batchtma: R package to adjust for batch effects, for example between tissue microarrays
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Updated
Jun 8, 2024 - R
batchtma: R package to adjust for batch effects, for example between tissue microarrays
RADseq Data Exploration, Manipulation and Visualization using R
An R package to test for batch effects in high-dimensional single-cell RNA sequencing data.
Unbiased integration of single cell transcriptomes.
Batch effect adjustment based on negative binomial regression for RNA sequencing count data. Credits: https://github.com/zhangyuqing/ComBat-seq
Visualization and analysis of single-cell RNA-seq data by alternative clustering
R script and Shiny app to perform stratified randomisation
BEER: Batch EffEct Remover for single-cell data
Correction of batch effects in DNA methylation data
Correction of batch effects with BEclear as a command line tool
Tools for Batch Effects Diagnostics and Correction
An implementation of MNN (Mutual Nearest Neighbors) correct in python.
RZiMM: A Regularized Zero-inflated Mixture Model for scRNA-seq Data
A curated list of resources for medical data harmonization algorithms
Uses regression and factor model approach to correct for site effects in fMRI volumes
Embedding to Reference t-SNE Space Addresses Batch Effects in Single-Cell Classification
Batch Effect Correction of RNA-seq Data through Sample Distance Matrix Adjustment
Code accompanying batch effects processing workflow for "omic" data, mainly targeted for proteomics
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