findNovelAlleles - Find novel alleles from repertoire sequencing data
findNovelAlleles analyzes mutation patterns in sequences thought to
align to each germline allele in order to determine which positions
might be polymorphic.
findNovelAlleles(data, germline_db, v_call = "V_CALL", germline_min = 200, min_seqs = 50, auto_mutrange = TRUE, mut_range = 1:10, pos_range = 1:312, y_intercept = 0.125, alpha = 0.05, j_max = 0.15, min_frac = 0.75, nproc = 1)
data.framein Change-O format. See details.
- a vector of named nucleotide germline sequences
matching the V calls in
- name of the column in
datawith V allele calls. Default is V_CALL.
- the minimum number of sequences that must have a particular germline allele call for the allele to be analyzed
- the minimum number of total sequences (within the desired mutational range and nucleotide range) required for the samples to be considered
TRUE, the algorithm will attempt to determine the appropriate mutation range automatically using the mutation count of the most common sequence assigned to each allele analyzed
- the range of mutations that samples may carry and be considered by the algorithm
- the range of IMGT-numbered positions that should be considered by the algorithm
- the y-intercept threshold above which positions should be considered potentially polymorphic
- the alpha value used for determining whether the
fit y-intercept is greater than the
- the maximum fraction of sequences perfectly aligning to a potential novel allele that are allowed to utilize to a particular combination of junction length and J gene
- the minimum fraction of sequences that must have usable nucleotides in a given position for that position to considered
- the number of processors to use
data.frame with a row for each known allele analyzed.
Besides metadata on the the parameters used in the search, each row will have
either a note as to where the polymorphism-finding algorithm exited or a
nucleotide sequence for the predicted novel allele, along with columns providing
The output contains the following columns:
GERMLINE_CALL: The input (uncorrected) V call.
NOTE: Comments regarding the inferrence.
POLYMORPHISM_CALL: The novel allele call.
NT_SUBSTITUTIONS: Mutations identified in the novel allele, relative to the reference germline (
NOVEL_IMGT: The novel allele sequence.
NOVEL_IMGT_COUNT: The number of times the sequence
NOVEL_IMGTis found in the input data. Considers the subsequence of
NOVEL_IMGT_UNIQUE_J: Number of distinct J calls associated to
NOVEL_IMGTin the input data. Considers the subsequence of
NOVEL_IMGT_UNIQUE_CDR3: Number of distinct CDR3 sequences associated with
NOVEL_IMGTin the input data. Considers the subsequence of
PERFECT_MATCH_COUNT: Final number of sequences retained to call the new allele. These are unique sequences that have V segments that perfectly match the predicted germline in the
PERFECT_MATCH_COUNT / GERMLINE_CALL_COUNT
GERMLINE_CALL_COUNT: The number of sequences with the
GERMLINE_CALLin the input data that were initially considered for the analysis.
GERMLINE_CALL_FREQ: The fraction of sequences with the
GERMLINE_CALLin the input data initially considered for the analysis.
GERMLINE_IMGT: Germline sequence for
GERMLINE_IMGT_COUNT: The number of times the
GERMLINE_IMGTsequence is found in the input data.
MUT_MIN: Minimum mutation considered by the algorithm.
MUT_MAX: Maximum mutation considered by the algorithm.
MUT_PASS_COUNT: Number of sequences in the mutation range.
POS_MIN: First position of the sequence considered by the algorithm (IMGT numbering).
POS_MAX: Last position of the sequence considered by the algorithm (IMGT numbering).
Y_INTERCEPT: The y-intercept above which positions were considered potentially polymorphic.
Y_INTERCEPT_PASS: Number of positions that pass the
SNP_PASS: Number of sequences that pass the
Y_INTERCEPTthreshold and are within the desired nucleotide range (
UNMUTATED_COUNT: Number of unmutated sequences.
UNMUTATED_FREQ: Number of unmutated sequences over
UNMUTATED_SNP_J_GENE_LENGTH_COUNT: Number of distinct combinations of SNP, J gene, and junction length.
SNP_MIN_SEQS_J_MAX_PASS: Number of SNPs that pass both the
ALPHA: Significance threshold to be used when constructing the confidence interval for the y-intercept.
min_seqs. The minimum number of total sequences (within the desired mutational range and nucleotide range) required for the samples to be considered.
j_max. The maximum fraction of sequences perfectly aligning to a potential novel allele that are allowed to utilize to a particular combination of junction length and J gene.
min_frac. The minimum fraction of sequences that must have usable nucleotides in a given position for that position to be considered.
The following comments can appear in the
- Novel allele found: A novel allele was detected.
- Plurality sequence too rare: No sequence is frequent enough to pass
the J test (
- A J-junction combination is too prevalent: Not enough J diversity (
- No positions pass y-intercept test: No positions above
- Insufficient sequences in desired mutational range:
- Not enough sequences: Not enough sequences in the desired mutational
range and nucleotide range (
- No unmutated versions of novel allele found: All observed variants of the allele are mutated.
The TIgGER allele-finding algorithm, briefly, works as follows: Mutations are determined through comparison to the provided germline. Mutation frequency at each position is determined as a function of sequence-wide mutation counts. Polymorphic positions exhibit a high mutation frequency despite sequence-wide mutation count. False positive of potential novel alleles resulting from clonally-related sequences are guarded against by ensuring that sequences perfectly matching the potential novel allele utilize a wide range of combinations of J gene and junction length.
# Find novel alleles and return relevant data novel <- findNovelAlleles(SampleDb, GermlineIGHV)
plotNovel to visualize the data supporting any novel alleles hypothesized to be present in the data and inferGenotype to determine if the novel alleles are frequent enought to be included in the subject’s genotype.