Avoiding deprecation warnings.

libworkflows/libworkflows/libworkflows.py

@@ -245,7 +245,7 @@ def sum_htseq_counts(counts_filename):
 
 
 def read_htseq_counts(counts_filename):
-    return pd.read_table(counts_filename, header=None, index_col=0).drop(
+    return pd.read_csv(counts_filename, sep="\t", header=None, index_col=0).drop(
         ["__no_feature",
          "__ambiguous",
          "__too_low_aQual",
@@ -260,11 +260,11 @@ def sum_feature_counts(counts_filename, nb_bams=1):
     This determines which columns should be used."""
     # Counts are in the 7-th column, starting from third row.
     # The first sum is over the the rows, the second over the columns
-    return pd.read_table(counts_filename, skiprows=2, usecols=range(6, 6 + nb_bams), header=None).sum().sum()
+    return pd.read_csv(counts_filename, sep="\t", skiprows=2, usecols=range(6, 6 + nb_bams), header=None).sum().sum()
 
 
 def read_feature_counts(counts_filename, nb_bams=1):
-    return pd.read_table(counts_filename, skiprows=1, usecols=[0, *range(6, 6 + nb_bams)], index_col=0)
+    return pd.read_csv(counts_filename, sep="\t", skiprows=1, usecols=[0, *range(6, 6 + nb_bams)], index_col=0)
 
 
 # I	3746	3909	"WBGene00023193"	-	.	17996
@@ -281,7 +281,7 @@ def sum_intersect_counts(counts_filename):
     """Sums all counts in a bedtools intersect generated *counts_filename*, where the annotation was in bed format."""
     # Counts are in the 7-th column
     try:
-        return pd.read_table(counts_filename, usecols=[6], header=None).sum().iloc[0]
+        return pd.read_csv(counts_filename, sep="\t", usecols=[6], header=None).sum().iloc[0]
     except pd.errors.EmptyDataError:
         return "NA"
 
@@ -289,7 +289,7 @@ def read_intersect_counts(counts_filename):
     # index_col takes effect after column selection with usecols, hence index_col=0 (ex-third column):
     # https://stackoverflow.com/a/45943627/1878788
     try:
-        return pd.read_table(counts_filename, usecols=[3,6], header=None, index_col=0)
+        return pd.read_csv(counts_filename, sep="\t", usecols=[3,6], header=None, index_col=0)
     except pd.errors.EmptyDataError:
         return pd.DataFrame(index = [], columns = ["gene", "counts"]).set_index("gene")