assocpairfeat {SeqFeatR}

Finding pairs of sequence alignment positions associated with sequence feature.

Description

Determines pairs of alignment positions that jointly mutate depending on sequence feature.

Usage

assocpairfeat(path_to_file_sequence_alignment = NULL, save_name_csv, dna = FALSE, 
    patnum_threshold = 1, significance_level = 0.05, 
    A11a, A12a, A21a, A22a, B11a, B12a, B21a, B22a,
    multiple_testing_correction = "bonferroni")

Arguments

path_to_file_sequence_alignment

FASTA file with sequence alignment. See example file.

save_name_csv

name of file to which results are written in csv format.

dna

DNA or amino acid sequences.

patnum_threshold

minimum number of patients per HLA type to consider in calculation.

significance_level

significance level in Fisher's exact test.

A11a

position of start of first HLA A allele in header line of FASTA file.

A12a

position of end of first HLA A allele in header line of FASTA file.

A21a

position of start of second HLA A allele in header line of FASTA file.

A22a

position of end of second HLA A allele in header line of FASTA file.

B11a

position of start of first HLA B allele in header line of FASTA file.

B12a

position of end of first HLA B allele in header line of FASTA file.

B21a

position of start of second HLA B allele in header line of FASTA file.

B22a

position of end of second HLA B allele in header line of FASTA file.

multiple_testing_correction

multiple testing correction applied to p-values. Input can be: "holm",
"hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none".

Details

Features may be HLA types, indicated by four blocks in the FASTA comment lines. The positions of these blocks in the comment lines are defined by parameters A11, ..., B22. For patients with a homozygous HLA allele the second allele has to be "00" (without the double quotes).

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 and every HLA-type. 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 assocpair, assocpairfeat uses an analysis with 'features' without a consensus sequence.

Value

Table with all alignment position pairs with significant association with sequence feature.

Note

Use visualizepairfeat for graphical output.

Author(s)

Bettina Budeus

See Also

visualizepairfeat, assocpair

Examples

#Input file
## Not run: 
fasta_input <- system.file("extdata", "Example_aa.fasta", package="SeqFeatR")

#Usage
assocpairfeat(
	path_to_file_sequence_alignment=fasta_input,
	save_name_csv="assocpairfeat_results.csv",
	dna=FALSE,
	patnum_threshold=1,
	significance_level=0.05,
	A11=10,
	A12=11,
	A21=13,
	A22=14,
	B11=17,
	B12=18,
	B21=20,
	B22=21,
	multiple_testing_correction="bonferroni")

## End(Not run)