Motivation: Counting molecules using next-generation sequencing (NGS) suffers from PCR amplification bias, which reduces the accuracy of many quantitative NGS-based experimental methods such as RNA-Seq. This is true even if molecules are made distinguishable using unique molecular identifiers (UMIs) before PCR amplification, and distinct UMIs are counted instead of reads: Molecules that are lost entirely during the sequencing process will still cause under-estimation of the molecule count, and amplification artifacts like PCR chimeras create phantom UMIs and thus cause over-estimation.
Results: gwpcR implements mechanistic model of PCR amplification that allows correction of both types of errors. In our paper we demonstrate that the model describes UMI-based NGS experiments well, and that using it to filter phantoms and correct for lost molecules considerably increases the accuracy of measured molecule counts over just counting the number of distinct UMIs.
Using gwpcR: The easiest way to integrate our loss- and phantom-correction algorithm into your UMI pipeline is by using our command-line tool TRUmiCount (based on gwpcR of course). TRUmiCount integrates with UMI-Tools, and allows you to get from a BAM file containing mapped reads to a per-gene count table already corrected for sequencing errors, amplification artifacts and lost molecules with a single command.
Using gwpcR directly: If your pipeline is already R-based, you might want to integrate gwpcR directly instead of using our command-line tool TRUmiCount. After installing the gwpcR package, see help(gwpcrpois.est) and help(gwpcrpois.groupest).
If you're already using Conda, you can install TRUmiCount from the Bioconda channel by doing
conda install -c bioconda r-gwpcr
gwpcR can also be installed directly from this GitHub repository using R's devtools package.
install.packages("devtools")
devtools::install_github("Cibiv/gwpcR", ref="latest-release")
The implemented model is described in detail in our paper
Florian G. Pflug, Arndt von Haeseler. (2018). TRUmiCount: Correctly counting absolute numbers of molecules using unique molecular identifiers. Bioinformatics, DOI: https://doi.org/10.1093/bioinformatics/bty283.
gwpcR is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
gwpcR is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.