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2 changes: 1 addition & 1 deletion DESCRIPTION
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Expand Up @@ -14,7 +14,6 @@ License: Artistic-2.0
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.3
biocViews: MassSpectrometry, Proteomics, Software, DataImport, QualityControl
Depends:
R (>= 4.0)
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'utils_logging.R'
'utils_shared_peptides.R'
VignetteBuilder: knitr
Config/roxygen2/version: 8.0.0
6 changes: 5 additions & 1 deletion R/utils_documentation.R
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Expand Up @@ -5,7 +5,11 @@
#' @param removeFewMeasurements TRUE (default) will remove the features that have 1 or 2 measurements across runs.
#' @param useUniquePeptide TRUE (default) removes peptides that are assigned for more than one proteins.
#' We assume to use unique peptide for each protein.
#' @param summaryforMultipleRows max or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities. Default is max for label-free converters and sum for TMT converters.
#' @param summaryforMultipleRows max or sum - when multiple PSMs identify
#' the same feature within a single MS run (duplicate PSMs), use the
#' highest (max) or sum of the duplicate intensities. Default is max for
#' label-free converters and sum for TMT converters. Note that this parameter
#' does NOT control collapsing across fractions of the same biological mixture.
#' @param removeProtein_with1Feature TRUE will remove the proteins which have only 1 feature, which is the combination of peptide, precursor charge, fragment and charge. FALSE is default.
#' @param removeProtein_with1Peptide TRUE will remove the proteins which have only 1 peptide and charge. FALSE is default.
#' @param removeOxidationMpeptides TRUE will remove the peptides including 'oxidation (M)' in modification. FALSE is default.
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6 changes: 5 additions & 1 deletion man/DIAUmpiretoMSstatsFormat.Rd

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6 changes: 5 additions & 1 deletion man/FragPipetoMSstatsFormat.Rd

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1 change: 1 addition & 0 deletions man/MSstatsConvert.Rd

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6 changes: 5 additions & 1 deletion man/MaxQtoMSstatsFormat.Rd

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6 changes: 5 additions & 1 deletion man/MaxQtoMSstatsTMTFormat.Rd

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6 changes: 5 additions & 1 deletion man/MetamorpheusToMSstatsFormat.Rd

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6 changes: 5 additions & 1 deletion man/OpenMStoMSstatsFormat.Rd

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6 changes: 5 additions & 1 deletion man/OpenSWATHtoMSstatsFormat.Rd

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6 changes: 5 additions & 1 deletion man/PDtoMSstatsFormat.Rd

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6 changes: 5 additions & 1 deletion man/PDtoMSstatsTMTFormat.Rd

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6 changes: 5 additions & 1 deletion man/PhilosophertoMSstatsTMTFormat.Rd

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6 changes: 5 additions & 1 deletion man/ProgenesistoMSstatsFormat.Rd

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6 changes: 5 additions & 1 deletion man/ProteinProspectortoMSstatsTMTFormat.Rd

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6 changes: 5 additions & 1 deletion man/SpectroMinetoMSstatsTMTFormat.Rd

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6 changes: 5 additions & 1 deletion man/SpectronauttoMSstatsFormat.Rd

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8 changes: 4 additions & 4 deletions man/dot-getFullDesign.Rd

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6 changes: 5 additions & 1 deletion man/dot-sharedParametersAmongConverters.Rd

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30 changes: 23 additions & 7 deletions vignettes/msstats_data_format.Rmd
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Expand Up @@ -304,13 +304,29 @@ should consists of elements named

# Fractions and balanced design

Finally, after preprocessing, `MSstatsBalancedDesign` function can be applied to
handle fractions and create balanced design.
For label-free and SRM data, it means that fractionation or technical replicates will be detected if these information is not provided. Features measured in multiple fractions (overlapped) will be assigned to a unique fraction. Then, the data will be adjusted so that within each fraction, every feature has a row for certain run. If the intensity value is missing, it will be denoted by `NA`.

For TMT data, a unique fraction will be selected for each overlapped feature and the
data will adjusted so that within each run, every feature has a row for each channel.
If the intensity is missing for a channel, it will be denoted by `NA`.
Finally, after preprocessing, the `MSstatsBalancedDesign` function can be
applied to handle fractions and create a balanced design.

For label-free data, fractionation or technical replicates are
detected if this information is not provided. Features that overlap
across multiple fractions of the same sample are assigned to a single
fraction by the following rule: for each feature, the fraction with the
**largest number of MS runs containing a non-missing measurement** is
kept. If multiple fractions tie on that count, the tie is broken by
choosing the fraction with the **highest mean intensity**. The
remaining fractions' rows for that feature are dropped. The data are
then adjusted so that within each fraction, every feature has a row
for each run. If the intensity value is missing, it is denoted by `NA`.

For TMT data, a unique fraction is selected for each overlapped feature
as well. After fraction selection, the data are adjusted so
that within each run, every feature has a row for each channel. If
the intensity is missing for a channel, it is denoted by `NA`.

Note also that this fraction-collapsing logic is distinct from the
`summaryforMultipleRows` argument on each converter, which only
combines duplicate PSMs identifying the same feature within a single
MS run.

```{r }
maxquant_balanced = MSstatsBalancedDesign(maxquant_processed, feature_columns)
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