slideWindowDb - Sliding window approach towards filtering sequences in a
slideWindowDb determines whether each input sequence in a
contains equal to or more than a given number of mutations in a given length of
consecutive nucleotides (a “window”) when compared to their respective germline
slideWindowDb( db, sequenceColumn = "sequence_alignment", germlineColumn = "germline_alignment_d_mask", mutThresh = 6, windowSize = 10, nproc = 1 )
data.framecontaining sequence data.
- name of the column containing IMGT-gapped sample sequences.
- name of the column containing IMGT-gapped germline sequences.
- threshold on the number of mutations in
windowSizeconsecutive nucleotides. Must be between 1 and
- length of consecutive nucleotides. Must be at least 2.
- Number of cores to distribute the operation over. If the
clusterhas already been set earlier, then pass the
cluster. This will ensure that it is not reset.
a logical vector. The length of the vector matches the number of input sequences in
db. Each entry in the vector indicates whether the corresponding input sequence
should be filtered based on the given parameters.
# Use an entry in the example data for input and germline sequence data(ExampleDb, package="alakazam") # Apply the sliding window approach on a subset of ExampleDb slideWindowDb(db=ExampleDb[1:10, ], sequenceColumn="sequence_alignment", germlineColumn="germline_alignment_d_mask", mutThresh=6, windowSize=10, nproc=1)
 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE