cfDNApipe: A comprehensive quality control and analysis pipeline for cell-free DNA high-throughput sequencing data
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Updated
Aug 18, 2022 - Python
cfDNApipe: A comprehensive quality control and analysis pipeline for cell-free DNA high-throughput sequencing data
R package to work with ctDNA sequencing data
FinaleToolkit is a package and standalone program to extract fragmentation features of cell-free DNA from paired-end sequencing data.
This is the official development repository for BaseVar, which call variants for large-scale ultra low-pass (<1.0x) WGS data, especially for NIPT data
High-intensity sequencing reveals the sources of plasma circulating cell-free DNA variants
Important papers relating to the biology of cell free DNA
R package and vignette to denoise metagenomic cell-free DNA sequencing data.
LIONHEART detects cancer from whole genome sequenced plasma cell-free DNA.
As a tool for cancer subtype prediction, Keraon uses features derived from cell-free DNA (cfDNA) in conjunction with PDX reference models to perform both classification and heterogenous phenotype fraction estimation.
This is the official development repository for BaseVar, which call variants for large-scale ultra low-pass (<1.0x) WGS data, especially for NIPT data
cfDNA methylation probe design from mybaits targeted sequencing
This repository serves as a dedicated space for housing the codebase used in our publication for cfGWAS reveal genetic basis of cell-free DNA features. It is intended to provide researchers with access to the methodologies and algorithms employed in our study, facilitating further research and analysis in the field of genetic.
Cancer estimation based on nucleosomes: Analysis of proportion of circulating tumor DNA fragments compared to nucleosome references.
Plasma cell-free DNA hydroxymethylomes discriminate disease state in EGFR-mutant non-small cell lung cancer.
Code for SCLC cfMeDIP-seq PRIME as described in the following paper: doi: 10.1016/j.isci.2022.105487
Integrative analysis of cfDNA methylation and miRNA expression for early lung cancer detection using machine learning.
This repository contains the code used in the following publication: doi.org/10.1016/j.isci.2022.105487
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