Introduction | Overview of Package Functions | Overview of Package Data | Installation | Workflow Examples | Ex.1: Aggregate PSMs from FragPipe Using the Pre-Trained Model. | Ex.2: Aggregate PSMs from Proteome Discoverer Using the Pre-Trained Model. | Ex.3: Build a Merged Training Set and Retrain the Model. | Step 1: Load Spike-in Datasets | Step 2: Calculate PSM Attributes and Average Scaled Error of log~2~FC | Step 3: Merge Spike-in Datasets as a New Training Set | Step 4: Train a New Random Forest Model
Package: AWAggregator 1.3.0
Jiahua Tan
AWAggregator: Attribute-Weighted Aggregation
This package implements an attribute-weighted aggregation algorithm which leverages peptide-spectrum match (PSM) attributes to provide a more accurate estimate of protein abundance compared to conventional aggregation methods. This algorithm employs pre-trained random forest models to predict the quantitative inaccuracy of PSMs based on their attributes. PSMs are then aggregated to the protein level using a weighted average, taking the predicted inaccuracy into account. Additionally, the package allows users to construct their own training sets that are more relevant to their specific experimental conditions if desired.
Authors:
AWAggregator_1.3.0.tar.gz
AWAggregator_1.3.0.zip(r-4.7)AWAggregator_1.3.0.zip(r-4.6)AWAggregator_1.3.0.zip(r-4.5)
AWAggregator_1.3.0.tgz(r-4.6-any)AWAggregator_1.3.0.tgz(r-4.5-any)
AWAggregator_1.3.0.tar.gz(r-4.7-any)AWAggregator_1.3.0.tar.gz(r-4.6-any)
AWAggregator_1.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
AWAggregator/json (API)
| # Install 'AWAggregator' in R: |
| install.packages('AWAggregator', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tan-jiahua/awaggregator/issues
Datasets:
- sample.prot.PD - Sample Protein Data from Protein Discoverer
- sample.PSM.FP - Sample PSM Data from FragPipe
- sample.PSM.PD - Sample PSM Data from Proteome Discoverer
On BioConductor:AWAggregator-1.3.0(bioc 3.24)AWAggregator-1.2.0(bioc 3.23)
softwaremassspectrometrypreprocessingproteomicsregression
Last updated from:a4529421f0. Checks:1 WARNING, 9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | WARNING | 172 | ||
| linux-devel-x86_64 | OK | 643 | ||
| source / vignettes | OK | 357 | ||
| linux-release-x86_64 | OK | 316 | ||
| macos-release-arm64 | OK | 285 | ||
| macos-oldrel-arm64 | OK | 285 | ||
| windows-devel | OK | 274 | ||
| windows-release | OK | 415 | ||
| windows-oldrel | OK | 403 | ||
| wasm-release | OK | 125 |
Exports:aggregateByAttributesconvertPDFormatfitQuantInaccuracyModelgetAvgScaledErrorOfLog2FCgetDistMetricgetPSMAttributesmergeTrainingSets
Dependencies:clicpp11crayoncurldplyrgenericsgluehmsjsonlitelatticelifecyclemagrittrMatrixPeptidespillarpkgconfigpkgsearchprettyunitsprogresspurrrR6rangerRcppRcppEigenrlangstringistringrtibbletidyrtidyselecttoOrdinalutf8vctrswithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Aggregate PSMs to Protein Level | aggregateByAttributes |
| Convert Proteome Discoverer Output to Required Input Format | convertPDFormat |
| Fit a Random Forest Model | fitQuantInaccuracyModel |
| Get Average Scaled Error of log2FC for PSMs in a Spike-in Dataset | getAvgScaledErrorOfLog2FC |
| Get Distance Metric | getDistMetric |
| Get attributes for PSMs | getPSMAttributes |
| Merge Training Sets | mergeTrainingSets |
| Sample Protein Data from Protein Discoverer | sample.prot.PD |
| Sample PSM Data from FragPipe | sample.PSM.FP |
| Sample PSM Data from Proteome Discoverer | sample.PSM.PD |
