Gene prediction on long reads, aka PacBio and Nanopore, is often impaired by indels causing frameshift. Proovframe detects and corrects frameshifts in coding sequences from raw long reads or long-read derived assemblies.
Proovframe uses frameshift-aware alignments to reference proteins as guides, and conservatively restores frame-fidelity by 1/2-base deletions or insertions of “N/NN”s, and masking of premature stops (“NNN”).
Good results can already be obtained with distantly related guide proteins- successfully tested with sets with <60% amino acid identity.
It can be used as an additional polishing step on top of classic consensus-polishing approaches for assemblies.
It can be used on raw reads directly, which means it can be used on data lacking sequencing depth for consensus polishing - a common problem for a lot of rare things from environmental metagenomic samples, for example.
Requires DIAMOND v2.0.3 or newer for mapping.
# install
git clone https://github.com/thackl/proovframe
# map proteins to reads
proovframe/bin/proovframe map -a proteins.faa -o raw-seqs.tsv raw-seqs.fa
# fix frameshifts in reads
proovframe/bin/proovframe fix -o corrected-seqs.fa raw-seqs.fa raw-seqs.tsvIf you use proovframe and DIAMOND please cite:
- Hackl T, Trigodet F, Murat Eren A, Biller SJ, Eppley JM, Luo E, et al. “proovframe: frameshift-correction for long-read (meta)genomics”, bioRxiv. 2021. p. 2021.08.23.457338. doi:10.1101/2021.08.23.457338
- Buchfink B, Reuter K, Drost HG, “Sensitive protein alignments at tree-of-life scale using DIAMOND”, Nature Methods 18, 366–368 (2021). doi:10.1038/s41592-021-01101-x