DNAp: A Pipeline for DNA-seq Data Analysis

Causey, Jason; Ashby, Cody; Walker, Karl; Wang, Zhiping Paul; Yang, Mary Qu; Guan, Yuanfang; Moore, Jason H.; Huang, Xiuzhen

doi:10.1038/s41598-018-25022-6

Cited by 17 publications

(14 citation statements)

References 25 publications

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“…Improved sequencing techniques and bioinformatics pipelines may, however, improve efficiency of WES and whole-genome sequencing for use in routine clinical practice over the next few years. 45…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of a Targeted Next-Generation Sequencing Gene Panel for Children With Neuroinflammation

et al. 2019

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IMPORTANCE Neuroinflammatory disorders are a range of severe neurological disorders causing brain and spinal inflammation and are now increasingly recognized in the pediatric population. They are often characterized by marked genotypic and phenotypic heterogeneity, complicating diagnostic work in clinical practice and molecular diagnosis. OBJECTIVE To develop and evaluate a next-generation sequencing panel targeting genes causing neuroinflammation or mimicking neuroinflammation. DESIGN, SETTING, AND PARTICIPANTS Cohort study in which a total of 257 genes associated with monogenic neuroinflammation and/or cerebral vasculopathy, including monogenic noninflammatory diseases mimicking these entities, were selected. A customized enrichment capture array, the neuroinflammation gene panel (NIP), was created. Targeted high-coverage sequencing was applied to DNA samples taken from eligible patients referred to Great Ormond Street Hospital in London,

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Section: Discussionmentioning

confidence: 99%

Development and Validation of a Targeted Next-Generation Sequencing Gene Panel for Children With Neuroinflammation

et al. 2019

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“…However, no objectively evaluated WGS QC pipeline had been developed until very recently 11 , and this pipeline did not utilize duplicate samples in determining QC filter thresholds or to prioritize filters based on efficacy, and it only considered biallelic variants. WGS studies typically use at least one hard filter based on output parameters from variant calling, but the exact filters and threshold values employed are often arbitrary or not empirically determined 12–14 . In previous studies, multiallelic (non-biallelic) variants were systematically removed in QC steps prior to downstream analysis 11,15,16 , as they were broadly deemed low in quality.…”

Section: Introductionmentioning

confidence: 99%

Empirical design of a variant quality control pipeline for whole genome sequencing data using replicate discordance

Adelson

Renton

et al. 2019

Sci Rep

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The success of next-generation sequencing depends on the accuracy of variant calls. Few objective protocols exist for QC following variant calling from whole genome sequencing (WGS) data. After applying QC filtering based on Genome Analysis Tool Kit (GATK) best practices, we used genotype discordance of eight samples that were sequenced twice each to evaluate the proportion of potentially inaccurate variant calls. We designed a QC pipeline involving hard filters to improve replicate genotype concordance, which indicates improved accuracy of genotype calls. Our pipeline analyzes the efficacy of each filtering step. We initially applied this strategy to well-characterized variants from the ClinVar database, and subsequently to the full WGS dataset. The genome-wide biallelic pipeline removed 82.11% of discordant and 14.89% of concordant genotypes, and improved the concordance rate from 98.53% to 99.69%. The variant-level read depth filter most improved the genome-wide biallelic concordance rate. We also adapted this pipeline for triallelic sites, given the increasing proportion of multiallelic sites as sample sizes increase. For triallelic sites containing only SNVs, the concordance rate improved from 97.68% to 99.80%. Our QC pipeline removes many potentially false positive calls that pass in GATK, and may inform future WGS studies prior to variant effect analysis.

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“…However, standalone pipelines are mostly applied in the high-performance computing environments (HPC). In this study, we have selected and evaluated eleven different WGS and WES pipelines of all three different types, which includes DNAp (Causey et al, 2018), STORMseq (Karczewski et al, 2014), ExScaliburn (Bao et al, 2015), Atlas2 (Evani et al, 2012), MC-GenomeKey (Elshazly et al, 2016), Simplex (Fischer et al, 2012), Whole Exome sequencing Pipeline web tool (WEP) (D'Antonio et al, 2013), SeqBench (Dander et al, 2014), VDAP-GUI (Menon et al, 2016), and fastq2vcf (Gao, Xu & Starmer, 2015).…”

Section: Pipelines For Wgs and Wes Data Processing And Variant Callingmentioning

confidence: 99%

Genomics pipelines to investigate susceptibility in whole genome and exome sequenced data for variant discovery, annotation, prediction and genotyping

Ahmed

Renart

Zeeshan

2021

PeerJ

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Over the last few decades, genomics is leading toward audacious future, and has been changing our views about conducting biomedical research, studying diseases, and understanding diversity in our society across the human species. The whole genome and exome sequencing (WGS/WES) are two of the most popular next-generation sequencing (NGS) methodologies that are currently being used to detect genetic variations of clinical significance. Investigating WGS/WES data for the variant discovery and genotyping is based on the nexus of different data analytic applications. Although several bioinformatics applications have been developed, and many of those are freely available and published. Timely finding and interpreting genetic variants are still challenging tasks among diagnostic laboratories and clinicians. In this study, we are interested in understanding, evaluating, and reporting the current state of solutions available to process the NGS data of variable lengths and types for the identification of variants, alleles, and haplotypes. Residing within the scope, we consulted high quality peer reviewed literature published in last 10 years. We were focused on the standalone and networked bioinformatics applications proposed to efficiently process WGS and WES data, and support downstream analysis for gene-variant discovery, annotation, prediction, and interpretation. We have discussed our findings in this manuscript, which include but not are limited to the set of operations, workflow, data handling, involved tools, technologies and algorithms and limitations of the assessed applications.

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DNAp: A Pipeline for DNA-seq Data Analysis

Cited by 17 publications

References 25 publications

Development and Validation of a Targeted Next-Generation Sequencing Gene Panel for Children With Neuroinflammation

Development and Validation of a Targeted Next-Generation Sequencing Gene Panel for Children With Neuroinflammation

Empirical design of a variant quality control pipeline for whole genome sequencing data using replicate discordance

Genomics pipelines to investigate susceptibility in whole genome and exome sequenced data for variant discovery, annotation, prediction and genotyping

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