[pre-commit.ci] pre-commit autoupdate

.pre-commit-config.yaml

@@ -11,7 +11,7 @@ exclude: |
    )
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v1.2.3
+    rev: v6.0.0
     hooks:
       - id: check-added-large-files
         args: ["--maxkb=10240"]
@@ -20,30 +20,30 @@ repos:
       - id: check-json
   # spell check
   - repo: https://github.com/codespell-project/codespell
-    rev: v2.4.1
+    rev: v2.4.2
     hooks:
       - id: codespell
         args: ["--ignore-words-list=bais"]
   # Python formatting
-  - repo: https://github.com/psf/black
-    rev: 23.7.0
+  - repo: https://github.com/psf/black-pre-commit-mirror
+    rev: 26.3.0
     hooks:
       - id: black
   # R formatting
   - repo: https://github.com/lorenzwalthert/precommit
-    rev: v0.1.2
+    rev: v0.4.3.9021
     hooks:
       - id: style-files
   # general linting
   - repo: https://github.com/pre-commit/mirrors-prettier
-    rev: "v3.1.0"
+    rev: "v4.0.0-alpha.8"
     hooks:
       - id: prettier
         additional_dependencies:
           - prettier@3.4.0
   # enforce commit format
   - repo: https://github.com/compilerla/conventional-pre-commit
-    rev: v2.3.0
+    rev: v4.4.0
     hooks:
       - id: conventional-pre-commit
         stages: [commit-msg]

bin/calc_effective_genome_fraction.py

@@ -65,9 +65,7 @@ def test():
 chr22	50818468
 chr_X	156040895
 chr_Y	57227415
-chr_M	16569""".split(
-        "\n"
-    )
+chr_M	16569""".split("\n")
     effective_genome_size = 2700000000
 
     assert calc_egf(effective_genome_size, chrom_sizes) == 0.9391299376153861

bin/check_samplesheet.py

@@ -3,6 +3,7 @@
 """
 adapted from: https://github.com/nf-core/chipseq/blob/51eba00b32885c4d0bec60db3cb0a45eb61e34c5/bin/check_samplesheet.py
 """
+
 import collections
 import os
 import errno

bin/compute_scaling_factors.py

@@ -8,6 +8,7 @@
 Example:
     python compute_scaling_factors.py "id1,id2,id3" "100,200,300" scaling_factors.tsv
 """
+
 import sys
 
 

bin/consensus_corces.py

@@ -5,6 +5,7 @@
 
 https://github.com/CCBR/CHAMPAGNE/issues/159
 """
+
 import sys
 
 

bin/createtable.py

@@ -11,9 +11,10 @@
        structure is then converted into a pandas dataframe.
        Example Usage:
        --------------
-	   cat sample1.qcmetrics sample2.qcmetrics sampleNth.qcmetrics | ./createQCTable > ChIPseq_QC_Table.txt
+           cat sample1.qcmetrics sample2.qcmetrics sampleNth.qcmetrics | ./createQCTable > ChIPseq_QC_Table.txt
 Python version: 3+
 """
+
 import pandas as pd
 import sys
 

bin/filterMetrics.py

@@ -12,29 +12,29 @@
 
        Example Usage:
        --------------
-	1.) Find total number of reads
+        1.) Find total number of reads
           # grep 'in total' H3k4me3_gran_1.sorted.bam.flagstat | awk '{print $1,$3}' | ./filterMetrics H3k4me3_gran_1 tnreads
 
-	2.) Find total number of mapped reads
-	  # grep 'mapped (' H3k4me3_gran_1.sorted.bam.flagstat | awk '{print $1,$3}' | ./filterMetrics H3k4me3_gran_1 mnreads
+        2.) Find total number of mapped reads
+          # grep 'mapped (' H3k4me3_gran_1.sorted.bam.flagstat | awk '{print $1,$3}' | ./filterMetrics H3k4me3_gran_1 mnreads
 
-	3.) Find total number of uniquely mapped reads
-	  # grep 'mapped (' H3k4me3_gran_1.sorted.Q5DD.bam.flagstat | awk '{print $1,$3}' | ./filterMetrics H3k4me3_gran_1 unreads
+        3.) Find total number of uniquely mapped reads
+          # grep 'mapped (' H3k4me3_gran_1.sorted.Q5DD.bam.flagstat | awk '{print $1,$3}' | ./filterMetrics H3k4me3_gran_1 unreads
 
-	4.) Find NRF, PCB1, PCB2
-	  # cat H3k4me3_gran_1.nrf | ./filterMetrics H3k4me3_gran_1 nrf
+        4.) Find NRF, PCB1, PCB2
+          # cat H3k4me3_gran_1.nrf | ./filterMetrics H3k4me3_gran_1 nrf
 
-	7.) Find FRiP (in the second half of ChIP-seq pipeline)
-	  # TO-DO
+        7.) Find FRiP (in the second half of ChIP-seq pipeline)
+          # TO-DO
 
-	8.) Find NGSQC statistics (detla RCIs)
-	  # grep '<' NGSQC_report.txt | awk '{print $(NF)}' | xargs | ./filterMetrics H3k4me3_gran_1 ngsqc
+        8.) Find NGSQC statistics (detla RCIs)
+          # grep '<' NGSQC_report.txt | awk '{print $(NF)}' | xargs | ./filterMetrics H3k4me3_gran_1 ngsqc
 
