OEFinder
Gene identifier
An R-based tool for identifying ordering effect genes in single cell RNA-seq data
Identify ordering effect genes in single cell RNA-seq data
3 stars
3 watching
3 forks
Language: R
last commit: over 8 years ago
Linked from 1 awesome list
Related projects:
Repository | Description | Stars |
---|---|---|
kdkorthauer/scdd | An R package to identify genes with differential distributions in single-cell RNA-seq experiments | 32 |
buenrostrolab/figr | A computational framework that integrates single-cell chromatin accessibility and gene expression data to infer transcriptional regulators of target genes. | 36 |
statgen/demuxlet | A software tool that identifies sample identity and detects multiplets in pooled single cell RNA-seq samples. | 121 |
agitter/single-cell-pseudotime | Catalogs algorithms for estimating the position of cells in a developmental trajectory from single-cell gene expression data | 408 |
zji90/sepa | A tool for analyzing single-cell RNA-seq data to identify gene expression patterns and perform GO enrichment analysis. | 4 |
zjufanlab/sccatch | Automated tool for annotating cell types from single-cell RNA sequencing data based on marker genes | 218 |
statomics/zinbwavezinger | A software framework for integrating zingeR with ZINB-WaVE weights for RNA-seq data analysis | 23 |
kieranrcampbell/embeddr | Analyzes single-cell RNA-seq data using pseudotemporal ordering and clustering | 12 |
gevaertlab/amaretto | An algorithm for identifying cancer driver genes by integrating multi-omics data and penalized regression | 16 |
qsong-github/sclm | A tool to automatically identify co-expressed genes across multiple single-cell RNA-seq datasets | 2 |
teichlab/spatialde | Tools and methods to analyze gene expression data in relation to spatial coordinates | 145 |
cz-ye/decent | A software package that analyzes single-cell RNA-seq data to identify differential gene expression with capture efficiency adjustments | 14 |
dfajar2/bigscale | An analytical framework for analyzing large-scale single-cell data by identifying coexpressed genes and detecting differentially expressed genes across multiple clusters. | 1 |
yeolab/outrigger | Automates detection and quantification of alternative splicing events from RNA seq data using graph databases. | 62 |
inoue0426/drgat | This implementation uses Graph Attention Networks to predict drug response based on genetic influences in heterogeneous networks. | 3 |