G2S3
Gene imputation method
An imputation method that applies graph signal processing to extract gene structure from scRNA-seq data and recover true expression levels by borrowing information from adjacent genes.
G2S3 (Sparse and Smooth Signal of Gene Graph-based imputation)
3 stars
3 watching
0 forks
Language: MATLAB
last commit: over 5 years agoLinked from 1 awesome list
graphsignalprocessingscrna-imputation-methodsscrna-seq
seandavi/awesome-single-cellRelated projects:
| Repository | Description | Stars |
|---|---|---|
 chenmengjie/viper | A software package implementing a method to impute missing values in gene expression data using a penalized regression model | 18 |
 h3abionet/chipimputation | An imputation workflow tool for genomics data analysis | 20 |
 bimsbbioinfo/netsmooth | Improves single cell RNA-seq data by smoothing out noise using prior information from gene interaction networks | 27 |
 lingfeiwang/normalisr | A software framework for analyzing single-cell RNA sequencing data | 18 |
 insilicodb/snp-imputation-nf | A portable and scalable pipeline for imputing missing single nucleotide polymorphism (SNP) data in genetic studies. | 1 |
 su-informatics-lab/dstg | Software implementation of graph-based AI method for decomposing spatial transcriptomics data | 35 |
 zqfang/gseapy | A software package for performing gene set enrichment analysis in various types of biological data. | 580 |
 jamesjcai/scgeatoolbox | A toolset for analyzing single-cell gene expression data from RNA sequencing experiments. | 24 |
 qsong-github/sclm | A tool to automatically identify co-expressed genes across multiple single-cell RNA-seq datasets | 2 |
 zjufanlab/spatalk | An R package that infers cell-cell communication and ligand-receptor-target networks from spatially resolved transcriptomic data | 61 |
 pachterlab/cwgflhgcchap_2021 | Analyzing multiplexed single-cell RNA-seq data from a marine organism, providing tools for preprocessing, clustering, and analysis of gene expression across different cell types. | 2 |
 broadinstitute/tangram | A Python package for aligning single-cell transcriptomic data with spatial gene expression data. | 261 |
 mohuangx/saver | Recover gene expression profiles from noisy single-cell RNA-seq data using regression and empirical Bayes methods. | 109 |
 krishnaswamylab/magic | An algorithm for denoising high-dimensional biological data by learning the manifold structure of the data using graph imputation | 347 |
 cellgeni/scrna.seq.course | An educational resource teaching computational analysis of single-cell RNA-seq data using R and Bioconductor tools | 125 |