infercnv
Copy Number Variation Detector
Software to detect copy number variations from single-cell RNA-seq data using probabilistic modeling and machine learning algorithms
Inferring CNV from Single-Cell RNA-Seq
579 stars
40 watching
166 forks
Language: R
last commit: almost 2 years agoLinked from 1 awesome list
Related projects:
| Repository | Description | Stars |
|---|---|---|
| A Python library that infers copy number variation events from single-cell transcriptomics data. | 140 | |
| Detects and characterizes copy-number variations in single-cell whole genome sequencing data using computational models | 17 | |
| An interactive R application to detect and annotate hidden sources of variation in single cell RNA-seq data | 7 | |
| Automated tool for classifying cells in scRNA data and inferring copy number profiles of malignant cells. | 94 | |
| A tool for inferring genomic copy number and subclonal structure from single cell RNA sequencing data. | 216 | |
| An R package that uses Bayesian inference and hidden Markov models to detect genetic variations in single-cell RNA-seq data | 98 | |
| A Nextflow-based pipeline for detecting structural variants in whole-genome reads using the Cortex-Var algorithm. | 2 | |
| Detects doublets in single-cell RNA sequencing data by analyzing cell distances and proportions of artificial neighbors | 424 | |
| Analyzes single-cell RNA-seq data to detect allele-specific copy number variations and infer lineage relationships in cancer cells | 171 | |
| Probabilistic analysis tools for single-cell omics data | 1,270 | |
| Determines the native resolution of upscaled material, typically anime, by applying various image processing algorithms. | 224 | |
| Detects cancer metastasis in whole slide images using deep learning and conditional random fields | 757 | |
| Software tool for detecting and analyzing structural variants in genomes | 104 | |
| A package for classifying single-cell RNA-Seq data across species and platforms | 131 | |
| Predicts cell health from morphological profiles using machine learning and image analysis | 35 |