andreas-wilm / graphmap Goto Github PK

Current Version: 0.21
Release date: 02 June 2015
Source code and precompiled binary for Linux x64 systems (built on Ubuntu 10.04 x64).

GraphMap is a novel mapper targeted at aligning long, error-prone third-generation sequencing data.
It is designed to handle Oxford Nanopore MinION 1d and 2d reads with very high sensitivity and accuracy, and also presents a significant improvement over the state-of-the-art for PacBio read mappers.

GraphMap was also designed for ease-of-use: the default parameters can handle a wide range of read lengths and error profiles, including: Illumina, PacBio and Oxford Nanopore.
This is an especially important feature for technologies where the error rates and error profiles can vary widely across, or even within, sequencing runs.

The GraphMap algorithm is structured to achieve high-sensitivity and speed using a five-stage read-funneling approach. In stage I, GraphMap uses a novel adaptation of gapped spaced seeds to efficiently reduce the search space and get seed hits as a form of coarse alignment. These are then refined in stage II using graph-based vertex-centric processing of seeds to efficiently construct alignment anchors. GraphMap then chains anchors using a kmer version of longest common subsequence (LCS) construction (stage III), refines alignments with a form of L1 linear regression (stage IV) and finally evaluates the remaining candidates to select the best location to reconstruct a final alignment (stage V). GraphMap computes a BLAST-like E-value as well as a mapping quality for its alignments.

Evaluation on MinION sequencing datasets against short and long-read mappers indicates that GraphMap increases mapping sensitivity by at least 15-80%. GraphMap alignments are the first to demonstrate consensus calling with <1 error in 100,000 bases, variant calling on the human genome with 76% improvement in sensitivity over the next best mapper (BWA-MEM), precise detection of structural variants from 100bp to 4kbp in length and species and strain-specific identification of pathogens using MinION reads.

Further details about the algorithm, comparison with other mappers and usage applications can be found in the preprint of our paper:
Fast and sensitive mapping of error-prone nanopore sequencing reads with GraphMap

Nanopore sequencing data of E. Coli UTI89 generated in-house and used in the paper now available on ENA:
PRJEB9557

• Mapping position agnostic to alignment parameters.
• Consistently very high sensitivity and precision across different error profiles, rates and sequencing technologies even with default parameters.
• Circular genome handling to resolve coverage drops near ends of the genome.
• E-value.
• Meaningful mapping quality.
• Various alignment strategies (semiglobal bit-vector and Gotoh, anchored).

To build GraphMap from source type:

make

Required libraries are prebuilt for Linux x64 systems. To rebuild them for other systems, type:

make deps

More installation instructions can be found in the INSTALL file.

# Align all reads from a given FASTA/FASTQ file with default number of threads using semiglobal bit-vector alignment:
./graphmap -r escherichia_coli.fa -d reads.fastq -o alignments.sam  

# Align all reads from a given FASTA/FASTQ file using anchored alignment approach:  
./graphmap -a anchor -r escherichia_coli.fa -d reads.fastq -o alignments.sam  

# Align reads using the Gotoh for semiglobal alignment:
./graphmap -a gotoh -r escherichia_coli.fa -d reads.fastq -o alignments.sam  

# Process reads from a circular genome:
./graphmap -C -r escherichia_coli.fa -d reads.fastq -o alignments.sam

# Threshold the E-value of alignments to 1e-100. Alignments with E-value > 1e-100 will be called unmapped:  
./graphmap -z 1e-100 -r escherichia_coli.fa -d reads.fastq -o alignments.sam  

# Output all similarly good alignments (to within F*num_kmers_of_best_alnmnt) instead of only one best:  
./graphmap -Z -F 0.05 -r escherichia_coli.fa -d reads.fastq -o alignments.sam  

# Limit the number of threads to 8, and load reads in batches of 50MB:  
./graphmap -t 8 -B 50 -r escherichia_coli.fa -d reads.fastq -o alignments.sam  

# Align reads using more sensitive parameters for Illumina data (currently equivalent to "-a gotoh"):  
./graphmap -x illumina -r escherichia_coli.fa -d reads.fastq -o alignments.sam  

# Load all reads in one batch and align only the first 1000 reads:
./graphmap -B 0 -n 1000 -r escherichia_coli.fa -d reads.fastq -o alignments.sam

# Process all reads from a given folder.
./graphmap -r escherichia_coli.fa -D reads_folder -O alignments_folder

# Generate only the index.
./graphmap -I -r escherichia_coli.fa

# Run a debug version of GraphMap (build with "make debug") and verbose the SAM output to see various info about alignment:
./graphmap-debug -b 3 -r escherichia_coli.fa -d reads.fastq -o alignments.sam  

For additional information, help and bug reports please send an email to one of the following: [email protected], [email protected], [email protected]