Single cell Nanopore sequencing data for Genotype and Phenotype
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Updated
May 31, 2024 - Python
Single cell Nanopore sequencing data for Genotype and Phenotype
A snakemake pipeline to call structure variants from ONT data
MetaCC allows scalable and integrative analyses of both long-read and short-read metagenomic Hi-C data
Kmer Analysis of Pileups for Genotyping
A short tandem repeat (STR) genotyping and analysis toolkit for long reads
A tool for refining long-reads binning using kingdom level information
a Python module to manipulate MIDS format.
Assembly and binning of metagenomes
Graph-based assembly phasing
ClairS-TO - a deep-learning method for tumor-only somatic variant calling
🔬 Genotyping tool for genome-edited samples, utilizing nanopore sequencer target sequencing
a deep neural network model for mapping modifications in nanopore Long-read sequencing data
Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics
Assembly and intrahost/low-frequency variant calling for viral samples
Efficient and accurate pathogenicity prediction for coding and regulatory structural variants in long-read genome sequencing
Linear-time de novo Long Read Assembler
ClairS - a deep-learning method for long-read somatic small variant calling
A collection of publications on comparison of high-throughput sequencing technologies.
Clair3-RNA - a long-read small variant caller for RNA sequencing data
This repository is the current repository for our Jones et al. 2024 manuscript titled Long-read RNA sequencing identifies region- and sex-specific C57BL/6J mouse brain mRNA isoform expression and usage.
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