diff --git a/.github/.DS_Store b/.github/.DS_Store new file mode 100644 index 0000000..a99cc2c Binary files /dev/null and b/.github/.DS_Store differ diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md new file mode 100644 index 0000000..d158d11 --- /dev/null +++ b/.github/pull_request_template.md @@ -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 diff --git a/.github/workflows/dry-run-build.yml b/.github/workflows/dry-run-build.yml new file mode 100644 index 0000000..0fa6255 --- /dev/null +++ b/.github/workflows/dry-run-build.yml @@ -0,0 +1,19 @@ +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 + diff --git a/R/clean_DIANN.R b/R/clean_DIANN.R index 77ea3e4..9aca175 100644 --- a/R/clean_DIANN.R +++ b/R/clean_DIANN.R @@ -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 diff --git a/R/converters.R b/R/converters.R index 799d768..e9ff703 100644 --- a/R/converters.R +++ b/R/converters.R @@ -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 #' @@ -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, @@ -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) # Preprocess the cleaned data (feature selection, etc.) msstats_data <- MSstatsPreprocessBig( diff --git a/man/bigDIANNtoMSstatsFormat.Rd b/man/bigDIANNtoMSstatsFormat.Rd index 0f14cfc..244d6b9 100644 --- a/man/bigDIANNtoMSstatsFormat.Rd +++ b/man/bigDIANNtoMSstatsFormat.Rd @@ -10,6 +10,9 @@ bigDIANNtoMSstatsFormat( 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, @@ -28,11 +31,24 @@ bigDIANNtoMSstatsFormat( \item{backend}{"arrow" or "sparklyr". Option "sparklyr" requires a spark installation and connection to spark instance provided in the `connection` parameter.} -\item{MBR}{True if analysis was done with match between runs.} +\item{MBR}{True if analysis was done with match between runs} \item{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+} +Use 'FragmentQuantRaw' for quantified intensities for DIANN 1.9.x. +Use 'auto' for quantified intensities for DIANN 2.x where each fragment intensity is a separate column, e.g. Fr0Quantity.} + +\item{global_qvalue_cutoff}{The qvalue cutoff for the Q.Value column, i.e. +the run-specific precursor q-value. Default is 0.01.} + +\item{qvalue_cutoff}{If MBR is false, the qvalue cutoff for the Global.Q.Value +column, i.e. global precursor q-value. If MBR is true, the qvalue cutoff for the +Lib.Q.Value column, i.e. the q-value for the library created after the first MBR pass. +Default is 0.01.} + +\item{pg_qvalue_cutoff}{If MBR is false, the qvalue cutoff for the Global.PG.Q.Value +column, i.e. the global q-value for the protein group. If MBR is true, the +qvalue cutoff for the Lib.PG.Q.Value column, i.e. the protein group q-value for +the library created after the first MBR pass. Default is 0.01.} \item{max_feature_count}{maximum number of features per protein. Features will be selected based on highest average intensity.}