Repository 'damidseq_consecutive_peaks'
hg clone https://toolshed.g2.bx.psu.edu/repos/mvdbeek/damidseq_consecutive_peaks

Changeset 1:f3ca59e53b73 (2018-10-29)
Previous changeset 0:7f827a8e4ec5 (2018-10-26)
Commit message:
planemo upload for repository https://github.com/bardin-lab/damid_galaxy_tools commit c753dd4f3e1863aae7ba45dcc7efdf6937b03542-dirty
modified:
consecutive_peaks.py
test-data/grouped.bed
b
diff -r 7f827a8e4ec5 -r f3ca59e53b73 consecutive_peaks.py
--- a/consecutive_peaks.py Fri Oct 26 11:58:06 2018 -0400
+++ b/consecutive_peaks.py Mon Oct 29 06:49:17 2018 -0400
[
@@ -19,11 +19,11 @@
     grouped = df.groupby(groupby_column, sort=False)
     if add_number_of_peaks:
         df[PEAKS_PER_GROUP] = grouped[groupby_column].transform(np.size)
-    df[SHIFTED_PADJ_COLUMN] = grouped[8].shift()
+    df[SHIFTED_PADJ_COLUMN] = grouped[padj_column].shift()
     df[CONSECUTIVE_MAX] = df[[padj_column, SHIFTED_PADJ_COLUMN]].max(axis=1)
     grouped = df.groupby(groupby_column, sort=False)
-    idx = grouped[CONSECUTIVE_MAX].transform(min)  # index of groupwise consecutive minimum
-    new_df = df[df[CONSECUTIVE_MAX] == idx]
+    idx = grouped[CONSECUTIVE_MAX].idxmin()  # index of groupwise consecutive minimum
+    new_df = df.loc[idx]
     new_df.sort_values(by=CONSECUTIVE_MAX)
     new_df[padj_column].replace(new_df[CONSECUTIVE_MAX])
     new_df = new_df.drop(labels=[CONSECUTIVE_MAX, SHIFTED_PADJ_COLUMN], axis=1)
b
diff -r 7f827a8e4ec5 -r f3ca59e53b73 test-data/grouped.bed
--- a/test-data/grouped.bed Fri Oct 26 11:58:06 2018 -0400
+++ b/test-data/grouped.bed Mon Oct 29 06:49:17 2018 -0400
b
@@ -1,9 +1,7 @@
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-37 2L 65315 65319 137.10185797165198 1.23449113928199 0.524990063103154 2.3514562008756097 0.0187000910325455 0.065785553432607 "gene_id ""FBgn0051973""; gene_symbol ""Cda5"";" 4
-39 2L 65671 65675 49.717233352585495 1.78672093221744 0.65335924547836 2.73466847616013 0.006244313130270829 0.0293462152487687 . 6