calcExpectedMutations - Calculate expected mutation frequencies of a sequence
Description¶
calcExpectedMutations
calculates the expected mutation
frequencies of a given sequence. This is primarily a helper function for
expectedMutations.
Usage¶
calcExpectedMutations(
germlineSeq,
inputSeq = NULL,
targetingModel = HH_S5F,
regionDefinition = NULL,
mutationDefinition = NULL
)
Arguments¶
- germlineSeq
- germline (reference) sequence.
- inputSeq
- input (observed) sequence. If this is not
NULL
, thengermlineSeq
will be processed to be the same same length asinputSeq
and positions ingermlineSeq
corresponding to positions with Ns ininputSeq
will also be assigned an N. - targetingModel
- TargetingModel object. Default is HH_S5F.
- regionDefinition
- RegionDefinition object defining the regions and boundaries of the Ig sequences.
- mutationDefinition
- MutationDefinition object defining replacement
and silent mutation criteria. If
NULL
then replacement and silent are determined by exact amino acid identity.
Value¶
A numeric
vector of the expected frequencies of mutations in the
regions in the regionDefinition
. For example, when using the default
IMGT_V definition, which defines positions for CDR and
FWR, the following columns are calculated:
mu_expected_cdr_r
: number of replacement mutations in CDR1 and CDR2 of the V-segment.mu_expected_cdr_s
: number of silent mutations in CDR1 and CDR2 of the V-segment.mu_expected_fwr_r
: number of replacement mutations in FWR1, FWR2 and FWR3 of the V-segment.mu_expected_fwr_s
: number of silent mutations in FWR1, FWR2 and FWR3 of the V-segment.
Details¶
calcExpectedMutations
calculates the expected mutation frequencies of a
given sequence and its germline.
Note, only the part of the sequences defined in regionDefinition
are analyzed.
For example, when using the default IMGT_V definition, mutations in
positions beyond 312 will be ignored.
Examples¶
# Load example data
data(ExampleDb, package="alakazam")
# Use first entry in the exampled data for input and germline sequence
in_seq <- ExampleDb[["sequence_alignment"]][1]
germ_seq <- ExampleDb[["germline_alignment_d_mask"]][1]
# Identify all mutations in the sequence
calcExpectedMutations(germ_seq,in_seq)
seq_r seq_s
0.7636446 0.2363554
# Identify only mutations the V segment minus CDR3
calcExpectedMutations(germ_seq, in_seq, regionDefinition=IMGT_V)
cdr_r cdr_s fwr_r fwr_s
0.20544721 0.04081758 0.56090228 0.19283293
# Define mutations based on hydropathy
calcExpectedMutations(germ_seq, in_seq, regionDefinition=IMGT_V,
mutationDefinition=HYDROPATHY_MUTATIONS)
cdr_r cdr_s fwr_r fwr_s
0.1209459 0.1253189 0.3169116 0.4368236
See also¶
expectedMutations calls this function.
To create a custom targetingModel
see createTargetingModel.
See calcObservedMutations for getting observed mutation counts.