trinityrnaseq
seqkit
| trinityrnaseq | seqkit | |
|---|---|---|
| 6 | 3 | |
| 803 | 1,205 | |
| 0.6% | - | |
| 2.8 | 8.5 | |
| 16 days ago | 3 days ago | |
| Perl | Go | |
| BSD 3-clause "New" or "Revised" License | MIT License |
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trinityrnaseq
- What are some good examples of well-engineered bioinformatics pipelines?
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Can I get so guidance on how to run sample data in trinityrnaseq-Trinity-v2.13.2 in Ubuntu Linux ?
The screen shot suggests you are not able to actually compile/install trinity. The cmake command is not used to run it. After you download and unpack the trinity software package: https://github.com/trinityrnaseq/trinityrnaseq/releases/download/Trinity-v2.13.2/trinityrnaseq-v2.13.2.FULL.tar.gz, you should look at the INSTALL file, which tells you to:
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Beginner question for using dockerized trinity
I'm trying commands from the Docker site and the trinity site. When I try to run the command, it behaves like the code is incomplete (hitting enter just gives me a new line). To my understanding, the issue can be either in the pathway/to/files part of the code, of in the trinityrnaseq/trinityrnaseq part.
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GATK version issue with variant calling following Trinity pipeline python script
For my analysis I am trying to do variant calling on my transcriptome. I am following the Trinity github pipeline for variant calling, in which they provided a python script for GATK for the variant calling. I use SLURM to run this job for me:
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What's your bioinformatics bible? Any bibliography recommendations for experimental design?
Since you're an R user, I would recommend Bioconductor. Here's an excellent tutorial on how to analyze RNA-seq data (make sure that you're R version is up to date!): https://www.bioconductor.org/packages/devel/workflows/vignettes/rnaseqGene/inst/doc/rnaseqGene.html . However, if you want to assemble raw transcriptome data, then Trinity is a great tool (https://github.com/trinityrnaseq/trinityrnaseq/wiki).
- Can DESeq2 and edgeR be used on Trinity assembled transcripts given that only the longest isoforms are used?
seqkit
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A look at the Mojo language for bioinformatics
I've been thinking to learn Rust for these use cases, but always get frustrated with the complexity.
I find Go is a great middle-ground though! And now there starts to be a few more bio-related tools and toolkits out there, including:
- https://github.com/vertgenlab/gonomics
- https://github.com/biogo/biogo
- https://github.com/shenwei356/bio
... except from there being some really popular bio tools written in Go, like:
- https://github.com/shenwei356/seqkit
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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
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What are some good examples of well-engineered bioinformatics pipelines?
Seqkit - thoroughly maintained with extensive tutorials and benchmarking info - https://github.com/shenwei356/seqkit
What are some alternatives?
spades - SPAdes Genome Assembler
seqtk - Toolkit for processing sequences in FASTA/Q formats
rnaseq - RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality control.
sage - Proteomics search & quantification so fast that it feels like magic
rush - A cross-platform command-line tool for executing jobs in parallel
juicer - A One-Click System for Analyzing Loop-Resolution Hi-C Experiments
fasql - DuckDB Extension for reading and writing FASTA and FASTQ Files
gatk4-genome-processing-pipeline-azure - Workflows used for processing whole genome sequence data + germline variant calling.