NGSTroubleFinder: A tool for detection and quantification of contamination and kinship across human NGS data

Abstract

Quality control is a fundamental but often neglected step in any NGS pipeline. Detecting issues like cross-sample contamination and sample swaps is essential to control the data integrity. Here, we present NGSTroubleFinder, a novel python tool to detect cross-sample contamination in human Whole-Genome and Whole-Transcriptome Sequencing data, sample swaps and mismatches between the reported and the inferred genetic and transcriptomic sexes. NGSTroubleFinder is implemented in Python and incorporates a custom-built parallelized pileup engine written in C. The tool reports extensive information on the samples both in textual and HTML format including key plots for easy interpretation of the results. Availability and Implementation NGSTroubleFinder is written in Python and C, and it can be easily installed with pip. The tool source code and the models are freely available on github (https://github.com/STALICLA-RnD/NGSTroubleFinder) and a containerized version is available on dockerhub (https://hub.docker.com/r/staliclarnd/ngstroublefinder).

Competing Interest Statement

Authors are employees of STALICLA DDS.

Footnotes

* https://github.com/STALICLA-RnD/NGSTroubleFinder