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README.md

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 # oarfish: transcript quantification from long-read RNA-seq data
 
+`oarfish` is a program, written in `rust`, for quantifying transcript-level expression from long-read (i.e. Oxford nanopore cDNA and direct RNA and PacBio) sequencing technologies. `oarfish` requires a sample of sequencing reads aligned to the *transcriptome* (not the genome). It handles multi-mapping reads through the use of probabilistic allocation via an expectation-maximization (EM) algorithm.  Further, it employs many filters to help discard alignments that may reduce quantification accuracy.  Currently, the set of filters applied in `oarfish` are directly derived from the [`NanoCount`](https://github.com/a-slide/NanoCount)[^Gleeson] tool; both the filters that exist, and the way their values are set (with the exception of the `--three-prime-clip` filter, which is not set by default in `oarfish` but is in `NanoCount`).
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 The usage can be provided by passing `-h` at the command line.
 ```
 Usage: oarfish [OPTIONS] --alignments <ALIGNMENTS> --output <OUTPUT>
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 The input should be a `bam` format file, with reads aligned using `minimap2` against the _transcriptome_. That is, `oarfish` does not currently handle spliced alignment to the genome.  Further, the output alignments should be name sorted (the default order produced by `minimap2` should be fine).
 
 The output is a tab separated file listing the quantified targets, as well as information about their length and other metadata. The `num_reads` column provides the estimate of the number of reads originating from each target.
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+### References
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+[^Gleeson]: Josie Gleeson, Adrien Leger, Yair D J Prawer, Tracy A Lane, Paul J Harrison, Wilfried Haerty, Michael B Clark, Accurate expression quantification from nanopore direct RNA sequencing with NanoCount, Nucleic Acids Research, Volume 50, Issue 4, 28 February 2022, Page e19, [https://doi.org/10.1093/nar/gkab1129](https://doi.org/10.1093/nar/gkab1129)