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Covest estimates the coverage and genome size, just from k-mer abundance histogram computed from DNA sequences reads.

Project description

Tool that estimates coverage (and genome size) of dna sequence from reads.

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Requirements

  • python 3.4+

  • python3-dev

  • gcc

Installation

We suggest to install CovEst in python3 virtual environment.

pip install covest

For development:

pip install -e . from the project directory

Usage

type covest --help for the usage.

Basic Usage:

covest histogram -m model -k K -r read_length

  • You can specify the read file using -s reads.fa parameter for more precise genome size computation.

  • default K is 21

  • default read length is 100

  • currently, the supported models are:

    • basic: for simple genomes without repeats

    • repeat: for genomes with repetitive sequences

Input Histogram Specification:

The input histogram can be generated from the read data using jellyfish.

  • jellyfish count -m K -C reads.fa -o table.jf

  • jellyfish histo table.jf -o reads.hist

The format of the histogram is just list of lines. Each lines contains an index and value separated by space.

Output Specification:

CovEst outputs it’s results in simple subset of YAML format for best human readability and possibility of machine processing.

The output are lines containing key: value. The most important keys are coverage and genome_size (or genome_size_reads if read file was specified).

Other included tools

  • geset.py tool for estimation genome size from reads size and known coverage

  • reads_size.py tool for computation of the total reads size

  • kmer_hist.py custom khmer histogram computation, it is much slower than other tools, so use it only if you have no other option.

  • read_sampler.py script for subsampling reads, useful if you have very high coverage data and want to make it smaller.

  • fasta_length.py get total length of all sequences in fasta file.

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