assocpairfeat: Finding pairs of sequence alignment positions associated with...
In SeqFeatR: A Tool to Associate FASTA Sequences and Features

Description Usage Arguments Details Value Note Author(s) See Also Examples

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

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")

`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".

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.

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

Use visualizepairfeat for graphical output.

Bettina Budeus

visualizepairfeat, assocpair

#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)