README.md

runlength_analysis_cpp

This library was built to replace rlorigro/runlength_analysis. Given raw sequences, or an assembly, this library will generate a confusion matrix of homopolymer length predictions. Some evaluation tools are included to aid in the development of runlength related methods.

Installation

Download repo and run library installation script:

git clone https://github.com/rlorigro/runlength_analysis_cpp.git
cd runlength_analysis_cpp/
sudo sh install_prerequisites_ubuntu_18.sh 

If minimap2 not installed and added to path:

cd your/preferred/installation/directory
sudo sh path/to/runlength_analysis_cpp/install_minimap2.sh

If cmake is not installed:

wget https://github.com/Kitware/CMake/releases/download/v3.14.4/cmake-3.14.4-Linux-x86_64.sh
sudo mkdir /opt/cmake 
sudo sh cmake-3.14.4-Linux-x86_64.sh --prefix=/opt/cmake --skip-license 
sudo ln -s /opt/cmake/bin/cmake /usr/local/bin/cmake
cmake --version

Finally:

mkdir build
cd build
cmake ..
make -j [n_threads]

Usage

Generating a Shasta config file

Acquire a FASTA file containing read sequences.

Run measure_runlength_distribution_from_fasta using the executable in your build directory:

/home/ubuntu/software/runlength_analysis_cpp/build/measure_runlength_distribution_from_fasta \
--minimap_preset map-ont \
--max_threads 92 \
--minimum_match_length 11 \
--output_dir /home/ubuntu/data/human/hg005/reads/rle_run1/ \
--ref /home/ubuntu/data/human/reference/hg005/HG005.paternal.f1_assembly_v2_genbank.fasta \
--sequences /home/ubuntu/data/human/hg005/reads/05_25_21_R941_GM24631_9X_2_Guppy_5.0.7_prom_sup.fasta

To avoid regions of the alignment that contain misalignments as a result of short repeats (dinucleotide or others), it is highly recommended that the minimum_match_length parameter is used. See below in the "x_repeat" channel for an example of misalignments in RLE-space:

For ONT data, be sure to use the map-ont preset, or for assemblies the asm20 preset, etc.

Once this finishes running, a CSV will be generated containing confusion matrices for each nucleotide's runlength from 1-50bp. This is used to generate a table of normalized likelihoods (shasta's Bayesian ConsensusCaller config file). For example:

../scripts/convert_frequency_matrix_to_shasta_config.py \
--prior human \
--name HG005_wg_guppy_5.0.7_with_10_pseudocount_4-6-2022 \
--input /home/ryan/data/human/hg005/rle/guppy5/run2/length_frequency_matrix_nondirectional.csv \
--output /home/ryan/data/human/hg005/rle/guppy5/run2/shasta_bayesian_config_nondirectional_zero-fix/ \
--pseudocount 10

This generates an output directory and in it is a CSV which can be used directly by Shasta.

You can also edit the plot_matrix script to generate comparisons of frequency matrices for debugging/QC purposes:

Generating a MarginPolish RLE Matrix

To generate a MarginPolish RLE Matrix you need to use the measure_runlength_distribution_from_fasta exectuable and the convert_frequency_matrix_to_marginpolish.py script from this repository, and a reference and .fasta (not .fastq) file with your reads.

From the build/ directory:

./measure_runlength_distribution_from_fasta --ref reference.fasta --sequences reads.fasta
python ../scripts/convert_frequency_matrix_to_marginpolish.py -i output/length_frequency_matrix_directional.csv -o output/marginPolish

This will create a file in output/marginPolish. The contents of this file can be placed into the "repeatCountSubstitutionMatrix" node of the polish parameters.