Dataset Information

Reliability of genomic variants across different next-generation sequencing platforms and bioinformatic processing pipelines.

ABSTRACT:

Background

Next Generation Sequencing (NGS) is the fundament of various studies, providing insights into questions from biology and medicine. Nevertheless, integrating data from different experimental backgrounds can introduce strong biases. In order to methodically investigate the magnitude of systematic errors in single nucleotide variant calls, we performed a cross-sectional observational study on a genomic cohort of 99 subjects each sequenced via (i) Illumina HiSeq X, (ii) Illumina HiSeq, and (iii) Complete Genomics and processed with the respective bioinformatic pipeline. We also repeated variant calling for the Illumina cohorts with GATK, which allowed us to investigate the effect of the bioinformatics analysis strategy separately from the sequencing platform's impact.

Results

The number of detected variants/variant classes per individual was highly dependent on the experimental setup. We observed a statistically significant overrepresentation of variants uniquely called by a single setup, indicating potential systematic biases. Insertion/deletion polymorphisms (indels) were associated with decreased concordance compared to single nucleotide polymorphisms (SNPs). The discrepancies in indel absolute numbers were particularly prominent in introns, Alu elements, simple repeats, and regions with medium GC content. Notably, reprocessing sequencing data following the best practice recommendations of GATK considerably improved concordance between the respective setups.

Conclusion

We provide empirical evidence of systematic heterogeneity in variant calls between alternative experimental and data analysis setups. Furthermore, our results demonstrate the benefit of reprocessing genomic data with harmonized pipelines when integrating data from different studies.

SUBMITTER: Weißbach S

PROVIDER: S-EPMC7814447 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

Reliability of genomic variants across different next-generation sequencing platforms and bioinformatic processing pipelines.

Weißbach Stephan S Sys Stanislav S Hewel Charlotte C Todorov Hristo H Schweiger Susann S Winter Jennifer J Pfenninger Markus M Torkamani Ali A Evans Doug D Burger Joachim J Everschor-Sitte Karin K May-Simera Helen Louise HL Gerber Susanne S

BMC genomics 20210119 1

<h4>Background</h4>Next Generation Sequencing (NGS) is the fundament of various studies, providing insights into questions from biology and medicine. Nevertheless, integrating data from different experimental backgrounds can introduce strong biases. In order to methodically investigate the magnitude of systematic errors in single nucleotide variant calls, we performed a cross-sectional observational study on a genomic cohort of 99 subjects each sequenced via (i) Illumina HiSeq X, (ii) Illumina H ...[more]

PMID: 33468057

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Dataset Information

Reliability of genomic variants across different next-generation sequencing platforms and bioinformatic processing pipelines.

Background

Results

Conclusion

Publications

Reliability of genomic variants across different next-generation sequencing platforms and bioinformatic processing pipelines.

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