CALISTA
Cell lineage analysis tool
Analyzes single cell expression data to infer cellular lineages and clustering structures
CALISTA: Clustering And Lineage Inference in Single Cell Transcriptional Analysis
9 stars
5 watching
2 forks
Language: HTML
last commit: almost 6 years ago
Linked from 1 awesome list
network-analysissingle-cell-analysis
Related projects:
Repository | Description | Stars |
---|---|---|
| An R package for identifying clonal structures from single-cell RNA sequencing data using Bayesian methods. | 59 |
| Infers gene regulatory networks from time-stamped single cell transcriptional expression profiles using a statistical method | 12 |
| Software for inferring evolutionary lineage of tumor cells from single cell copy number profiles | 17 |
| A toolkit for single cell sequencing analysis with methods for normalization and clustering of RNA sequencing data. | 3 |
| Analyzes single-cell RNA-seq data to detect allele-specific copy number variations and infer lineage relationships in cancer cells | 171 |
| An integrated Bayesian hierarchical model to analyze single-cell sequencing data | 84 |
| An open-source software framework for analyzing single-cell RNA sequencing data and predicting gene networks | 35 |
| An exploratory tool for analyzing intercellular communication from single-cell transcriptional data. | 12 |
| A software tool for analyzing single-cell DNA sequencing data to reconstruct copy number events and cell histories in cancer research. | 20 |
| Probabilistic analysis tools for single-cell omics data | 1,270 |
| Automated method for identifying putative cell types from single-cell RNA-seq data using clustering and machine learning | 94 |
| An interactive software tool for analyzing single-cell omics data | 32 |
| A computational tool for analyzing single cell sequencing data to infer fitness landscapes of cancer cell populations. | 5 |
| Automated tool for classifying cells in scRNA data and inferring copy number profiles of malignant cells. | 94 |
| An algorithmic framework for inferring cell lineages from gene expression data through multiple rounds of downsampling and clustering, followed by consensus clustering and graph construction. | 1 |