complexity.entropy: Sequence Complexity Using The Shannon-Wiener Algorithm

In R453Plus1Toolbox: A package for importing and analyzing data from Roche's Genome Sequencer System

Description

This function evaluates the sequence complexity using the Shannon-Wiener Algorithm.

Usage

  complexity.entropy(object, xlab="Complexity score (0=low, 100=high)", ylab="Number of sequences", 
    xlim=c(0, 100), col="firebrick1", breaks=100, ...)

Arguments

object	An object of class DNAStringSet, ShortRead or SFFContainer.
xlab	The X axis label.
ylab	The Y axis label.
xlim	The limits of the X axis.
col	The plotting color.
breaks	The number of breaks in the histogram (see ‘hist’).
...	Arguments to be passed to methods, such as graphical parameters (see ‘par’).

Details

The entropy approach evaluates the entropy of trinucleotides in a sequence. The entropy values are scaled from 0 to 100 and lower entropy values imply lower complexity. A sequence of homopolymer repeats (e.g. TTTTTTTTTT) has an entropy value of 0, of dinucleotide repeats (e.g. TATATATATA) has an entropy value around 16, and of trinucleotide repeats (e.g. TAGTAGTAG) has an entropy value around 26. Scores below 70 can be considered low-complexity.

Value

A numeric vector containing the complexity score for each sequence.

Author(s)

Christian Ruckert

References

Schmieder R. (2011) Quality control and preprocessing of metagenomic datasets. Bioinformatics, 2011 Mar 15;27(6):863-4.

R453Plus1Toolbox documentation built on Nov. 8, 2020, 5:59 p.m.