Reference mapping for single-cell genomics
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Updated
Aug 28, 2024 - Jupyter Notebook
Reference mapping for single-cell genomics
R package for the joint analysis of multiple single-cell RNA-seq datasets
Testing differences in cell type proportions from single-cell data.
Harmony framework for connecting scRNA-seq data from discrete time points
Calculation of Reference/Cluster Similarity Spectrum (RSS/CSS)
Digital Cell Sorter (DCS): single cell RNA-seq analysis toolkit. Documentation:
Clone of the Bioconductor repository for the batchelor package.
single cell foundation model for Gene network inference and more
MAAPster is a comprehensive tool to perform transcriptome analysis of human or mouse Affymetrix gene expression data
Methylation array preprocessing.
Detecting and dissecting anomalous anatomic regions in spatial transcriptomics with STANDS
Confounded Domain Adapter
A comparison of data integration methods for single-cell RNA sequencing of cancer samples
M2ASDA
Batman: Batch effect correction via minimum weight MAtchiNg
A similarity-assisted variational autoencoder (saVAE) is a new method that adopts similarity information in the framework of the VAE.
A Python tool for performing downstream analysis on Single-Cell RNA-seq datasets
Comparison of batch correction methods for scRNA-seq data - basically a clone of BatchBench
An R tool to detect and correct batch-effects in gene-expression data (Microarray and bulk-RNAseq))
An R package for the alignment and scaling of LC-MS metabolomics data
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