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 NanoCount¹ 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).

Additionally, as a core component of oarfish we are developing novel coverage models that further improve quantification estimates by taking into account the coverage profile of the long mapped reads over the transcripts. A detailed writeup of these coverage models is currently being drafted. In the meantime, if you make use of oarfish, please cite this repository.

The usage can be provided by passing -h at the command line.

accurate transcript quantification from long-read RNA-seq data

Usage: oarfish [OPTIONS] --alignments <ALIGNMENTS> --output <OUTPUT>

Options:
      --quiet                    be quiet (i.e. don't output log messages that aren't at least warnings)
      --verbose                  be verbose (i.e. output all non-developer logging messages)
  -a, --alignments <ALIGNMENTS>  path to the file containing the input alignments
  -o, --output <OUTPUT>          location where output quantification file should be written
  -t, --threads <THREADS>        maximum number of cores that the oarfish can use to obtain binomial probability [default: 1]
  -h, --help                     Print help
  -V, --version                  Print version

filters:
      --filter-group <FILTER_GROUP>
          [possible values: no-filters, nanocount-filters]
  -t, --three-prime-clip <THREE_PRIME_CLIP>
          maximum allowable distance of the right-most end of an alignment from the 3' transcript end [default: 4294967295]
  -f, --five-prime-clip <FIVE_PRIME_CLIP>
          maximum allowable distance of the left-most end of an alignment from the 5' transcript end [default: 4294967295]
  -s, --score-threshold <SCORE_THRESHOLD>
          fraction of the best possible alignment score that a secondary alignment must have for consideration [default: 0.95]
  -m, --min-aligned-fraction <MIN_ALIGNED_FRACTION>
          fraction of a query that must be mapped within an alignemnt to consider the alignemnt valid [default: 0.5]
  -l, --min-aligned-len <MIN_ALIGNED_LEN>
          minimum number of nucleotides in the aligned portion of a read [default: 50]
  -n, --allow-negative-strand
          allow both forward-strand and reverse-complement alignments

coverage model:
      --model-coverage  apply the coverage model
  -b, --bins <BINS>     number of bins to use in coverage model [default: 10]

EM:
      --max-em-iter <MAX_EM_ITER>
          maximum number of iterations for which to run the EM algorithm [default: 1000]
      --convergence-thresh <CONVERGENCE_THRESH>
          maximum number of iterations for which to run the EM algorithm [default: 0.001]
  -q, --short-quant <SHORT_QUANT>
          location of short read quantification (if provided)

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.

References

Footnotes

1. 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 ↩