Characterization and remediation of sample index swaps by non-redundant dual indexing on massively parallel sequencing platforms.
BMC Genomics
; 19(1): 332, 2018 May 08.
Article
em En
| MEDLINE
| ID: mdl-29739332
ABSTRACT
BACKGROUND:
Here we present an in-depth characterization of the mechanism of sequencer-induced sample contamination due to the phenomenon of index swapping that impacts Illumina sequencers employing patterned flow cells with Exclusion Amplification (ExAmp) chemistry (HiSeqX, HiSeq4000, and NovaSeq). We also present a remediation method that minimizes the impact of such swaps.RESULTS:
Leveraging data collected over a two-year period, we demonstrate the widespread prevalence of index swapping in patterned flow cell data. We calculate mean swap rates across multiple sample preparation methods and sequencer models, demonstrating that different library methods can have vastly different swapping rates and that even non-ExAmp chemistry instruments display trace levels of index swapping. We provide methods for eliminating sample data cross contamination by utilizing non-redundant dual indexing for complete filtering of index swapped reads, and share the sequences for 96 non-combinatorial dual indexes we have validated across various library preparation methods and sequencer models. Finally, using computational methods we provide a greater insight into the mechanism of index swapping.CONCLUSIONS:
Index swapping in pooled libraries is a prevalent phenomenon that we observe at a rate of 0.2 to 6% in all sequencing runs on HiSeqX, HiSeq 4000/3000, and NovaSeq. Utilizing non-redundant dual indexing allows for the removal (flagging/filtering) of these swapped reads and eliminates swapping induced sample contamination, which is critical for sensitive applications such as RNA-seq, single cell, blood biopsy using circulating tumor DNA, or clinical sequencing.Palavras-chave
Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Análise de Sequência
/
Sequenciamento de Nucleotídeos em Larga Escala
Tipo de estudo:
Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
BMC Genomics
Assunto da revista:
GENETICA
Ano de publicação:
2018
Tipo de documento:
Article
País de afiliação:
Estados Unidos