ArticleBMC research notes2015
Challenges in exome analysis by LifeScope and its alternative computational pipelines.
Article in BMC research notes, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A common pathomechanism in GMAP-210- and LBR-related diseases.JCI insight · 2018Article
- Analysis of selected genes associated with cardiomyopathy by next-generation sequencing.Journal of clinical laboratory analysis · 2018Article
- Analysis of pathogenic variants from the ClinVar database in healthy people using next-generation sequencing.Genetics research · 2017Article
- Evaluating the Calling Performance of a Rare Disease NGS Panel for Single Nucleotide and Copy Number Variants.Molecular diagnosis & therapy · 2017Article
- Predicting Species-Resolved Macronutrient Acquisition during Succession in a Model Phototrophic Biofilm Using an Integrated 'Omics Approach.Frontiers in microbiology · 2017Article
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4 authors.
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Abstract
backgroundEvery 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.
resultsSufficient 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.
conclusionsWe 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.
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