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fix(diann): Add q-value filtering to DIANN big clean function #11

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Merged
tonywu1999 merged 2 commits into from
Feb 8, 2026
Merged

fix(diann): Add q-value filtering to DIANN big clean function #11

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0870e2b
fix(diann): Add q-value filtering to DIANN big clean function
tonywu1999 Feb 6, 2026
2877c01
add pull request template and dry run build workflow
tonywu1999 Feb 6, 2026
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18 changes: 18 additions & 0 deletions .github/pull_request_template.md
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Original file line number Diff line number Diff line change
@@ -0,0 +1,18 @@
# Motivation and Context

Please include relevant motivation and context of the problem along with a short summary of the solution.

## Changes

Please provide a detailed bullet point list of your changes.

-

## Testing

Please describe any unit tests you added or modified to verify your changes.

## Checklist Before Requesting a Review
- [ ] I have read the MSstats [contributing guidelines](https://github.com/Vitek-Lab/MSstatsConvert/blob/master/.github/CONTRIBUTING.md)
- [ ] My changes generate no new warnings
- [ ] Any dependent changes have been merged and published in downstream modules
19 changes: 19 additions & 0 deletions .github/workflows/dry-run-build.yml
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name: Dry runs for PRs
on:
pull_request:
branches: [devel]
jobs:
build:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Setup R and Bioconductor
uses: grimbough/bioc-actions/setup-bioc@v1
with:
bioc-version: devel
- name: Install dependencies
uses: r-lib/actions/setup-r-dependencies@v2
- name: Build, Install, Check
uses: grimbough/bioc-actions/build-install-check@v1

10 changes: 7 additions & 3 deletions R/clean_DIANN.R
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Expand Up @@ -49,10 +49,14 @@ cleanDIANNChunk = function(input, output_path, MBR, quantificationColumn, pos,
qvalue_cutoff = 0.01,
pg_qvalue_cutoff = 0.01) {
input = MSstatsImport(list(input = input),
"MSstats", "DIANN")
"MSstats", "DIANN")
input = MSstatsClean(
input, MBR, quantificationColumn
#Todo: Add , global_qvalue_cutoff, qvalue_cutoff, pg_qvalue_cutoff params
input,
MBR = MBR,
quantificationColumn = quantificationColumn,
global_qvalue_cutoff = global_qvalue_cutoff,
qvalue_cutoff = qvalue_cutoff,
pg_qvalue_cutoff = pg_qvalue_cutoff
)
.writeChunkToFile(input, output_path, pos)
NULL
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11 changes: 6 additions & 5 deletions R/converters.R
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Original file line number Diff line number Diff line change
Expand Up @@ -158,10 +158,7 @@ bigSpectronauttoMSstatsFormat <- function(input_file, output_file_name,
#' Convert out-of-memory DIANN files to MSstats format.
#'
#' @inheritParams MSstatsPreprocessBig
#' @param MBR True if analysis was done with match between runs.
#' @param quantificationColumn Use 'FragmentQuantCorrected'(default) column for quantified intensities for DIANN 1.8.x.
#' Use 'FragmentQuantRaw' for quantified intensities for DIANN 1.9.x.
#' Use 'auto' for quantified intensities for DIANN 2.0+
#' @inheritParams MSstatsConvert::DIANNtoMSstatsFormat
#'
#' @export
#'
Expand All @@ -173,6 +170,9 @@ bigDIANNtoMSstatsFormat <- function(input_file,
backend,
MBR = TRUE,
quantificationColumn = "FragmentQuantCorrected",
global_qvalue_cutoff = 0.01,
qvalue_cutoff = 0.01,
pg_qvalue_cutoff = 0.01,
max_feature_count = 100,
filter_unique_peptides = FALSE,
aggregate_psms = FALSE,
Expand All @@ -186,7 +186,8 @@ bigDIANNtoMSstatsFormat <- function(input_file,
reduceBigDIANN(input_file,
paste0("reduce_output_", output_file_name),
MBR,
quantificationColumn)
quantificationColumn,
global_qvalue_cutoff, qvalue_cutoff, pg_qvalue_cutoff)
Comment on lines 186 to +190
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⚠️ Potential issue | 🟠 Major

Use file.path() for intermediate file path construction.

paste0("reduce_output_", output_file_name) will produce a broken path when output_file_name contains directory components (e.g., "results/output.csv" → "reduce_output_results/output.csv"). Both references (lines 187 and 194) should be fixed.

🐛 Proposed fix 
-  reduceBigDIANN(input_file, 
-                 paste0("reduce_output_", output_file_name),
+  intermediate_file <- file.path(dirname(output_file_name),
+                                 paste0("reduce_output_", basename(output_file_name)))
+  reduceBigDIANN(input_file, 
+                 intermediate_file,
                  MBR,
                  quantificationColumn,
                  global_qvalue_cutoff, qvalue_cutoff, pg_qvalue_cutoff)
  
   # Preprocess the cleaned data (feature selection, etc.)
   msstats_data <- MSstatsPreprocessBig(
-    paste0("reduce_output_", output_file_name),
+    intermediate_file,
     output_file_name, backend, max_feature_count,

Based on learnings: "In R converters across the MSstatsBig package, replace direct concatenation with file names by constructing intermediate file paths using file.path(dirname(output_file_name), paste0("prefix_", basename(output_file_name))). This ensures the intermediate file is created in the correct directory even when output_file_name contains directories."

📝 Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change
reduceBigDIANN(input_file,
paste0("reduce_output_", output_file_name),
MBR,
quantificationColumn)
quantificationColumn,
global_qvalue_cutoff, qvalue_cutoff, pg_qvalue_cutoff)
intermediate_file <- file.path(dirname(output_file_name),
paste0("reduce_output_", basename(output_file_name)))
reduceBigDIANN(input_file,
intermediate_file,
MBR,
quantificationColumn,
global_qvalue_cutoff, qvalue_cutoff, pg_qvalue_cutoff)
🤖 Prompt for AI Agents 
In `@R/converters.R` around lines 186 - 190, The intermediate output path is built
by concatenating strings which breaks when output_file_name contains
directories; update the calls around reduceBigDIANN to construct the path with
file.path(dirname(output_file_name), paste0("reduce_output_",
basename(output_file_name))) (and the analogous construct used at the other
occurrence on line ~194) so the intermediate file is created in the same
directory as output_file_name; change both references to use dirname(...) and
basename(...) wrapped with file.path(...) instead of paste0("reduce_output_",
output_file_name).


# Preprocess the cleaned data (feature selection, etc.)
msstats_data <- MSstatsPreprocessBig(
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22 changes: 19 additions & 3 deletions man/bigDIANNtoMSstatsFormat.Rd
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