Try out alevin (salmon's single-cell processing module)! Get started with the tutorial
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Below, you can find download some pre-processed transcriptomes for common species (if you have a particular species or a particular annotation request, let us know). You can easily build your own decoy-enhanced transcriptome using the the genereateDecoyTranscriptome.sh script from the SalmonTools repository. However, we are providing these for convenience. Below, you can simply download the file in the "transcriptome with decoys" column, and unzip the archive with tar xzvf. Each decompressed directory contains a gentrome.fa file and decoys.txt file that can be provided to salmon as:
$ salmon index -t gentrome.fa -d decoys.txt -i combined_index
| description | transcriptome with decoys | link to base genome | link to annotation |
|---|---|---|---|
| human (GENCODE v29) | human_GENCODEv29.tar.gz | GRCh38.primary_assembly.genome.fa.gz | gencode.v29.annotation.gtf.gz |
| mouse (GENCODE vM21) | mouse_GENCODEvM21.tar.gz | GRCm38.primary_assembly.genome.fa.gz | gencode.vM21.annotation.gtf.gz |
| human (ensembl) | human.tar.gz | Homo_sapiens.GRCh38.dna.toplevel.fa.gz | Homo_sapiens.GRCh38.91.gtf.gz |
| mouse (ensembl) | mouse.tar.gz | Mus_musculus.GRCm38.dna.toplevel.fa.gz | Mus_musculus.GRCm38.91.gtf.gz |
| drosophila (ensembl) | drosophila.tar.gz | Drosophila_melanogaster.BDGP6.dna.toplevel.fa.gz | Drosophila_melanogaster.BDGP6.91.gtf.gz |
| zebrafish (ensembl) | zebrafish.tar.gz | Danio_rerio.GRCz11.dna.toplevel.fa.gz | Danio_rerio.GRCz11.96.gtf.gz |
Salmon is a wicked-fast program to produce a highly-accurate, transcript-level quantification estimates from RNA-seq data. Salmon achieves its accuracy and speed via a number of different innovations, including the use of quasi-mapping (accurate but fast-to-compute proxies for traditional read alignments), and massively-parallel stochastic collapsed variational inference. The result is a versatile tool that fits nicely into many different pipelines. For example, you can choose to make use of our quasi-mapping algorithm by providing Salmon with raw sequencing reads, or, if it is more convenient, you can provide Salmon with regular alignments (e.g. an unsorted BAM file produced with your favorite aligner), and it will use the same wicked-fast, state-of-the-art inference algorithm to estimate transcript-level abundances for your experiment.
Give salmon a try! You can find the latest binary releases here.
The current version number of the master branch of Salmon can be found here
NOTE: Salmon works by (quasi)-mapping sequencing reads directly to the transcriptome. This means the Salmon index should be built on a set of target transcripts, not on the genome of the underlying organism. If indexing appears to be taking a very long time, or using a tremendous amount of memory (which it should not), please ensure that you are not attempting to build an index on the genome of your organism!
The documentation for Salmon is available on ReadTheDocs, check it out here.
Salmon is, and will continue to be, freely and actively supported on a best-effort basis. If you need industrial-grade technical support, please consider the options at oceangenomics.com/support.
You can chat with the Salmon developers and other users via Gitter!
