biotite
seqtk
| biotite | seqtk | |
|---|---|---|
| 2 | 8 | |
| 557 | 1,314 | |
| 1.3% | - | |
| 9.0 | 5.1 | |
| 2 days ago | 6 months ago | |
| Python | C | |
| BSD 3-clause "New" or "Revised" License | MIT License |
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biotite
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Journey into bioinformatics
For bioinformatics in Python, the BioPython library (https://biopython.org/) is commonly used. An alternative to this package is Biotite (https://www.biotite-python.org/), a package I am maintaining.
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What bioinformatics software can i give my contribute?
If you like programming in Python, you could contribute to Biotite (https://www.biotite-python.org/). You may have a look at the open issues at https://github.com/biotite-dev/biotite/issues or the projects at https://github.com/biotite-dev/biotite/projects. If you are interested in a project, you can get in contact via Mail or our Discord channel (https://discord.gg/cUjDguF).
seqtk
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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?
Biopython - Official git repository for Biopython (originally converted from CVS)
seqkit - A cross-platform and ultrafast toolkit for FASTA/Q file manipulation
3DFI - The 3DFI pipeline predicts the 3D structure of proteins and searches for structural homology in the 3D space.
samtools - [Moved to: https://github.com/ingolia/SamTools]
Clairvoyante - Clairvoyante: a multi-task convolutional deep neural network for variant calling in Single Molecule Sequencing
htslib - C library for high-throughput sequencing data formats
CNApy - An integrated visual environment for metabolic modeling with common methods such as FBA, FVA and Elementary Flux Modes, and advanced features such as thermodynamic methods, extended Minimal Cut Sets, OptKnock, RobustKnock, OptCouple and more!
samtools - Tools (written in C using htslib) for manipulating next-generation sequencing data
minimap2 - A versatile pairwise aligner for genomic and spliced nucleotide sequences
bam-filter - Use simple expressions to filter a BAM/CRAM file
MMseqs2 - MMseqs2: ultra fast and sensitive search and clustering suite
fastp - An ultra-fast all-in-one FASTQ preprocessor (QC/adapters/trimming/filtering/splitting/merging...)