PathoScope 2.0: A complete computational framework for strain identification in environmental or clinical sequencing samples

Changjin Hong, Solaiappan Manimaran, Ying Shen, Joseph F. Perez-Rogers, Allyson L. Byrd, Eduardo Castro-Nallar, Keith A. Crandall, William E. Johnson

Resultado de la investigación: Article

56 Citas (Scopus)

Resumen

Background: Recent innovations in sequencing technologies have provided researchers with the ability to rapidly characterize the microbial content of an environmental or clinical sample with unprecedented resolution. These approaches are producing a wealth of information that is providing novel insights into the microbial ecology of the environment and human health. However, these sequencing-based approaches produce large and complex datasets that require efficient and sensitive computational analysis workflows. Many recent tools for analyzing metagenomic-sequencing data have emerged, however, these approaches often suffer from issues of specificity, efficiency, and typically do not include a complete metagenomic analysis framework.Results: We present PathoScope 2.0, a complete bioinformatics framework for rapidly and accurately quantifying the proportions of reads from individual microbial strains present in metagenomic sequencing data from environmental or clinical samples. The pipeline performs all necessary computational analysis steps; including reference genome library extraction and indexing, read quality control and alignment, strain identification, and summarization and annotation of results. We rigorously evaluated PathoScope 2.0 using simulated data and data from the 2011 outbreak of Shiga-toxigenic Escherichia coli O104:H4.Conclusions: The results show that PathoScope 2.0 is a complete, highly sensitive, and efficient approach for metagenomic analysis that outperforms alternative approaches in scope, speed, and accuracy. The PathoScope 2.0 pipeline software is freely available for download at: http://sourceforge.net/projects/pathoscope/.

Idioma originalEnglish
Número de artículo33
PublicaciónMicrobiome
Volumen2
N.º1
DOI
EstadoPublished - 5 sep 2014

Huella dactilar

Metagenomics
Shiga-Toxigenic Escherichia coli
Genomic Library
Workflow
Ecology
Computational Biology
Quality Control
Disease Outbreaks
Software
Research Personnel
Technology
Health

ASJC Scopus subject areas

  • Microbiology
  • Microbiology (medical)

Citar esto

Hong, Changjin ; Manimaran, Solaiappan ; Shen, Ying ; Perez-Rogers, Joseph F. ; Byrd, Allyson L. ; Castro-Nallar, Eduardo ; Crandall, Keith A. ; Johnson, William E. / PathoScope 2.0 : A complete computational framework for strain identification in environmental or clinical sequencing samples. En: Microbiome. 2014 ; Vol. 2, N.º 1.
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abstract = "Background: Recent innovations in sequencing technologies have provided researchers with the ability to rapidly characterize the microbial content of an environmental or clinical sample with unprecedented resolution. These approaches are producing a wealth of information that is providing novel insights into the microbial ecology of the environment and human health. However, these sequencing-based approaches produce large and complex datasets that require efficient and sensitive computational analysis workflows. Many recent tools for analyzing metagenomic-sequencing data have emerged, however, these approaches often suffer from issues of specificity, efficiency, and typically do not include a complete metagenomic analysis framework.Results: We present PathoScope 2.0, a complete bioinformatics framework for rapidly and accurately quantifying the proportions of reads from individual microbial strains present in metagenomic sequencing data from environmental or clinical samples. The pipeline performs all necessary computational analysis steps; including reference genome library extraction and indexing, read quality control and alignment, strain identification, and summarization and annotation of results. We rigorously evaluated PathoScope 2.0 using simulated data and data from the 2011 outbreak of Shiga-toxigenic Escherichia coli O104:H4.Conclusions: The results show that PathoScope 2.0 is a complete, highly sensitive, and efficient approach for metagenomic analysis that outperforms alternative approaches in scope, speed, and accuracy. The PathoScope 2.0 pipeline software is freely available for download at: http://sourceforge.net/projects/pathoscope/.",
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PathoScope 2.0 : A complete computational framework for strain identification in environmental or clinical sequencing samples. / Hong, Changjin; Manimaran, Solaiappan; Shen, Ying; Perez-Rogers, Joseph F.; Byrd, Allyson L.; Castro-Nallar, Eduardo; Crandall, Keith A.; Johnson, William E.

En: Microbiome, Vol. 2, N.º 1, 33, 05.09.2014.

Resultado de la investigación: Article

TY - JOUR

T1 - PathoScope 2.0

T2 - A complete computational framework for strain identification in environmental or clinical sequencing samples

AU - Hong, Changjin

AU - Manimaran, Solaiappan

AU - Shen, Ying

AU - Perez-Rogers, Joseph F.

AU - Byrd, Allyson L.

AU - Castro-Nallar, Eduardo

AU - Crandall, Keith A.

AU - Johnson, William E.

PY - 2014/9/5

Y1 - 2014/9/5

N2 - Background: Recent innovations in sequencing technologies have provided researchers with the ability to rapidly characterize the microbial content of an environmental or clinical sample with unprecedented resolution. These approaches are producing a wealth of information that is providing novel insights into the microbial ecology of the environment and human health. However, these sequencing-based approaches produce large and complex datasets that require efficient and sensitive computational analysis workflows. Many recent tools for analyzing metagenomic-sequencing data have emerged, however, these approaches often suffer from issues of specificity, efficiency, and typically do not include a complete metagenomic analysis framework.Results: We present PathoScope 2.0, a complete bioinformatics framework for rapidly and accurately quantifying the proportions of reads from individual microbial strains present in metagenomic sequencing data from environmental or clinical samples. The pipeline performs all necessary computational analysis steps; including reference genome library extraction and indexing, read quality control and alignment, strain identification, and summarization and annotation of results. We rigorously evaluated PathoScope 2.0 using simulated data and data from the 2011 outbreak of Shiga-toxigenic Escherichia coli O104:H4.Conclusions: The results show that PathoScope 2.0 is a complete, highly sensitive, and efficient approach for metagenomic analysis that outperforms alternative approaches in scope, speed, and accuracy. The PathoScope 2.0 pipeline software is freely available for download at: http://sourceforge.net/projects/pathoscope/.

AB - Background: Recent innovations in sequencing technologies have provided researchers with the ability to rapidly characterize the microbial content of an environmental or clinical sample with unprecedented resolution. These approaches are producing a wealth of information that is providing novel insights into the microbial ecology of the environment and human health. However, these sequencing-based approaches produce large and complex datasets that require efficient and sensitive computational analysis workflows. Many recent tools for analyzing metagenomic-sequencing data have emerged, however, these approaches often suffer from issues of specificity, efficiency, and typically do not include a complete metagenomic analysis framework.Results: We present PathoScope 2.0, a complete bioinformatics framework for rapidly and accurately quantifying the proportions of reads from individual microbial strains present in metagenomic sequencing data from environmental or clinical samples. The pipeline performs all necessary computational analysis steps; including reference genome library extraction and indexing, read quality control and alignment, strain identification, and summarization and annotation of results. We rigorously evaluated PathoScope 2.0 using simulated data and data from the 2011 outbreak of Shiga-toxigenic Escherichia coli O104:H4.Conclusions: The results show that PathoScope 2.0 is a complete, highly sensitive, and efficient approach for metagenomic analysis that outperforms alternative approaches in scope, speed, and accuracy. The PathoScope 2.0 pipeline software is freely available for download at: http://sourceforge.net/projects/pathoscope/.

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