Structural variation caller using third generation sequencing
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Updated
Apr 2, 2026 - Python
Structural variation caller using third generation sequencing
A PyTorch Basecaller for Oxford Nanopore Reads
Clair3 - Symphonizing pileup and full-alignment for deep learning-based long-read variant calling
pycoQC computes metrics and generates Interactive QC plots from the sequencing summary report generated by Oxford Nanopore technologies basecaller (Albacore/Guppy)
PEPPER-Margin-DeepVariant
Transcript discovery and quantification with long RNA reads (Nanopores and PacBio)
Methylation/modified base calling separated from basecalling.
Identification of differential RNA modifications from nanopore direct RNA sequencing
SquiggleKit: A toolkit for manipulating nanopore signal data
Comprehensive TE insertion identification with WGS/WES data from multiple sequencing technics
Detection of RNA modifications from Oxford Nanopore direct RNA sequencing reads (Liu*, Begik* et al., Nature Comm 2019)
Research release basecalling models and configurations
Pipeline for calling structural variations in whole genomes sequencing Oxford Nanopore data
Pipeline for differential gene expression (DGE) and differential transcript usage (DTU) analysis using long reads
ClairS - a deep-learning method for long-read somatic small variant calling
Recentrifuge: robust comparative analysis and contamination removal for metagenomics
Graph-based assembly phasing
Snakemake pipelines for nanopore sequencing data archiving and processing
ClairS-TO - a deep-learning method for tumor-only somatic variant calling
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