Salmon is a wicked-fast program to produce a highly-accurate, transcript-level quantification estimates from RNA-seq data. Salmon achieves is 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 differnt 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. Alevin adds to this functionality with a fast end-to-end pipeline to process droplet-based single-cell RNA sequencing data, performing cell barcode detection, read mapping, unique molecular identifier (UMI) deduplication, gene count estimation, and cell barcode whitelisting. |
hg clone https://toolshed.g2.bx.psu.edu/repos/bgruening/alevin
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Name | Description | Version | Minimum Galaxy Version |
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Quantification and analysis of 3-prime tagged-end single-cell sequencing data | 1.10.1+galaxy2 | 20.01 |