An overview of the implementation of alphabetr.

Abstract

(A) From the population of interest, multiple samples of 10–300 T cells are sorted into 96-well plates. This design allows for a given clone to be sampled in multiple wells. (B) Multiplex RT-PCR is used to create cDNA libraries of CDR3α and CDR3β from each well, and (C) high-throughput sequencing is used to recover the unpaired CDR3α and CDR3β sequences of the clones sampled in each well. (D)(i) A random subset of the wells is chosen, (ii) association scores between every unique α and β found across the wells within this sample are calculated, and (iii) the set of unique αβ pairs that maximises the sum of association scores is identified using the Hungarian algorithm [39]. Step (iii) is illustrated for a particular set of CDR3α and CDR3β recovered from one well, as a matrix of association scores calculated across all wells in the subsample. (E) Steps D(i)-(iii) are repeated to generate a consensus list of pairs, filtering out candidates that appear rarely across replicates. (F) The frequencies of each remaining candidate αβ pair within the parent population are estimated using a maximum-likelihood approach, assuming only sharing (no dual TCR). Dual TCRα clones α1 α2 β1 are then distinguished from clones apparently sharing a TCRβ chain (α1 β1 and α2 β1), by examining the patterns of co-occurrences of the three chains, and the frequencies of these clones are re-calculated. (G) The output of the algorithm is a list of single and dual TCRα clones, each with their estimated frequency within the parent population. See text and Methods for more details.</p