Wd (#14)

ChangeLog

@@ -1,15 +1,17 @@
 CHANGES
 =======
 
-* non-canonical deeptools to get rid of comp problem
-* ignore
-* cap snakemake -> tmp & profile
-* rewrite - after alsieve
-* ignore build
-* purge&ignore
-* restructure to make code less obfuscated + pave way for multicomps
-* egg exclude
-* RPKM bigwigs
+* include frig fig, ignore > 1000 for fragsize, set threads motif cluster
+* uropa change defaults + checks gtf
+* make to preserve key order in yaml dump. Purge ESS
+* switch to gene for uropa annotation as default
+* Update README.md
+* Wd (#9)
+* meme working
+* babysteps into tobias/motifs
+* purgebuild
+* Wd (#8)
+* Wd (#6)
 * update readme
 * Shuffling
 * fix batch vs non batch in 1 run

src/AOS/helper.py

@@ -30,8 +30,9 @@ def plotfragsize(frags):
     for i,r in df.iterrows():
         size = int(r[0])
         occ = int(r[1])
-        for k in repeat(size, occ):
-            reps.append([r['Sample'], size])
+        if size < 1000:
+            for k in repeat(size, occ):
+                reps.append([r['Sample'], size])
     df = pd.DataFrame(reps)
     df.columns = ['sample', 'size']
     df.sort_values(by=['sample'], inplace=True)
@@ -238,15 +239,15 @@ def peak_boundaries(peaks, genomefa, of):
     with open(genomefa) as f:
         for line in f:
             if line.startswith('>'):
-                header = line.strip().replace('>', '')
+                header = str(line.strip().replace('>', '').split(' ')[0])
                 chromdic[header] = 0
             else:
                 chromdic[header] += len(line.strip())
     bedlis = []
     peakchange = 0 
     with open(peaks) as f:
         for line in f:
-            chrom = line.strip().split()[0]
+            chrom = str(line.strip().split()[0])
             start = int(line.strip().split()[1])
             end = int(line.strip().split()[2])
             if end > chromdic[chrom]:
@@ -266,3 +267,38 @@ def peak_boundaries(peaks, genomefa, of):
         header=False,
         index=False
     )
+
+def PCA_colors(config):
+    colors = [
+        '#1f77b4',
+        '#ff7f0e',
+        '#2ca02c',
+        '#d62728',
+        '#9467bd',
+        '#8c564b',
+        '#e377c2',
+        '#7f7f7f',
+        '#bcbd22',
+        '#17becf'
+    ]
+    if config['files']['samplesheet']:
+        sdf = pd.read_csv(
+            config['files']['samplesheet'],
+            sep='\t',
+            header=0
+        )
+        sdf = sdf.set_index('sample')
+        sdf = sdf.loc[config['samples']]
+        colDic = {}
+        colIx = 0
+        for s in sdf.iloc[:,[0]].values:
+            if s[0] not in colDic:
+                colDic[s[0]] = colors[colIx]
+                colIx += 1
+        PCAstr = "--colors"
+        for s in sdf.iloc[:,[0]].values:
+            PCAstr += " \"{}\"".format(
+                colDic[s[0]]
+            )
+        return (PCAstr)
+    return ("")

src/AOS/rules/motifs.smk

@@ -11,6 +11,7 @@ rule clustermotifs:
   output:
     'motifs_clustered/clusteredmotifs_consensus_motifs.meme'
   conda: config['envs']['tobias']
+  threads: 10
   shell:'''
   TOBIAS ClusterMotifs -m {input} -t 0.4 -a meme -p clusteredmotifs -o 'motifs_clustered' --dist_method seqcor
   '''

src/AOS/rules/peaks.smk

@@ -1,4 +1,6 @@
 from AOS.helper import peak_boundaries
+from AOS.helper import PCA_colors
+
 rule lnBams:
   input: 
     os.path.join(config['dirs']['bamdir'], "{sample}.bam")
@@ -164,11 +166,13 @@ rule multibigwigsum:
 
 rule plotPCA:
   input:
-    'peakset/counts.bw.npz'
+    peakset = 'peakset/counts.bw.npz'
   output:
     'figures/PCA.png'
   threads: 1
+  params:
+    colstr = PCA_colors(config)
   conda: config['envs']['seqtools']
   shell:'''
-  plotPCA --corData {input} -o {output} --transpose --ntop 5000
+  plotPCA --corData {input.peakset} -o {output} --transpose --ntop 5000 {params.colstr}
   '''

src/AOS/workflow.smk

@@ -33,7 +33,8 @@ def geto():
       'figures/mitofraction.png',
       'qc/fragsize.tsv',
       'figures/alignmentsieve.png',
-      'figures/fragmentsizes.png'
+      'figures/fragmentsizes.png',
+      'figures/fripscores.png'
     ]
   )
   # Differential