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Transcriptome Analysis of Single Cells
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Exploiting antigen receptor information to quantify index switching in single-cell transcriptome sequencing

Ying Yao1, Asima Zia1, Łukasz Wyrożemski2

  • 1Department of Immunology, Centre for Immune Regulation, University of Oslo, Oslo, Norway.

Plos One
|December 6, 2018
PubMed
Summary

Index switching, a problem in multiplexed libraries on Illumina HiSeq 3000/4000, leads to incorrect sample assignment. This study quantifies index switching in single-cell RNA-seq data, finding a median of 3.9% incorrectly assigned reads.

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Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Illumina next-generation sequencing platforms offer high throughput but can suffer from index switching in multiplexed libraries.
  • Index switching causes reads to be assigned to the wrong sample, impacting data accuracy.
  • Newer Illumina systems (HiSeq 3000/4000) using exclusion amplification (ExAmp) may have higher index switching rates.

Purpose of the Study:

  • To quantify the rate of index switching on Illumina HiSeq 3000 and HiSeq 4000 platforms using single-cell RNA-seq data.
  • To assess the impact of index switching on immune cell antigen receptor expression data.
  • To determine if index switching is a stochastic process or shows specific patterns.

Main Methods:

  • Utilized single-cell RNA-seq data from immune cells with known cell-specific antigen receptor expression.
  • Reconstructed full-length T cell receptor (TCR) sequences using TraCeR.
  • Quantified TCR gene expression using Kallisto to identify incorrectly assigned reads due to index switching.

Main Results:

  • Index switching was detected in all three experimental batches analyzed.
  • The median percentage of incorrectly detected markers (index switching) was 3.9% (IQR: 1.7%-7.3%).
  • No consistent patterns of specific indices being more prone to switching were observed, suggesting a stochastic process.

Conclusions:

  • Index switching is a significant issue affecting multiplexed library experiments on Illumina HiSeq 3000 and HiSeq 4000 platforms.
  • The stochastic nature of index switching necessitates careful data validation and potential bioinformatic correction.
  • Accurate quantification of index switching is crucial for reliable results in single-cell genomics studies.