Pipeline for structural variation detection in cohorts

A snakemake pipeline for SV analysis from nanopore genome sequencing

Code and custom scripts relevant to gnomAD-SV (Collins*, Brand*, et al., 2020)

Automatised pipeline of ConsensuSV workflow.

Provides custom Javascript evaluation contexts and the Svelte Compiler as Svelte Stores, for REPLs, IDEs, etc.

SVsim: a tool that generates synthetic Structural Variant calls as benchmarks to test/evaluate SV calling pipelines.

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A long-read SV calling pipeline

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An ensemble structural variant calling pipeline driven by snakemake using multiple SV and CNV callers.

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Simple RISC-V Pipelined processor implemented on SystemVerilog.

Snakemake pipeline for SV discovery and analysis

Genome Structural Variants Detection and Annotation Pipeline. Functions include NGS data QC, both germline and somatic SVs and CNVs detections, SVs and CNVs annotation and visualization.

SV calling pipeline from short reads data

For ADSP 17k SV analysis

SV Python-based pipeline to automatically generate models of coronary arteries based on geometric descriptors

The pipeline for genome assembly, annotation, pangenome construction, SNP and indel calling, and SV genotyping.

Processing of raw Strand-seq data as part of the SV calling pipeline

This repo will host the templates and scripts needed for enabling gatk-sv pipeline on Cromwell EC2 server

ROS2 verison of SVIn Pipeline featuring saving gopro raw videos to ros2 bag, SVIn SLAM, and keyframes extraction.

Fully automated SVM pipeline for classification analysis

Work-in-progress RTL pipelined MIPS processor in SystemVerilog, targeting FPGA deployment on DE10-Lite.

pipeline and script for human-chimp sv affecting cis regulatory elements

Nextflow pipeline to call germline structural variants and copy number variants using DELLY and Manta

SV calling pipeline from ONT data

According to the benchmarking study of Liu et al., six optimal combinations were selected for HiFi read–based and assembly-based SV calling.

Generating svBRDF textures from photos taken with mobile phone

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