R: Percent Identity

seqidentity {bio3d} | R Documentation

## Percent Identity

### Description

Determine the percent identity scores for aligned sequences.

### Usage

      seqidentity(alignment, normalize=TRUE, similarity=FALSE, ncore=1, nseg.scale=1)

### Arguments

`alignment` | sequence alignment obtained from `read.fasta` or an alignment character matrix.
`normalize` | logical, if TRUE output is normalized to values between 0 and 1 otherwise percent identity is returned.
`similarity` | logical, if TRUE sequence similarity is calculated instead of identity.
`ncore` | number of CPU cores used to do the calculation. `ncore>1` requires package ‘parallel’ installed.
`nseg.scale` | split input data into specified number of segments prior to running multiple core calculation. See `fit.xyz`.

### Details

The percent identity value is a single numeric score determined for each pair of aligned sequences. It measures the number of identical residues (“matches”) in relation to the length of the alignment.

### Value

Returns a numeric matrix with all pairwise identity values.

### Author(s)

Barry Grant

### References

Grant, B.J. et al. (2006) Bioinformatics 22, 2695–2696.

### See Also

`read.fasta`, `filter.identity`, `entropy`, `consensus`

### Examples

    attach(kinesin)

    ide.mat <- seqidentity(pdbs)

    # Plot identity matrix
    plot.dmat(ide.mat, color.palette=mono.colors,
              main="Sequence Identity", xlab="Structure No.",
              ylab="Structure No.")

    # Histogram of pairwise identity values
    hist(ide.mat[upper.tri(ide.mat)], breaks=30,xlim=c(0,1),
         main="Sequence Identity", xlab="Identity")

    # Compare two sequences
    seqidentity( rbind(pdbs$ali[1,], pdbs$ali[15,]) )

    detach(kinesin)

[Package bio3d version 2.4-2 Index]