Trying to fix garbage collection issues.

When R crashes, rpy doesn't seem to handle this properly.

libdeseq/libdeseq/libdeseq.py

@@ -14,6 +14,7 @@ as_df = r("as.data.frame")
 from rpy2.rinterface import RRuntimeError
 from rpy2.robjects.packages import importr
 deseq2 = importr("DESeq2")
+#import gc
 
 
 def do_deseq2(cond_names, conditions, counts_data,
@@ -65,6 +66,7 @@ def do_deseq2(cond_names, conditions, counts_data,
     #     raise
     try:
         dds = deseq2.estimateSizeFactors_DESeqDataSet(dds, type="ratio")
+        #gc.collect()
     except RRuntimeError as e:
         if sum(counts_data.prod(axis=1)) == 0:
             msg = "".join(["Error occurred in estimateSizeFactors:\n%s\n" % e,
@@ -73,10 +75,12 @@ def do_deseq2(cond_names, conditions, counts_data,
             warnings.warn(msg)
             try:
                 dds = deseq2.estimateSizeFactors_DESeqDataSet(dds, type="poscounts")
+                #gc.collect()
             except RRuntimeError as e:
                 msg = "".join(["Error occurred in estimateSizeFactors:\n%s\n" % e,
                                "We give up."])
                 warnings.warn(msg)
+                #gc.collect()
                 raise
                 #print(counts_data.dtypes)
                 #print(counts_data.columns)
@@ -91,24 +95,29 @@ def do_deseq2(cond_names, conditions, counts_data,
     #pd.DataFrame({cond : size_factors.loc[cond][0] for cond in COND_NAMES}, index=('size_factor',))
     try:
         dds = deseq2.estimateDispersions_DESeqDataSet(dds, fitType="parametric")
+        #gc.collect()
     except RRuntimeError as e:
         msg = "".join(["Error occurred in estimateDispersions:\n%s\n" % e,
                     "We will try with fitType=\"local\"."])
         warnings.warn(msg)
         try:
             dds = deseq2.estimateDispersions_DESeqDataSet(dds, fitType="local")
+            #gc.collect()
         except RRuntimeError as e:
             msg = "".join(["Error occurred in estimateDispersions:\n%s\n" % e,
                         "We will try with fitType=\"mean\"."])
             warnings.warn(msg)
             try:
                 dds = deseq2.estimateDispersions_DESeqDataSet(dds, fitType="mean")
+                #gc.collect()
             except RRuntimeError as e:
                 msg = "".join(["Error occurred in estimateDispersions:\n%s\n" % e,
                             "We give up."])
                 warnings.warn(msg)
+                #gc.collect()
                 raise
     dds = deseq2.nbinomWaldTest(dds, betaPrior=deseq2_args["betaPrior"])
+    #gc.collect()
     res = pandas2ri.ri2py(as_df(deseq2.results(
         dds,
         contrast=contrast,