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The collection of immunoglobulin genes in an individual's germline, whichgives rise to B cell receptors via recombination, is known to varysignificantly across individuals. In humans, for example, each individual hasonly a fraction of the several hundred known V alleles. Furthermore, thecurrently-accepted set of known V alleles is both incomplete (particularly fornon-European samples), and contains a significant number of spurious alleles.The resulting uncertainty as to which immunoglobulin alleles are present in anygiven sample results in inaccurate B cell receptor sequence annotations, and inparticular inaccurate inferred naive ancestors. In this paper we first showthat the currently widespread practice of aligning each sequence to its closestmatch in the full set of IMGT alleles results in a very large number ofspurious alleles that are not in the sample's true set of germline V alleles.We then describe a new method for inferring each individual's germline gene setfrom deep sequencing data, and show that it improves upon existing methods bymaking a detailed comparison on a variety of simulated and real data samples.This new method has been integrated into the partis annotation and clonalfamily inference package, available at https://github.com/psathyrella/partis,and is run by default without affecting overall run time.

Per-sample immunoglobulin germline inference from B cell receptor deep sequencing data