QuantTB – a method to classify mixed Mycobacterium tuberculosis infections within whole genome sequencing data

摘要

Iterative multiple strain identification process in QuantTB for a mixed sample, where two strains are present, strain 1(red) and strain 2 (green). First, SNPs from the sample are compared against SNP sequences in the reference database to calculate a strain presence score for every genome in the database. The sample is represented as a pileup, where every circle represents an allele copy. Red circles indicate alleles unique to strain A, green indicates alleles unique to strain B, and blue indicates reference strain (blue). The database (top right) is an example matrix representation of a reference genome database. Each column represents a single SNP (unique position and variant), and each row represents a genome in the reference database with this SNP present (1) or absent (0). Strain presence scores are calculated for every genome in the reference database. The genome with the highest strain presence score ( ) is selected, in this case strain A (red). The SNPs associated with strain A are removed from the database and the input sample, along with additional reference alleles. In each subsequent iteration the scores are recalculated, allowing for the identification of additional strains, and the process continues until there are no more SNPs or a threshold has been reached