Validation of StrainIQ software performance using metagenomic data from ATCC staggered mix genomes
Authors/Creators
- 1. University of Nebraska Medical center, Omaha, NE 68198, USA
Description
StrainIQ (Strain Identification and Quantification) is a novel tool that implements a new n-gram based algorithm for predicting and quantifying strain-level taxa from whole genome metagenomic sequencing data. We tested our method using simulated (GI tract reference genomes) and mock metagenomic datasets (from ATCC microbial genomic mix) and compared its performance with existing methods. Here, the gut_mix.zip file contains the metagenomic sequence data from the ATCC 20 strain staggered genomic mix (MSA-1003). From this original sequencing sequence (nearly 120X), we created additional datasets with 90X, 60X, 30X, 5X, 3X, and 1X coverage and tested StrainIQ performance on those varying sequencing datasets.
Please find the new link for this data at https://zenodo.org/record/8132164