Nanocaller
Description
NanoCaller is a computational method that integrates long reads in deep convolutional neural network for the detection of SNPs/indels from long-read sequencing data. NanoCaller uses long-range haplotype structure to generate predictions for each SNP candidate variant site by considering pileup information of other candidate sites sharing reads. Subsequently, it performs read phasing, and carries out local realignment of each set of phased reads and the set of all reads for each indel candidate variant site to generate indel calling, and then creates consensus sequences for indel sequence prediction.
Environment Modules
Run module spider nanocaller to find out what environment modules are available for this application.
System Variables
- HPC_NANOCALLER_DIR - installation directory
Citation
If you publish research that uses nanocaller you have to cite it as follows:
Ahsan, M.U., Liu, Q., Fang, L. et al. NanoCaller for accurate detection of SNPs and indels in difficult-to-map regions from long-read sequencing by haplotype-aware deep neural networks. Genome Biol 22, 261 (2021). https://doi.org/10.1186/s13059-021-02472-2.