Triqler (TRansparent Identification-Quantification-linked Error Rates) integrates identification and quantification error rates for protein quantification into a single probabilistic model. This avoids several pitfalls in error reporting and error propagation that frequently arise when several separate thresholds are employed. Triqler manages to discover more significantly differentially abundant proteins than previously published pipelines and at the same time controls the quantification false discovery rate.
Triqler is a Python package and can be installed easily using pip. Examples and installation guides are available on the GitHub page.
Github: https://github.com/statisticalbiotechnology/triqler
Publication: The, M., Käll, L. (2018). “Integrated identification and quantification error probabilities for shotgun proteomics.” Molecular & Cellular Proteomics, mcp-RA118.