-	9.) Find NSC, RSC, Qtag
-	  # awk '{print $(NF-2),$(NF-1),$(NF)}' H3k4me3_gran_1.sorted.Q5DD.ppqt | ./filterMetrics H3k4me3_gran_1 ppqt
+        9.) Find NSC, RSC, Qtag
+          # awk '{print $(NF-2),$(NF-1),$(NF)}' H3k4me3_gran_1.sorted.Q5DD.ppqt | ./filterMetrics H3k4me3_gran_1 ppqt
 
-	10.) Find the Fragment Length
-	  # awk -F '\t' '{print $3}' H3k4me3_gran_1.sorted.Q5DD.ppqt | sed -e 's/,/ /g' | ../Scripts/filterMetrics H3k4me3_gran_1 fragLen
+        10.) Find the Fragment Length
+          # awk -F '\t' '{print $3}' H3k4me3_gran_1.sorted.Q5DD.ppqt | sed -e 's/,/ /g' | ../Scripts/filterMetrics H3k4me3_gran_1 fragLen
 
 Python version(s):	2.7 or 3.X
 

bin/frip.py

@@ -113,15 +113,15 @@ def process_files(bamfile, bedfiles, genome, filetypes, bedtool=None, bedsample=
         ]
     ]
     nreads = count_reads_in_bam(bamfile)
-    (bamsample, condition) = clip_bamfile_name(bamfile)
+    bamsample, condition = clip_bamfile_name(bamfile)
     for i in range(len(bedfileL)):
         bed = bedfileL[i]
         if len(filetypesL) > 1:
             filetype = filetypesL[i]
         else:
             filetype = filetypesL[0]
         if not bedtool and not bedsample:
-            (bedtool, bedsample) = clip_bedfile_name(bed, filetype)
+            bedtool, bedsample = clip_bedfile_name(bed, filetype)
         noverlaps = count_reads_in_bed(bamfile, bed, genome)
         frip = calculate_frip(nreads, noverlaps)
         nbases = measure_bedfile_coverage(bed, genome) / 1000000
@@ -134,7 +134,7 @@ def process_files(bamfile, bedfiles, genome, filetypes, bedtool=None, bedsample=
 
 def create_outfile_name(bamfile, outroot):
     """uses outroot to create the output file name"""
-    (bamsample, condition) = clip_bamfile_name(bamfile)
+    bamsample, condition = clip_bamfile_name(bamfile)
     outtable = bamsample + "." + condition + "." + "FRiP_table.txt"
     if outroot != "":
         outtable = outroot + "." + outtable
@@ -200,7 +200,7 @@ def main():
         "-s", dest="sample", default="", help="Sample name/ID of the bedfile(s)"
     )
 
-    (options, args) = parser.parse_args()
+    options, args = parser.parse_args()
     bedfiles = options.peakfiles
     bamfile = options.bamfile
     genomefile = options.genomefile

bin/get_consensus_peaks.py

@@ -2,6 +2,7 @@
 """
 adapted from https://github.com/CCBR/ASPEN/blob/55f909d76500c3502c1c397ef3000908649b0284/workflow/scripts/ccbr_get_consensus_peaks.py
 """
+
 import os
 import argparse
 import uuid

bin/make_sf_table.py

@@ -8,6 +8,7 @@
 Example:
     python make_sf_table.py scaling_factors_1.tsv,scaling_factors_2.tsv id1,id2,id3 ab1,ab2 100,200,300 spike_sf.tsv
 """
+
 from collections import defaultdict
 import sys
 

bin/ngsqc_plot.py

@@ -145,7 +145,7 @@ def main():
 the output file name.",
     )
 
-    (options, args) = parser.parse_args()
+    options, args = parser.parse_args()
     directory = options.directory
     ext = options.ext
     group = options.group

modules/local/check_contrasts/templates/check_contrasts.R

@@ -13,7 +13,7 @@ main <- function(contrasts_filename = "${contrasts}",
   assert_that(all(colnames(contrasts_df) == c("contrast_name", "group1", "group2")))
 
   samples_df <- readr::read_csv(samplesheet_filename)
-  sample_names  <- samples_df %>% dplyr::pull(sample)
+  sample_names <- samples_df %>% dplyr::pull(sample)
   # check individual contrasts
   purrr::pmap(contrasts_df, check_contrast, sample_names = sample_names)
 
@@ -32,13 +32,16 @@ check_contrast <- function(contrast_name, group1, group2, sample_names) {
   group2_samples <- unlist(strsplit(group2, ","))
   # Ensure each group has at least 1 sample
   assert_that(length(group1_samples) > 0,
-              msg = glue("group1 must have at least one sample for {contrast_name}"))
+    msg = glue("group1 must have at least one sample for {contrast_name}")
+  )
   assert_that(length(group2_samples) > 0,
-              msg = glue("group2 must have at least one sample for {contrast_name}"))
+    msg = glue("group2 must have at least one sample for {contrast_name}")
+  )
   # Ensure every sample is in the sample sheet
-  extra_samples <- setdiff(c(group1_samples,group2_samples), sample_names)
+  extra_samples <- setdiff(c(group1_samples, group2_samples), sample_names)
   assert_that(length(extra_samples) == 0,
-              msg = glue("All samples in {contrast_name} must be in the sample sheet. Extra samples found: {paste(extra_samples, collapse = ',')}"))
+    msg = glue("All samples in {contrast_name} must be in the sample sheet. Extra samples found: {paste(extra_samples, collapse = ',')}")
+  )
   # Ensure each sample is in only one group
   assert_that(
     length(intersect(group1_samples, group2_samples)) == 0,