Fix/pr62 lint and snapshot

.github/actions/nf-test/action.yml

@@ -19,6 +19,16 @@ inputs:
 runs:
   using: "composite"
   steps:
+    # The pipeline pulls ~17 container images, three of them heavy bioconductor/R stacks, which
+    # overruns the runner disk part-way through (docker exit 125, "no space left on device").
+    # Reclaim the preinstalled toolchain first: the RunsOn default image is ubuntu24-full-x64, so the
+    # same Android/.NET/Haskell bloat as a GitHub-hosted runner is present and removable.
+    - name: Free disk space
+      uses: jlumbroso/free-disk-space@54081f138730dfa15788a46383842cd2f914a1be # v1.3.1
+      with:
+        tool-cache: false # later steps need the toolchain
+        large-packages: false # slowest sweep, smallest reliable gain
+
     - name: Setup Nextflow
       uses: nf-core/setup-nextflow@b4ec1bc7c16a94435159de94a05253542fddf6ef # v3
       with:

conf/modules.config

@@ -43,6 +43,9 @@ process {
     // --- Reference-derived, merged into intermediate_files ---
 
     withName: 'BWA_INDEX' {
+        cpus   = 1
+        memory = 1.GB
+        time   = 30.min
         publishDir = [
             path: "${params.outdir}/intermediate_files",
             mode: 'copy',

modules/local/dmsanalysis/process_variant_counts/templates/process_variant_counts.R

@@ -82,6 +82,7 @@ filter_counts_by_codon_library <- function(counts_file_path, codon_library_path,
   }
 
   # Filter the variant-count table
+  counts_table\$codon_mut <- toupper(counts_table\$codon_mut)
   filtered_counts <- counts_table %>%
     filter(varying_codons == 1) %>% # Keep rows with single-codon mutations
     rowwise() %>%
@@ -190,6 +191,7 @@ complete_prefiltered_counts <- function(possible_nnk_path, prefiltered_counts_pa
     mutate(codon_mut = paste0(Codon_Number, ":", wt_codon, ">", Variant))
 
   # Merge both dataframes based on the codon_mut column (full join to include all)
+  prefiltered_counts\$codon_mut <- toupper(prefiltered_counts\$codon_mut)
   merged_data <- full_join(prefiltered_counts, possible_nnk, by = "codon_mut")
 
   # Fill missing values in counts_per_cov and counts with 0.0000001

nextflow.config

@@ -11,8 +11,8 @@ params {
 
     input                      = null
 
-    min_counts			= 10
-    base_qual			= 30
+    min_counts			= 1
+    base_qual			= 40
     min_flank			= 2
     error_correction		= 'false_doubles'
     false_doubles_method	= 'mle'

nextflow_schema.json

@@ -50,13 +50,13 @@
                     "type": "integer",
                     "description": "minimum counts for variant to be recognized. All variants below min_counts will be set to 0",
                     "minimum": 1,
-                    "default": 10
+                    "default": 1
                 },
                 "base_qual": {
                     "type": "integer",
                     "description": "Minimum base quality (Phred) for a mutation to be counted by the variant counter.",
                     "minimum": 0,
-                    "default": 30
+                    "default": 40
                 },
                 "min_flank": {
                     "type": "integer",

