ArticleBMC genomics2012
The effect of strand bias in Illumina short-read sequencing data.
Article in BMC genomics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers.
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Who cites it
73 citing papers in PubMed.
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- Genomic reproducibility in the bioinformatics era.Genome biology · 2024Review
- Improving rigor and reproducibility in chromatin immunoprecipitation assay data analysis workflows with Rocketchip.bioRxiv : the preprint server for biology · 2024Article
- CD59 gene: 143 haplotypes of 22,718 nucleotides length by computational phasing in 113 individuals from different ethnicities.Transfusion · 2024Article
- Analysis of somatic mutations in whole blood from 200,618 individuals identifies pervasive positive selection and novel drivers of clonal hematopoiesis.Nature genetics · 2024Article
- Crykey: Rapid identification of SARS-CoV-2 cryptic mutations in wastewater.Nature communications · 2024Article
- High throughput AS LNA qPCR method for the detection of a specific mutation in poliovirus vaccine strains.Vaccine · 2024Article
- Detecting Somatic Mutations Without Matched Normal Samples Using Long Reads.bioRxiv : the preprint server for biology · 2024Article
- Crykey: Rapid Identification of SARS-CoV-2 Cryptic Mutations in Wastewater.medRxiv : the preprint server for health sciences · 2023Article
- Varying strength of selection contributes to the intragenomic diversity of rRNA genes.Nature communications · 2022Article
13 more citing papers are in PubMed but not listed here.
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6 authors.
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Abstract
backgroundWhen using Illumina high throughput short read data, sometimes the genotype inferred from the positive strand and negative strand are significantly different, with one homozygous and the other heterozygous. This phenomenon is known as strand bias. In this study, we used Illumina short-read sequencing data to evaluate the effect of strand bias on genotyping quality, and to explore the possible causes of strand bias.
resultWe collected 22 breast cancer samples from 22 patients and sequenced their exome using the Illumina GAIIx machine. By comparing the consistency between the genotypes inferred from this sequencing data with the genotypes inferred from SNP chip data, we found that, when using sequencing data, SNPs with extreme strand bias did not have significantly lower consistency rates compared to SNPs with low or no strand bias. However, this result may be limited by the small subset of SNPs present in both the exome sequencing and the SNP chip data. We further compared the transition and transversion ratio and the number of novel non-synonymous SNPs between the SNPs with low or no strand bias and those with extreme strand bias, and found that SNPs with low or no strand bias have better overall quality. We also discovered that the strand bias occurs randomly at genomic positions across these samples, and observed no consistent pattern of strand bias location across samples. By comparing results from two different aligners, BWA and Bowtie, we found very consistent strand bias patterns. Thus strand bias is unlikely to be caused by alignment artifacts. We successfully replicated our results using two additional independent datasets with different capturing methods and Illumina sequencers.
conclusionExtreme strand bias indicates a potential high false-positive rate for SNPs.
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