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.
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softwaremassspectrometrypreprocessingproteomicsregression
4.00 score 4 scripts 221 downloadsAWAggregatorData - Attribute-Weighted Aggregation Data
The AWAggregatorData package contains the data associated with the AWAggregator R package. It includes two pre-trained random forest models, one incorporating the average coefficient of variation as a feature, and the other one not including it. It also contains the PSMs in Benchmark Set 1~3 derived from the psm.tsv output files generated by FragPipe, which are used to train the random forest models.
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experimentdatapackagetypedataexperimenthubmassspectrometrydataproteomedatapkg
4.00 score 5 scripts