inferGenotype - Infer a subject-specific genotype


inferGenotype infers an subject’s genotype by finding the minimum number set of alleles that can explain the majority of each gene’s calls. The most common allele of each gene is included in the genotype first, and the next most common allele is added until the desired fraction of alleles can be explained. In this way, mistaken allele calls (resulting from sequences which by chance have been mutated to look like another allele) can be removed.


inferGenotype(clip_db, fraction_to_explain = 0.875, gene_cutoff = 1e-04,
find_unmutated = TRUE, germline_db = NA, novel_df = NA)


a data.frame containing V allele calls from a single subject under "V_CALL". If find_unmutated is TRUE, then the sample IMGT-gapped V(D)J sequence should be provided in a column "SEQUENCE_IMGT"
the portion of each gene that must be explained by the alleles that will be included in the genotype
either a number of sequences or a fraction of the length of allele_calls denoting the minimum number of times a gene must be observed in allele_calls to be included in the genotype
if TRUE, use germline_db to find which samples are unmutated. Not needed if allele_calls only represent unmutated samples.
named vector of sequences containing the germline sequences named in allele_calls. Only required if find_unmutated is TRUE.
an optional data.frame of the type novel returned by findNovelAlleles containing germline sequences that will be utilized if find_unmutated is TRUE. See details.


A table of alleles denoting the genotype of the subject


Allele calls representing cases where multiple alleles have been assigned to a single sample sequence are rare among unmutated sequences but may result if nucleotides for certain positions are not available. Calls containing multiple alleles are treated as belonging to all groups. If novel_df is provided, all sequences that are assigned to the same starting allele as any novel germline allele will have the novel germline allele appended to their assignent prior to searching for unmutated sequences.


This method works best with data derived from blood, where a large portion of sequences are expected to be unmutated. Ideally, there should be hundreds of allele calls per gene in the input.


# Infer the IGHV genotype, using only unmutated sequences, including any 
# novel alleles
inferGenotype(sample_db, find_unmutated = TRUE, germline_db = germline_ighv,
novel_df = novel_df)
1    IGHV1-2       02,04     664,302   966     
2    IGHV1-3          01         226   226     
3    IGHV1-8 01,02_G234T     467,370   837     
4   IGHV1-18          01        1005  1005     
5   IGHV1-24          01         105   105     
6   IGHV1-46          01         624   624     
7   IGHV1-58       01,02       23,18    41     
8   IGHV1-69    01,04,06 515,469,280  1279     
9 IGHV1-69-2          01          31    31     

See also

plotGenotype for a colorful visualization and genotypeFasta to convert the genotype to nucleotide sequences.