MinorityReport, software for generalized analysis of causal genetic variants

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Background: The widespread availability of next generation genome sequencing technologies has enabled a wide range of variant detection applications, especially in cancer and inborn genetic disorders. For model systems and microorganisms, the same technology may be used to discover the causative mutations for any phenotype, including those generated in response to chemical perturbation. In the case of pathogenic organisms, these approaches have allowed the determination of drug targets by means of resistance selection followed by genome sequencing. Results: MinorityReport is open source software written in python that facilitates the comparison of any two sets of genome alignments for the purpose of rapidly identifying the spectrum of nonsynonymous changes, insertions or deletions, and copy number variations in a presumed mutant relative to its parent. Specifically, MinorityReport relates mapped sequence reads in SAM format output from any alignment tool for both the mutant and parent genome, relative to a reference genome, and produces the set of variants that distinguishes the mutant from the parent, all presented in an intuitive, straightforward report format. MinorityReport features tunable parameters for evaluating evidence and a scoring system that prioritizes reported variants based on relative proportions of read counts supporting the variant in the mutant versus parent data sets. The utility of MinorityReport is demonstrated using previously published publicly available data sets to find the determinants of resistance for novel anti-malarial drugs. Conclusions: MinorityReport is readily available (github: JeremyHorst/MinorityReport) to identify the genetic mechanisms of drug resistance in Plasmodium, genotype-phenotype relationships in human diads, or genomic variations between any two related organisms.




Horst, J. A., Wu, W., & Derisi, J. L. (2017). MinorityReport, software for generalized analysis of causal genetic variants. Malaria Journal, 16(1). https://doi.org/10.1186/s12936-017-1730-2

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