tests/default.nf.test.snap

@@ -342,26 +342,26 @@
                 "GID1A.sa:md5,1f697dcb3fedd2f3f29642598bdd795b",
                 "possible_mutations.csv:md5,9ce59fe91b726b1d88587a13fa899567",
                 "seq_error_rate.csv:md5,350a018c981eca2506ac6291a6e9e161",
-                "variantCounts_for_heatmaps.csv:md5,842bd5c00760d594e2a450aec929e4aa",
-                "variantCounts_for_heatmaps_error_corrected.csv:md5,842bd5c00760d594e2a450aec929e4aa",
+                "variantCounts_for_heatmaps.csv:md5,8794f9fc716405d1891d24af6b636a2f",
+                "variantCounts_for_heatmaps_error_corrected.csv:md5,8794f9fc716405d1891d24af6b636a2f",
                 "seq_error_rate.csv:md5,350a018c981eca2506ac6291a6e9e161",
-                "variantCounts_for_heatmaps.csv:md5,44069d5abca76323ccaed3c182447104",
-                "variantCounts_for_heatmaps_error_corrected.csv:md5,44069d5abca76323ccaed3c182447104",
+                "variantCounts_for_heatmaps.csv:md5,63c358cb04210b9dda2416ab3352494a",
+                "variantCounts_for_heatmaps_error_corrected.csv:md5,63c358cb04210b9dda2416ab3352494a",
                 "seq_error_rate.csv:md5,350a018c981eca2506ac6291a6e9e161",
-                "variantCounts_for_heatmaps.csv:md5,3a9ce900a567cb663bc71033d3771d8a",
-                "variantCounts_for_heatmaps_error_corrected.csv:md5,3a9ce900a567cb663bc71033d3771d8a",
+                "variantCounts_for_heatmaps.csv:md5,33c6c3af1825b9ea7fbc949a18bb38aa",
+                "variantCounts_for_heatmaps_error_corrected.csv:md5,33c6c3af1825b9ea7fbc949a18bb38aa",
                 "seq_error_rate.csv:md5,350a018c981eca2506ac6291a6e9e161",
-                "variantCounts_for_heatmaps.csv:md5,f263448ec0d7ec68f6e23aa050b961e6",
-                "variantCounts_for_heatmaps_error_corrected.csv:md5,f263448ec0d7ec68f6e23aa050b961e6",
+                "variantCounts_for_heatmaps.csv:md5,5277b202849d27c0b1773cacd8aae416",
+                "variantCounts_for_heatmaps_error_corrected.csv:md5,5277b202849d27c0b1773cacd8aae416",
                 "variant_counts_columns.tsv:md5,c94801255a553ce5ff4a00d3170f6768",
                 "variant_counts_columns.tsv:md5,c94801255a553ce5ff4a00d3170f6768",
                 "variant_counts_columns.tsv:md5,c94801255a553ce5ff4a00d3170f6768",
                 "variant_counts_columns.tsv:md5,c94801255a553ce5ff4a00d3170f6768",
-                "seqdepth_curve.csv:md5,eceecf3eff21b17b1d818c6ccefa72d9",
-                "seqdepth_curve.csv:md5,04649f2dd97ae3f7f4d7a94efb299d78",
-                "seqdepth_curve.csv:md5,5bde4b2a2b0cce57f4696913f4cdf8e7",
-                "seqdepth_curve.csv:md5,0deb002959055376128c81bcfba8e0e2",
-                "error_correction_report.html:md5,45455144c768473a8242381380deeba8",
+                "seqdepth_curve.csv:md5,b3d9041a2812b56a813bb69f61c7163a",
+                "seqdepth_curve.csv:md5,47bc7210d898e07966ac9a7adfec9ebf",
+                "seqdepth_curve.csv:md5,148be1fe719cf8194e4539cba7a7361a",
+                "seqdepth_curve.csv:md5,96bbb8a5e431acfa97a2e3960cce1e32",
+                "error_correction_report.html:md5,802b1cca71ffb34758810cea748c73ea",
                 "fastqc-status-check-heatmap.txt:md5,58a9580c11af4210b1af65753383e120",
                 "fastqc_adapter_content_plot.txt:md5,2990ad34b6fa29151dd4b9a38828afbe",
                 "fastqc_overrepresented_sequences_plot.txt:md5,c703a9df0ea3a5c1c5f515a1fd88bbe8",
@@ -377,11 +377,11 @@
                 "multiqc_general_stats.txt:md5,7c2fd44ded06835128a208d3365aa23b"
             ],
             {
-                "edger_rowCount": 1231,
-                "limma_rowCount": 1231
+                "edger_rowCount": 1230,
+                "limma_rowCount": 1230
             }
         ],
-        "timestamp": "2026-07-22T20:08:15.261389",
+        "timestamp": "2026-08-25T00:14:40.583305",
         "meta": {
             "nf-test": "0.9.4",
             "nextflow": "26.04.1"