KSiga is a toolkit for evaluate the lenght of optimal k-mer in dataset.
KSiga provides many methods to evaluate the amount of information by given k-mer. This quantitative measurement could be use to calculate the amount of need k-mer
Clone the repository and install it throught pip
git clone https://github.com/yumyai/ksiga.git
cd ksiga
pip install -e .
To create a k-mer profiles.
wget https://github.com/yumyai/ksiga/blob/devel/examples.tar.gz?raw=true # Download example dataset
tar -xzf examples.tar.gz
# This will create an index in folder ex-index
ksiga index examples -o ex-index
KSiga provides three commands for calculate an appropiate k-mer using CRE, ACF, and OCF.
ksiga cre_kmer ex-index/* -ks 5 -ke 10
ksiga acf_kmer ex-index/* -ks 5 -ke 10
ksiga ocf_kmer ex-index/* -ks 5 -ke 10
Each of these command will print out the optimal k-mer.
Calculating CRE are very computing intensive. We planned to provide a way to run in on cluster soon.