -89,24 +89,24 @@ def parseArguments(args=None):
 
 def main(args):
     """
-    The algorithm samples the genome a number of times as specified 
+    The algorithm samples the genome a number of times as specified
     by the --numberOfSamples parameter to estimate scaling factors of
-    betweeen to samples  
+    betweeen to samples
 
     """
     if len(args.bamfiles) > 2:
         print("SES method to stimate scale factors only works for two samples")
         exit(0)
 
     sys.stderr.write("{:,} number of samples will be computed.\n".format(args.numberOfSamples))
-    sizeFactorsDict = estimateScaleFactor(args.bamfiles, args.sampleWindowLength, 
+    sizeFactorsDict = estimateScaleFactor(args.bamfiles, args.sampleWindowLength,
                                           args.numberOfSamples,
                                           args.normalizationLength,
                                           numberOfProcessors=args.numberOfProcessors,
                                           chrsToSkip=args.ignoreForNormalization,
                                           verbose=args.verbose)
 
-    for k, v in sizeFactorsDict.iteritems():
+    for k, v in sizeFactorsDict.items():
          print("{}: {}".format(k, v))
 
 

deeptools/_version.py

@@ -2,4 +2,4 @@
 # This file is originally generated from Git information by running 'setup.py
 # version'. Distribution tarballs contain a pre-generated copy of this file.
 
-__version__ = '3.4.2'
+__version__ = '3.4.3'

deeptools/parserCommon.py

@@ -573,6 +573,14 @@ def heatmapperOptionalArgs(mode=['heatmap', 'profile'][0]):
                               type=int,
                               default=8)
 
+        optional.add_argument('--clusterUsingSamples',
+                              help='List of sample numbers (order as in '
+                              'matrix), that are used for clustering by '
+                              '--kmeans or --hclust if not given, all samples '
+                              'are taken into account for clustering. '
+                              'Example: --ClusterUsingSamples 1 3',
+                              type=int, nargs='+')
+
     elif mode == 'heatmap':
         optional.add_argument(
             '--plotType',

deeptools/plotProfile.py

@@ -909,12 +909,12 @@ def main(args=None):
         filterHeatmapValues(hm, hm.parameters['min threshold'], hm.parameters['max threshold'])
 
     if args.kmeans is not None:
-        hm.matrix.hmcluster(args.kmeans, method='kmeans')
+        hm.matrix.hmcluster(args.kmeans, method='kmeans', clustering_samples=args.clusterUsingSamples)
     else:
         if args.hclust is not None:
             print("Performing hierarchical clustering."
                   "Please note that it might be very slow for large datasets.\n")
-            hm.matrix.hmcluster(args.hclust, method='hierarchical')
+            hm.matrix.hmcluster(args.hclust, method='hierarchical', clustering_samples=args.clusterUsingSamples)
 
     group_len_ratio = np.diff(hm.matrix.group_boundaries) / float(len(hm.matrix.regions))
     if np.any(group_len_ratio < 5.0 / 1000):

galaxy/wrapper/deepTools_macros.xml

@@ -1,10 +1,10 @@
 <macros>
 
     <token name="@THREADS@">--numberOfProcessors "\${GALAXY_SLOTS:-4}"</token>
-    <token name="@WRAPPER_VERSION@">3.4.2.0</token>
+    <token name="@WRAPPER_VERSION@">3.4.3.0</token>
     <xml name="requirements">
         <requirements>
-            <requirement type="package" version="3.4.2">deeptools</requirement>
+            <requirement type="package" version="3.4.3">deeptools</requirement>
             <requirement type="package" version="1.9">samtools</requirement>
         </requirements>
         <expand macro="stdio" />