lra is a sequence alignment program that aligns long reads from single-molecule sequencing (SMS) instruments, or megabase-scale contigs from SMS assemblies. lra implements seed chaining sparse dynamic programming with a concave gap function to read and assembly alignment, which is also extended to allow for inversion cases. lra alignment approach increases sensitivity and specificity for SV discovery, particularly for variants above 1kb and when discovering variation from ONT reads, while having runtime that arecomparable (1.05-3.76×) to current methods. When applied to calling variation from *de novo* assembly contigs, there is a 3.2% increase in Truvari F1 score compared to minimap2+htsbox.
Users’ Guide
Installation
Install lra by bioconda: conda install -c bioconda lra
Install lra from github or release: The dependencies are zlib, htslib.
Users can install zlib and htslib through conda and build lra in conda environment.
Get released latest source code from github wget https://github.com/ChaissonLab/lra/archive/VX.XX.tar.gz && tar -xvf VX.XX.tar.gz && cd lra-X.XX/ && make.
Or get source code directly from the master branch git clone --recursive https://github.com/ChaissonLab/lra.git -b master && cd lra && make. You are all set for the installation!
Index reference
lra needs to first build a two-tiered minimizer indexes (global and local) for the reference before mapping. Both can be built at once using commands:
lra index -CCS/CLR/ONT/CONTIG ref.fa
lra has different parameters setting for the index when aligning reads from different sequencing instruments (CCS/CLR/ONT/CONTIG). You can also custimize the parameters. Details see lra index --help. lra takes a few minutes to index the human reference genome.
Alternatively the global and local indexes may be built separately:
lra global -CCS/CLR/ONT/CONTIG ref.fa
lra local -CCS/CLR/ONT/CONTIG ref.fa
Align reads/contigs to reference
lra takes reads fasta, fastq or bam format in the mapping step. The output format can be SAM, PAF, BED and pairwise alignment. Details see lra align --help. The usage of multiple threads can be specified by -t. lra uses the same base algorithm for mapping all datatypes with different parameters settings. It is recommended to choose among CCS/CLR/ONT/CONTIG based on the accuracy and average length of the input reads.
Getting Started
Getting Started
Table of Contents
Introduction
Users’ Guide
Introduction
lra is a sequence alignment program that aligns long reads from single-molecule sequencing (SMS) instruments, or megabase-scale contigs from SMS assemblies. lra implements seed chaining sparse dynamic programming with a concave gap function to read and assembly alignment, which is also extended to allow for inversion cases. lra alignment approach increases sensitivity and specificity for SV discovery, particularly for variants above 1kb and when discovering variation from ONT reads, while having runtime that arecomparable (1.05-3.76×) to current methods. When applied to calling variation from *de novo* assembly contigs, there is a 3.2% increase in Truvari F1 score compared to minimap2+htsbox.
Users’ Guide
Installation
Install lra by bioconda:
conda install -c bioconda lraInstall lra from github or release: The dependencies are zlib, htslib. Users can install
zlibandhtslibthrough conda and build lra in conda environment.conda activate env;conda install -c bioconda htslibandconda install -c anaconda zlib;wget https://github.com/ChaissonLab/lra/archive/VX.XX.tar.gz && tar -xvf VX.XX.tar.gz && cd lra-X.XX/ && make. Or get source code directly from the master branchgit clone --recursive https://github.com/ChaissonLab/lra.git -b master && cd lra && make. You are all set for the installation!Index reference
lra needs to first build a two-tiered minimizer indexes (global and local) for the reference before mapping. Both can be built at once using commands:
lra has different parameters setting for the index when aligning reads from different sequencing instruments (CCS/CLR/ONT/CONTIG). You can also custimize the parameters. Details see
lra index --help. lra takes a few minutes to index the human reference genome.Alternatively the global and local indexes may be built separately:
Align reads/contigs to reference
lra takes reads fasta, fastq or bam format in the mapping step. The output format can be SAM, PAF, BED and pairwise alignment. Details see
lra align --help. The usage of multiple threads can be specified by-t. lra uses the same base algorithm for mapping all datatypes with different parameters settings. It is recommended to choose amongCCS/CLR/ONT/CONTIGbased on the accuracy and average length of the input reads.If you have read.fa.gz, you may pip the read.fa to lra.
Output format
lra uses a set of customized tags in SAM and PAF output.