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Performance evaluation method for read mapping tool in clinical panel sequencing.

ABSTRACT: In addition to the rapid advancement in Next-Generation Sequencing (NGS) technology, clinical panel sequencing is being used increasingly in clinical studies and tests. However, tools that are used in NGS data analysis have not been comparatively evaluated in performance for panel sequencing. This study aimed to evaluate the tools used in the alignment process, the first procedure in bioinformatics analysis, by comparing tools that have been widely used with ones that have been introduced recently. With the accumulated panel sequencing data, detected variant lists were cataloged and inserted into simulated reads produced from the reference genome (h19). The amount of unmapped reads and misaligned reads, mapping quality distribution, and runtime were measured as standards for comparison. As the most widely used tools, Bowtie2 and BWA-MEM each showed explicit performance with AUC of 0.9984 and 0.9970 respectively. Kart, maintaining superior runtime and less number of misaligned read, also similarly possessed high level of AUC (0.9723). Such selection and optimization method of tools appropriate for panel sequencing can be utilized for fields requiring error minimization, such as clinical application and liquid biopsy studies.

SUBMITTER: Lee H

PROVIDER: S-EPMC5846869 | biostudies-other | 2018

REPOSITORIES: biostudies-other

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Performance evaluation method for read mapping tool in clinical panel sequencing.

Lee Hojun H Lee Ki-Wook KW Lee Taeseob T Park Donghyun D Chung Jongsuk J Lee Chung C Park Woong-Yang WY Son Dae-Soon DS

Genes & genomics 20171109 2

In addition to the rapid advancement in Next-Generation Sequencing (NGS) technology, clinical panel sequencing is being used increasingly in clinical studies and tests. However, tools that are used in NGS data analysis have not been comparatively evaluated in performance for panel sequencing. This study aimed to evaluate the tools used in the alignment process, the first procedure in bioinformatics analysis, by comparing tools that have been widely used with ones that have been introduced recent ...[more]

PMID: 29568413

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Project description:A long-standing challenge in human microbiome research is achieving the taxonomic and functional resolution needed to generate testable hypotheses about the gut microbiota's impact on health and disease. With a growing number of live microbial interventions in clinical development, this challenge is renewed by a need to understand the pharmacokinetics and pharmacodynamics of therapeutic candidates. While short-read sequencing of the bacterial 16S rRNA gene has been the standard for microbiota profiling, recent improvements in the fidelity of long-read sequencing underscores the need for a re-evaluation of the value of distinct microbiome-sequencing approaches. We leveraged samples from participants enrolled in a phase 1b clinical trial of a novel live biotherapeutic product to perform a comparative analysis of short-read and long-read amplicon and metagenomic sequencing approaches to assess their utility for generating clinical microbiome data. Across all methods, overall community taxonomic profiles were comparable and relationships between samples were conserved. Comparison of ubiquitous short-read 16S rRNA amplicon profiling to long-read profiling of the 16S-ITS-23S rRNA amplicon showed that only the latter provided strain-level community resolution and insight into novel taxa. All methods identified an active ingredient strain in treated study participants, though detection confidence was higher for long-read methods. Read coverage from both metagenomic methods provided evidence of active-ingredient strain replication in some treated participants. Compared to short-read metagenomics, approximately twice the proportion of long reads were assigned functional annotations. Finally, compositionally similar bacterial metagenome-assembled genomes (MAGs) were recovered from short-read and long-read metagenomic methods, although a greater number and more complete MAGs were recovered from long reads. Despite higher costs, both amplicon and metagenomic long-read approaches yielded added microbiome data value in the form of higher confidence taxonomic and functional resolution and improved recovery of microbial genomes compared to traditional short-read methodologies.

Dataset Information

Performance evaluation method for read mapping tool in clinical panel sequencing.

Publications

Performance evaluation method for read mapping tool in clinical panel sequencing.

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