assocpair {SeqFeatR} | R Documentation |
Finding pairs of alignment positions that jointly mutate
Description
Determines pairs of sequence alignment positions that mutate in a correlated fashion with respect to a consensus sequence.
Usage
assocpair(path_to_file_sequence_alignment = NULL,
path_to_file_consensus = NULL, save_name_csv, dna = FALSE,
significance_level = 0.05, multiple_testing_correction = "bonferroni")
Arguments
path_to_file_sequence_alignment |
FASTA file with sequence alignment. See example file. |
path_to_file_consensus |
FASTA file with consensus sequence. See example file. |
save_name_csv |
name of file to which results are written in csv format. |
dna |
indicates whether sequences are DNA or amino acids. |
significance_level |
significance level for Fisher's exact test. |
multiple_testing_correction |
multiple testing correction applied to p-values. Input can be: "holm", |
Details
For every position in the sequence alignment from the FASTA file a Fisher's exact test is applied with every other position in the sequence to check whether at both positions we have correlated mutations with respect to a given consensus sequence. Significant p-values are collected in one big table. p.adjust from stats package is used for multiple testing correction; corrected values are given as extra column in csv output.
In contrast to assocpairfeat, assocpair does not use features, but uses a consensus approach. Please be sure, that this is really what you want to use. Otherwise, use assocpairfeat or assoctuple instead.
Value
A csv file with every possible co-mutation below the given p-value.
Note
For graphical output use:
visualizepair
.
Author(s)
Bettina Budeus
See Also
visualizepairfeat
, assocpairfeat
, assoctuple
Examples
#Input files
## Not run:
fasta_input <- system.file("extdata", "Example_aa.fasta", package="SeqFeatR")
consensus_input <- system.file("extdata", "Example_Consensus_aa.fasta", package="SeqFeatR")
#Usage
assocpair(
path_to_file_sequence_alignment=fasta_input,
path_to_file_consensus=consensus_input,
save_name_csv="assocpair_results.csv",
dna=FALSE,
significance_level=0.05,
multiple_testing_correction="bonferroni")
## End(Not run)