cnv

🌲 An easy-to-use and scalable toolkit for genomic alteration signature (a.k.a. mutational signature) analysis and visualization in R https://shixiangwang.github.io/sigminer/reference/index.html

Annotation and Ranking of Structural Variation

ClassifyCNV: a tool for clinical annotation of copy-number variants

cfDNApipe: A comprehensive quality control and analysis pipeline for cell-free DNA high-throughput sequencing data

Integrated copy number variation detection toolset

What is true, thank you, ernestly. A large variant benchmarking tool analogous to hap.py for small variants.

Copy number estimation of highly duplicated sequences

This repository contains the code to run the ASCETS arm-level copy number events caller for targeted sequencing data. ASCETS produces arm-level copy-number variant calls and arm-level weighted average log2 segment means from segmented copy number data.

Official code repository for JAX-CNV

Short reads aligner for NIPT/CNV

A fork of the project Excavator2 from sourceforge.

R Package to compare copy number variant (CNV) results from multiple samples/methods

Dzyaloshinskii-Moriya interaction for crystallographic class Cnv

A pipeline for detecting Somatic Insertion of DE novo RETROcopies

eXome Hidden Markov model (XHMM) - Copy Number Variants (CNVs) from Whole Exome Sequencing Data

X11 related utilities for hts

Materials & Methods for CNV calling with Genalice software against a benchmark dataset

肿瘤体细胞突变检测流程（组织、cfDNA均可，需要有对照）

Workflow for running PennCNV with Illumina platform final report

MSDS Thesis - Pan-Collagen Survival Analysis of CNV in Ovarian Cancer

Using Convolutional Neural Networks to model an association between a genomic sequence and the number of sequenced reads that align to it

Hidden Markov Model based Copy number caller

TCGA hg19 and hg38 data downloader.

Workflow for running PennCNV with Affymetrix platform files

Bioinformatics CNV Detection with Random Forest Model

A tool to call CNV (Copy Number Variation) from bulk ATAC-Seq data

This project compares two learning paradigm, namely transfer-learning and self-supervised learning in a classification task of three retina disorders CNV, DME and DUSEN in addition to the normal condition using an OCT B-scans

Workflow for Sequenza, cellularity and ploidy

A new CNV calling method for DNA-seq data

An R package to integrate and analyze CNV calling results from multiple methods in a uniformed and standardized manner