An optimised re-implementation of the index, call-methylation and eventalign modules in Nanopolish. Given a set of basecalled Nanopore reads and the raw signals, f5c call-methylation detects the methylated cytosine and f5c eventalign aligns raw nanopore signals (events) to the reference k-mers. f5c can optionally utilise NVIDIA graphics cards for acceleration. For best performance and easy usability, it is recommended to use f5c on BLOW5 format. Use slow5tools for FAST5->BLOW5 conversion and blue-crab for POD5->BLOW5 conversion.
First, the reads have to be indexed using f5c index. Then, invoke f5c call-methylation to detect methylated cytosine bases. Finally, you may use f5c meth-freq to obtain methylation frequencies. Alternatively, invoke f5c eventalign to perform event alignment. The results are almost the same as from nanopolish except a few differences due to floating point approximations.
- f5c v1.2 onwards support nanopore R10.4.1 chemistry (must specify –pore r10 if FAST5 input, autodetected for S/BLOW5 input).
- f5c v1.4 onwards support nanopore RNA004 chemistry (make specify –pore rna004 if FAST5 input, autodetected for S/BLOW5 input).
Full Documentation : https://hasindu2008.github.io/f5c/docs/overview Latest release : https://github.com/hasindu2008/f5c/releases/latest Pre-print : https://doi.org/10.1101/756122 Publication : https://doi.org/10.1186/s12859-020-03697-x Supplementary: nanopore_signal_alignment_supplementary_material.pdf
Please cite the following when using f5c in your publications:
Gamaarachchi, H., Lam, C.W., Jayatilaka, G. et al. GPU accelerated adaptive banded event alignment for rapid comparative nanopore signal analysis. BMC Bioinformatics 21, 343 (2020). https://doi.org/10.1186/s12859-020-03697-x
@article{gamaarachchi2020gpu,
title={GPU accelerated adaptive banded event alignment for rapid comparative nanopore signal analysis},
author={Gamaarachchi, Hasindu and Lam, Chun Wai and Jayatilaka, Gihan and Samarakoon, Hiruna and Simpson, Jared T and Smith, Martin A and Parameswaran, Sri},
journal={BMC bioinformatics},
volume={21},
number={1},
pages={1--13},
year={2020},
publisher={BioMed Central}
}