calcParProtSeqSim {Rcpi} | R Documentation

## Parallellized Protein Sequence Similarity Calculation based on Sequence Alignment

### Description

Parallellized Protein Sequence Similarity Calculation based on Sequence Alignment

### Usage

    calcParProtSeqSim(protlist, cores = 2, type = "local",
      submat = "BLOSUM62")

### Arguments

`protlist` | A length `n` list containing `n` protein sequences, each component of the list is a character string, storing one protein sequence. Unknown sequences should be represented as `''`.
`cores` | Integer. The number of CPU cores to use for parallel execution, default is `2`. Users could use the `detectCores()` function in the `parallel` package to see how many cores they could use.
`type` | Type of alignment, default is `'local'`, could be `'global'` or `'local'`, where `'global'` represents Needleman-Wunsch global alignment; `'local'` represents Smith-Waterman local alignment.
`submat` | Substitution matrix, default is `'BLOSUM62'`, could be one of `'BLOSUM45'`, `'BLOSUM50'`, `'BLOSUM62'`, `'BLOSUM80'`, `'BLOSUM100'`, `'PAM30'`, `'PAM40'`, `'PAM70'`, `'PAM120'`, `'PAM250'`.

### Details

This function implemented the parallellized version for calculating protein sequence similarity based on sequence alignment.

### Value

A `n` x `n` similarity matrix.

### Author(s)

Nan Xiao <https://nanx.me>

### See Also

See `calcTwoProtSeqSim` for protein sequence alignment for two protein sequences. See `calcParProtGOSim` for protein similarity calculation based on Gene Ontology (GO) semantic similarity.

### Examples

    s1 = readFASTA(system.file('protseq/P00750.fasta', package = 'Rcpi'))[[1]]
    s2 = readFASTA(system.file('protseq/P08218.fasta', package = 'Rcpi'))[[1]]
    s3 = readFASTA(system.file('protseq/P10323.fasta', package = 'Rcpi'))[[1]]
    s4 = readFASTA(system.file('protseq/P20160.fasta', package = 'Rcpi'))[[1]]
    s5 = readFASTA(system.file('protseq/Q9NZP8.fasta', package = 'Rcpi'))[[1]]
    plist = list(s1, s2, s3, s4, s5)

    psimmat = calcParProtSeqSim(plist, cores = 2, type = 'local',
                                submat = 'BLOSUM62')
    print(psimmat)

[Package Rcpi version 1.24.0 Index]