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Abstract Shotgun sequencing is routinely employed to study bacteria in microbial communities. With the vast amount of shotgun sequencing reads generated in a metagenomic project, it is crucial to determine the microbial composition at the strain level. This study investigated 20 computational tools that attempt to infer bacterial strain genomes from shotgun reads. For the first time, we discussed the methodology behind these tools. We also systematically evaluated six novel-strain-targeting tools on the same datasets and found that BHap, mixtureS and StrainFinder performed better than other tools. Because the performance of the best tools is still suboptimal, we discussed future directions that may address the limitations.
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This content will become publicly available on December 1, 2026
Missing mate pairs reported as poly-G reads can confound analyses of rare members of microbial assemblages
Using sequence reads from shotgun metagenomic analyses in both cattle and sheep, we describe how failures in mate pairing on Illumina sequencing can interact with bioinformatics pipelines to give spurious patterns among rare components of a metagenomic sample. We identified several different shotgun metagenomic datasets from different animals and different laboratories where the two members of the read pair matched a viral database at very different frequencies. We traced this bias to a set of poly-G reads of high quality that resulted from failures in generating read pairs during library preparation. These results reinforce the need to remove poly-G-rich reads when quality filtering shotgun metagenomic data.
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- Award ID(s):
- 2241312
- PAR ID:
- 10659598
- Publisher / Repository:
- Ecological Genetics and Genomics
- Date Published:
- Journal Name:
- Ecological Genetics and Genomics
- Volume:
- 37
- Issue:
- C
- ISSN:
- 2405-9854
- Page Range / eLocation ID:
- 100399
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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