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: TRUmiCount uses a mechanistic model of PCR amplification to correct
for both types of errors. In our paper (see below) we demonstrate that the
phantom-filtered and loss-corrected molecule counts computed by TRUmiCount
measure the true number of molecules with considerably higher accuracy than the
raw number of distinct UMIs.
TRUmiCount is available on the Bioconda channel of the Conda package manager.
conda install -c bioconda trumicount
See https://cibiv.github.io/trumicount for detailes on the installation & usage of TRUmiCount.
The TRUmiCount algorithmus and our model of PCR amplification and sequencing is described in details 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.
TRUmiCount 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.
TRUmiCount 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.