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Validation of StrainIQ software performance using metagenomic data from ATCC staggered mix genomes

<p>StrainIQ (Strain Identification and Quantification) is a novel tool that implements a new&nbsp;<em>n</em>-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.&nbsp;Here, the&nbsp;gut_mix.zip file contains the&nbsp;metagenomic sequence data&nbsp;from the ATCC 20 strain staggered genomic mix&nbsp;(MSA-1003). From this original sequencing sequence (nearly 120X), we created additional datasets with 90X, 60X, 30X, 5X, 3X, and 1X coverage&nbsp;and tested StrainIQ performance on&nbsp;those varying sequencing datasets.</p> <p>Please find the&nbsp;new link for this data at https://zenodo.org/record/8132164</p>

ShareScore

24/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
16
Reuse readiness
0
Engagement
0

Dataset details

Repository
zenodo
Published
March 30, 2023
License
cc-by-4.0
DOI
10.5281/zenodo.7789970

Scored with release 0.9.0

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