---
title: Introduction
description: What salmon does and how the 2.0 Rust release differs from the C++ tool.
---

salmon[^salmon] estimates transcript-level abundances from RNA-seq reads. Rather
than producing a full base-to-base alignment of every read to a genome, salmon
maps reads directly to a **transcriptome** and uses a probabilistic model —
streaming/online inference followed by an offline EM/VBEM, in the spirit of
eXpress[^express] — to assign multi-mapping reads, correct for technical
biases[^roberts][^alpine], and report abundances in TPM and estimated read
counts.

## The pipeline

1. **`salmon index`** builds a reusable index from a transcriptome FASTA (the set
   of transcript sequences you want to quantify against, optionally with decoy
   sequences such as the genome).
2. **`salmon quant`** maps your reads against that index, fits the experiment
   model (fragment-length distribution, optional sequence/GC/positional bias),
   runs the EM/VBEM optimizer over equivalence classes, and writes the results.
3. **`quant.sf`** is the primary output: one row per transcript with its length,
   effective length, TPM, and estimated read count. Downstream R/Bioconductor
   tools (tximport, tximeta, fishpond, swish) read it directly.

## salmon 2.0 (Rust) vs. C++ salmon

salmon 2.0 is a complete rewrite in Rust. The design goals were speed,
portability, and easy installation, **without** breaking the things downstream
tools depend on.

- **Same outputs.** `quant.sf`, `cmd_info.json`, `lib_format_counts.json`, and
  `aux_info/meta_info.json` are unchanged. Inferential replicates
  (bootstrap/Gibbs) are written in the same format, so tximport/fishpond/swish
  keep working. See the [output format specification](../reference/output-formats/).
- **Single portable binary.** No compiler, Boost, or system libraries to install.
- **A new alignment-free mode** (`--sketch`) for when you want maximum speed.
- **Decoupled mapping and quantification** via the RAD format (`--writeRad` /
  `--rad`, interoperable with piscem `map-bulk`), plus a fully reproducible
  `--deterministic` mode. See [RAD I/O & deterministic quantification](../guides/rad-and-determinism/).
- **One breaking change you must act on:** the index format changed, so **you
  must rebuild your index** with 2.0. Pointing 2.0 at a C++ (pufferfish) index —
  or C++ salmon at a 2.0 index — is detected and rejected with a clear message.

If you are upgrading from C++ salmon, read [Migrating from C++ salmon](../migrating/from-cpp/)
for the full list of changed, removed, and new options.

:::note[Single-cell data]
Single-cell quantification (the old `salmon alevin`) now lives in the
[alevin-fry](https://github.com/COMBINE-lab/alevin-fry) ecosystem. `salmon
alevin` in 2.0 just prints a redirect.
:::

## References

[^salmon]: Patro, R., Duggal, G., Love, M. I., Irizarry, R. A., & Kingsford, C. (2017). Salmon provides fast and bias-aware quantification of transcript expression. *Nature Methods*, 14(4), 417–419. https://doi.org/10.1038/nmeth.4197

[^express]: Roberts, A., & Pachter, L. (2013). Streaming fragment assignment for real-time analysis of sequencing experiments. *Nature Methods*, 10(1), 71–73. https://doi.org/10.1038/nmeth.2251

[^roberts]: Roberts, A., Trapnell, C., Donaghey, J., Rinn, J. L., & Pachter, L. (2011). Improving RNA-Seq expression estimates by correcting for fragment bias. *Genome Biology*, 12(3), R22. https://doi.org/10.1186/gb-2011-12-3-r22

[^alpine]: Love, M. I., Hogenesch, J. B., & Irizarry, R. A. (2016). Modeling of RNA-seq fragment sequence bias reduces systematic errors in transcript abundance estimation. *Nature Biotechnology*, 34(12), 1287–1291. https://doi.org/10.1038/nbt.3682
