MMseqs2
MMseqs2: ultra fast and sensitive search and clustering suite (by soedinglab)
seqtk
Toolkit for processing sequences in FASTA/Q formats (by lh3)
| MMseqs2 | seqtk | |
|---|---|---|
| 5 | 8 | |
| 1,527 | 1,422 | |
| 1.6% | 0.8% | |
| 9.2 | 3.5 | |
| 14 days ago | 6 months ago | |
| C | C | |
| MIT License | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
MMseqs2
Posts with mentions or reviews of MMseqs2.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-11-09.
- Segmenting Credit Card Customers with K-Means: A Fun Dive into Clustering
-
Clustering tool that could help cluster protein sequences based on percentage identity
A tool I often recommend for sequence clustering is mmseqs2 : https://github.com/soedinglab/MMseqs2, fast and efficient :)
- MMseqs2 – an example of great software for biology
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Metagenomics: abundances of short reads using genome databases
Tools like the the mmseqs2 "taxonomy" module, or DIAMOND v2, can efficiently align contigs to genome databases to assign taxonomy, but it seems like they aren't intended to provide abundance estimates for each taxon (since that would require mapping reads, and mmseqs2 can't even use paired-reads). Can anyone recommend tools or methods for A) connecting per-contig coverage information to contig taxonomy, or B) mapping short reads against genome databases?
- Retrieving One-to-One Orthologs of Unprocessed cDNAs
seqtk
Posts with mentions or reviews of seqtk.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-07-04.
-
Illumina adapters and quality trimming
seqtk: A lightweight and versatile tool for processing FASTQ and FASTA files. https://github.com/lh3/seqtk
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looking for a tool to filter non-coding regions/excise ORFs from a draft assembly
Perhaps seqtk could be helpful https://github.com/lh3/seqtk
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Help with understanding awk code
You could also check out tools specialized for FASTA processing like https://github.com/shenwei356/seqkit and https://github.com/lh3/seqtk
- !help
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Doubts with my first ever mRNA-seq QC analysis
If I were to analyze I would use a random fastq sampler like Seqtk and bring all your samples to a lowest read depth of your 27 libraries although I wouldn't analyze a library with less than 2mil reads. 5 mil is fine for differential, you can obviously get more reads and probably received more information but increasing read depth may plateau.
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Reverse sequencing of fastq file
It's a little toolkit written by one of the Illuminati of the Bioinformatics world: seqtk on GH
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[Help] Copying head of fastq file into a .txt file named .fastq, doesn't include the header resolving in an error when converting to .bam file.
I recommend installing seqtk, which makes this easy. Of course sed/awk/perl are theoretically entirely sufficient but why make life more difficult than necessary?
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Looking for small SRA Data Sets
Most SRA files are grouped by projects. On a basic level for something common like RNA-seq you will have replicates of the control and treatment/diseased samples. Each file (i.e. sample) contains raw sequencing reads, usually millions per sample. You could randomly subsample the sequencing reads very easily using many tools (common choice is https://github.com/lh3/seqtk). There is no way you are going to assemble an animal genome with MB file sizes (for example the human genome itself is already over 3GB in size). You should probably look for bacterial or viral DNA samples and subset those to an appropriate size.
What are some alternatives?
When comparing MMseqs2 and seqtk you can also consider the following projects:
htslib - C library for high-throughput sequencing data formats
seqkit - A cross-platform and ultrafast toolkit for FASTA/Q file manipulation
samtools - Tools (written in C using htslib) for manipulating next-generation sequencing data
fastp - An ultra-fast all-in-one FASTQ preprocessor (QC/adapters/trimming/filtering/splitting/merging...)
SqueezeMeta - A complete pipeline for metagenomic analysis
kraken-biom - Create BIOM-format tables (http://biom-format.org) from Kraken output (http://ccb.jhu.edu/software/kraken/, https://github.com/DerrickWood/kraken).
dada2 - Accurate sample inference from amplicon data with single nucleotide resolution
minimap2 - A versatile pairwise aligner for genomic and spliced nucleotide sequences
GTDBTk - GTDB-Tk: a toolkit for assigning objective taxonomic classifications to bacterial and archaeal genomes.
samtools - [Moved to: https://github.com/ingolia/SamTools]