VACmap-—a long-read aligner specifically designed for complex structural variation discovery.
git clone https://github.com/micahvista/VACmap.git
cd VACmap
conda env create --name vacmap_env --file VACmap_environment.yml
conda activate vacmap_env
python setup.py installUsage
Map long genomic reads:
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vacmap -ref /ref.fasta -read /read.fasta -mode S -t 8 | samtools sort -@4 > alignments.sorted.bam
samtools index -@4 alignments.sorted.bam
*Memory usage: <20GB
*Speed: Processing HG002 50X ONT data (170GB) took 5.8 hours using 40 threads.
Map assembly:
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vacmap -ref /ref.fasta -read /read.fasta -mode asm -t 8 -workdir /home/usr/workdir/ --H --fakecigar | samtools sort -@4 > alignments.sorted.bam
samtools index -@4 alignments.sorted.bam
or (lower memory usage)
vacmap -ref /ref.fasta -read /read.fasta -mode asm -t 8 -workdir /home/usr/workdir/ --H --fakecigar > alignments.sam
samtools sort -@4 alignments.sam > alignments.sorted.bam
samtools index -@4 alignments.sorted.bam
*Memory usage: 30GB-70GB Using more threads requires more memory.
*Speed: Processing HG002 v1.0 assembly(48 contigs) took 2.3 hours using 40 threads.Parameter
Mandatory parameter:
-ref The path of reference sequence.
-read The path of long reads.
-t The number of threads to use. (Note: In asm mode, using fewer threads results in lower memory usage.)
-mode S|L|H|R|asm
-workdir Only for asm mode, store temporary data. If the folder not existexist, VACmap will create it automatically.
Input:
Supported read input types: FASTA, FASTA.GZ, FASTQ, FASTQ.GZ, BAM.
[Warning: Duplicate reads (based on read names) will be processed only once.]
Multiple read input options:
-read read_1.fa read_2.fa ...
-read read_1.fa -read read_2.fa ...
Mapping:
-mode H For aligning high error rate long read (Pacbio CLR, ONT).
-mode L For aligning low error rate long read (Pacbio HiFi).
-mode S Increase the sensitivity for small variants. (<100bp). (Pacbio CLR, ONT, HiFi).
-mode R Use a fixed value for the variation penalty, more sensitive to translocation events,
such as gene conversion. (Pacbio CLR, ONT, HiFi).
-mode asm For full genome alignment.
-k k-mer size (no larger than 28, deflaut: 15) # set -k 19 -w 10 for HiFi data
to reduce run time (2X faster) but there is very small decrease in accuracy.
-w minimizer window size. (deflaut: 10)
Output:
--eqx Output =/X CIGAR operators for sequence match/mismatch.
--MD Output the MD tag.
--cs[=short|long] Output the cs tag. (deflaut: short cs).
--copycomments Copy FASTA/Q comments to output.
--H Use hard-clipping instead of soft-clipping for clipped sequences.
[Warning: SV callers may fail to detect split-read events.]
--Q Ignore base quality in the input file.
--fakecigar Use approximate CIAGR in the SA tag.
--rg-id <string> Adds RG:Z:<string> to all alignments
--rg-sm <string> RG header: Sample
--rg-lb <string> RG header: Library
--rg-pl <string> RG header: Platform
--rg-ds <string> RG header: Description
--rg-dt <string> RG header: Date (format: YYYY-MM-DD)
--rg-pu <string> RG header: Platform unit
--rg-pi <string> RG header: Median insert size
--rg-pg <string> RG header: Programs
--rg-cn <string> RG header: sequencing center
--rg-fo <string> RG header: Flow order
--rg-ks <string> RG header: Key sequence
--rg-pm <string> Platform model. Free-form text providing further details of the platform/technology used.
--rg-bc <string> Barcode sequence identifying the sample or library.Limitations
Single Reference Sequence Size Limit:
2,147,483,647 bases.
Single Query Sequence Size Limit:
2,147,483,647 bases for Modes L, H, S, R.
Unlimited for Mode asm.Reduce runtime (45% faster for aligning HiFi data) and include options to decrease output size. Seq 3, 2024
Copy FASTA/Q comments to output. Aug 22, 2024
Improved speed, 40% faster. Aug 9, 2024
Fix bug. Aug 5, 2024
Enabled overlapping anchors in non-linear chaining. Jul 4, 2024
If you experience any problems or have suggestions please create an issue or a pull request.
This is a demonstration of the non-linear alignment algorithm used in VACmap: http://64.64.240.35:8050/. I hope this tool proves helpful for your research!
https://www.biorxiv.org/content/10.1101/2023.08.03.551566v2
The project is licensed under the GNU General Public License.