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Challenges in exome analysis by LifeScope and its alternative computational pipelines
BACKGROUND: Every next generation sequencing (NGS) platform relies on proprietary and open source computational tools to analyze sequencing data. NGS tools for Illumina platforms are well documented which is not the case with AB SOLiD systems. We applied several computational and variant calling pip...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4562342/ https://www.ncbi.nlm.nih.gov/pubmed/26346699 http://dx.doi.org/10.1186/s13104-015-1385-4 |
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author | Pranckevičiene, Erinija Rančelis, Tautvydas Pranculis, Aidas Kučinskas, Vaidutis |
author_facet | Pranckevičiene, Erinija Rančelis, Tautvydas Pranculis, Aidas Kučinskas, Vaidutis |
author_sort | Pranckevičiene, Erinija |
collection | PubMed |
description | BACKGROUND: Every next generation sequencing (NGS) platform relies on proprietary and open source computational tools to analyze sequencing data. NGS tools for Illumina platforms are well documented which is not the case with AB SOLiD systems. We applied several computational and variant calling pipelines to analyse targeted exome sequencing data obtained using AB SOLiD 5500 system. Our investigated tools comprised proprietary LifeScope’s pipeline in combination with open source color-space competent mapping programs and a variant caller. We present instrumental details of the pipelines that were used and quantitative comparative analysis of variant lists generated by LifeScope’s pipeline versus open source tools. RESULTS: Sufficient coverage of targeted regions was achieved by all investigated pipelines. High variability was observed in identities of variants across the mapping programs. We observed less than 50 % concordance of variant lists produced by approaches based on different mapping algorithms. We summarized different approaches with regards to coverage (DP) and quality (QUAL) properties of the variants provided by GATK and found that LifeScope’s computational pipeline is superior. Fusion of information on mapping profiles (pileup) at genomic positions of variants in several different alignments proved to be a useful strategy to assess questionable singleton variants. CONCLUSIONS: We quantitatively supported a conclusion that Lifescope’s pipeline is superior for processing sequencing data obtained by AB SOLiD 5500 system. Nevertheless the use of alternative pipelines is encouraged because aggregation of information from other mapping and variant calling approaches helps to resolve questionable calls and increases the confidence of the call. It was noted that a coverage threshold for variant to be considered for further analysis has to be chosen in data-driven way to prevent a loss of important information. |
format | Online Article Text |
id | pubmed-4562342 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-45623422015-09-09 Challenges in exome analysis by LifeScope and its alternative computational pipelines Pranckevičiene, Erinija Rančelis, Tautvydas Pranculis, Aidas Kučinskas, Vaidutis BMC Res Notes Research Article BACKGROUND: Every next generation sequencing (NGS) platform relies on proprietary and open source computational tools to analyze sequencing data. NGS tools for Illumina platforms are well documented which is not the case with AB SOLiD systems. We applied several computational and variant calling pipelines to analyse targeted exome sequencing data obtained using AB SOLiD 5500 system. Our investigated tools comprised proprietary LifeScope’s pipeline in combination with open source color-space competent mapping programs and a variant caller. We present instrumental details of the pipelines that were used and quantitative comparative analysis of variant lists generated by LifeScope’s pipeline versus open source tools. RESULTS: Sufficient coverage of targeted regions was achieved by all investigated pipelines. High variability was observed in identities of variants across the mapping programs. We observed less than 50 % concordance of variant lists produced by approaches based on different mapping algorithms. We summarized different approaches with regards to coverage (DP) and quality (QUAL) properties of the variants provided by GATK and found that LifeScope’s computational pipeline is superior. Fusion of information on mapping profiles (pileup) at genomic positions of variants in several different alignments proved to be a useful strategy to assess questionable singleton variants. CONCLUSIONS: We quantitatively supported a conclusion that Lifescope’s pipeline is superior for processing sequencing data obtained by AB SOLiD 5500 system. Nevertheless the use of alternative pipelines is encouraged because aggregation of information from other mapping and variant calling approaches helps to resolve questionable calls and increases the confidence of the call. It was noted that a coverage threshold for variant to be considered for further analysis has to be chosen in data-driven way to prevent a loss of important information. BioMed Central 2015-09-07 /pmc/articles/PMC4562342/ /pubmed/26346699 http://dx.doi.org/10.1186/s13104-015-1385-4 Text en © Pranckevičiene et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Pranckevičiene, Erinija Rančelis, Tautvydas Pranculis, Aidas Kučinskas, Vaidutis Challenges in exome analysis by LifeScope and its alternative computational pipelines |
title | Challenges in exome analysis by LifeScope and its alternative computational pipelines |
title_full | Challenges in exome analysis by LifeScope and its alternative computational pipelines |
title_fullStr | Challenges in exome analysis by LifeScope and its alternative computational pipelines |
title_full_unstemmed | Challenges in exome analysis by LifeScope and its alternative computational pipelines |
title_short | Challenges in exome analysis by LifeScope and its alternative computational pipelines |
title_sort | challenges in exome analysis by lifescope and its alternative computational pipelines |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4562342/ https://www.ncbi.nlm.nih.gov/pubmed/26346699 http://dx.doi.org/10.1186/s13104-015-1385-4 |
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