Eliminates biases inherent in raw unique molecular identifier (UMI) counts and produces unbiased and low-noise measurements of transcript abundance. TRUmiCount is able to perform comparisons between different genes, exons, and others genomic features. This algorithm exploits the tree-step bias-correction and phantom-removal in expected read counts. It aims to increase the accuracy of quantitative applications of next generation sequencing (NGS) and can to be used in conjunction with the UMI-tools software.
Center for Integrative Bioinformatics Vienna (CIBIV), Vienna, Austria; Joint Institute of the University of Vienna and Medical University of Vienna, Max F. Perutz Laboratories (MFPL), Vienna, Austria; Bioinformatics and Computational Biology, Faculty of Computer Science, University of Vienna, Vienna, Austria
TRUmiCount funding source(s)
Supported by the Austrian Science Fund (FWF): W1207-B09.