  The collection of immunoglobulin genes in an individual's germline, which
gives rise to B cell receptors via recombination, is known to vary
significantly across individuals. In humans, for example, each individual has
only a fraction of the several hundred known V alleles. Furthermore, the
currently-accepted set of known V alleles is both incomplete (particularly for
non-European samples), and contains a significant number of spurious alleles.
The resulting uncertainty as to which immunoglobulin alleles are present in any
given sample results in inaccurate B cell receptor sequence annotations, and in
particular inaccurate inferred naive ancestors. In this paper we first show
that the currently widespread practice of aligning each sequence to its closest
match in the full set of IMGT alleles results in a very large number of
spurious 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 set
from deep sequencing data, and show that it improves upon existing methods by
making a detailed comparison on a variety of simulated and real data samples.
This new method has been integrated into the partis annotation and clonal
family inference package, available at https://github.com/psathyrella/partis,
and is run by default without affecting overall run time.
