Exploiting antigen receptor information to quantify index switching in single-cell transcriptome sequencing experiments

PLoS One. 2018 Dec 5;13(12):e0208484. doi: 10.1371/journal.pone.0208484. eCollection 2018.


By offering high sequencing speed and ultra-high-throughput at a low price, Illumina next-generation sequencing platforms have been widely adopted in recent years. However, an experiment with multiplexed library could be at risk of molecular recombination, known as "index switching", which causes a proportion of the reads to be assigned to an incorrect sample. It is reported that a new advance, exclusion amplification (ExAmp) in conjunction with the patterned flow cell technology introduced on HiSeq 3000/HiSeq 4000/HiSeq X sequencing systems, potentially suffers from a higher rate of index switching than conventional bridge amplification. We took advantage of the diverse but highly cell-specific expression of antigen receptors on immune cells to quantify index switching on single cell RNA-seq data that were sequenced on HiSeq 3000 and HiSeq 4000. By utilizing the unique antigen receptor expression, we could quantify the spread-of-signal from many different wells (n = 55 from total of three batches) due to index switching. Based on full-length T cell receptor (TCR) sequences from all samples reconstructed by TraCeR and TCR gene expression quantified by Kallisto, we found index switching in all three batches of experiments investigated. The median percentage of incorrectly detected markers was estimated to be 3.9% (interquartile range (IQR): 1.7%-7.3%). We did not detect any consistent patterns of certain indices to be more prone to switching than others, suggesting that index switching is a stochastic process. Our results confirm that index switching is a problem that affects samples run in multiplexed libraries on Illumina HiSeq 3000 and HiSeq 4000 platforms.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Gene Expression Profiling / methods
  • Gene Expression Profiling / standards*
  • High-Throughput Nucleotide Sequencing / methods
  • High-Throughput Nucleotide Sequencing / standards
  • Humans
  • Receptors, Antigen / genetics*
  • Receptors, Antigen, B-Cell / genetics
  • Receptors, Antigen, T-Cell / genetics
  • Sequence Analysis, RNA / methods
  • Sequence Analysis, RNA / standards
  • Single-Cell Analysis / methods*


  • Receptors, Antigen
  • Receptors, Antigen, B-Cell
  • Receptors, Antigen, T-Cell

Grant support

This study was supported by grants from Stiftelsen Kristian Gerhard Jebsen (project SKGJ-MED-017) to S.W.Q, G.K.S., and L.A.W.; and the Research Council of Norway (project 179573/V40 through the Centre of Excellence funding scheme and project 233885) to S.W.Q., A.Z. and Y.Y.