Skip to content

Latest commit

 

History

History
163 lines (134 loc) · 5.4 KB

README.md

File metadata and controls

163 lines (134 loc) · 5.4 KB
Raw

longread_umi_hiv

Tool set for analyzing HIV-PULSE data. This repository is a modified branch of the longread_umi pipeline developed by Karst et al., 2021, Nature Methods.

Table of contents

Citation
Lambrechts et al. (2023). HIV-PULSE: A long-read sequencing assay for high-throughput near full-length HIV-1 proviral genome characterization NAR.

Installation

1. Conda

  1. Download and install usearch >=10 according to instructions on the website

  2. Download installer script from terminal

    wget https://raw.githubusercontent.com/laulambr/longread_umi_hiv/master/scripts/install_conda.sh

  3. Run installation script from terminal and follow instructions

    bash ./install_conda.sh

  4. If miniconda was installed along with the pipeline, initiate conda and refresh terminal before using pipeline.

    conda init; source ~/.bashrc

  5. Activate and deactivate conda environment

    conda activate longread_umi_HIV
...
conda deactivate

  6. Test if installation was succesfull by running following command when environment is activated

    longread_umi -h

2. Install medaka

  1. Create directory for medaka installation

    mkdir /path/to/medaka

  2. Install medaka (beware latest version (v1.11.3) does only support python 3.8-3.10)

    cd /path/to/medaka

python3 -m venv medaka --prompt "medaka"
source medaka/bin/activate
pip install --upgrade pip
pip install medaka
medaka tools download_models
deactivate

  3. Edit medaka location in scripts/dependencies.sh

    export MEDAKA_ENV_START="source /path/to/medaka/bin/activate"

Usage

Main tools

longread_umi nanopore: Generate UMI bin sequences from Nanopore data.

longread_umi demultiplex: Dual barcode demultiplexing.

longread_umi clustering: Cluster related UMI bin sequences.

usage: 

longread_umi nanopore_pipeline [-h] [ -k flag] (-d file -v value -o dir -s value) 
(-e value -m value -M value -f string -F string -r string -R string )
( -c value -p value -n value -u dir -U string -t value -T value ) 

where:
    -h  Show this help text.
    -d  Single file containing raw Nanopore data in fastq format.
    -v  Minimum read coverage for using UMI consensus sequences for 
        variant calling.
    -o  Output directory.
    -s  Check start of read up to s bp for UMIs.
    -e  Check end of read up to f bp for UMIs.
    -m  Minimum read length.
    -M  Maximum read length.
    -f  Forward adaptor sequence. 
    -F  Forward primer sequence.
    -r  Reverse adaptor sequence.
    -R  Reverse primer sequence.
    -c  Number of iterative rounds of consensus calling with Racon.
    -p  Number of iterative rounds of consensus calling with Medaka.
    -q  Medaka model used for polishing. r941_min_high_g360, r103_min_high_g360 etc.
    -k  Flag for keeping failed bins in output.
    -n  Process n number of bins. If not defined all bins are processed.
        Pratical for testing large datasets.
    -u  Directory with UMI binned reads.
    -U  UMI filter settings. Define settings for:
        - UMI match error mean (UMEM): Mean match error between reads in a bin
          and the UMI reference.
        - UMI match error SD (UMESD): Standard deviation for match error between
          reads in a bin and the UMI reference.
        - Bin cluster ratio (BCR): Ratio between UMI bin size and UMI cluster size.
        - Read orientation ratio (ROR): n(+ strand reads)/n(all reads). '0' is the
          means disabled.
        Settings can be provided as a string: 'UMEM/UMESD/BCR/ROR'
        Or as a preset:
        - 'r941_min_high_g360' == '3;2;6;0.3'
        - 'r103_min_high_g360' == '3;2.5;12;0.3'
    -t  Number of threads to use.
    -T  Number of medaka jobs to start. Threads pr. job is threads/jobs.
        [Default = 1].		

usage: 

longread_umi demultiplex [-h] (-c file -r file -u file -o dir -b file)
(-p string -n range -t value) 

where:
    -h  Show this help text.
    -c  UMI consensus sequences that need demultiplexing.
    -r  Raw read sequences that were used to generate
        the consensus sequences.
    -u  List of raw read names and UMI bin assignments.
    -o  Output directory.
    -b  File containing barcodes. 
        [Default = "$BARCODES"].
    -p  Barcode name prefix [Default = 'barcode'].
    -n  Barcode numbers used. [Default  = '1-120'].
    -t  Number of threads used.

usage: 

longread_umi clustering [-h -b] (-c file -F string -R string -m value -M value -p value -o dir -i dir -t value ) 

where:
    -h  Show this help text.
    -c  UMI consensus file.
    -F  Forward tagging primer sequence.
    -R  Reverse tagging primer sequence.
    -m  Minimum read length.
    -M  Maximum read length.
    -p  Percentage identity for usearch [Default = 0.995].
    -o  Output directory.
    -i  Input directory.
    -t  Number of threads to use. [Default = 1]
    -b  Debug flag. Keep temp files. [Default = NO]

Example script

See following file for example commands to perform HIV-PULSE data analysis.

License

GNU General Public License, version 3