R script and Shiny app to perform stratified randomisation
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Updated
Aug 28, 2023 - R
R script and Shiny app to perform stratified randomisation
Package for analyzing batch effects in single cell RNA sequencing (scRNA-seq) analysis and predicting their impact on downstream analysis.
Correction of batch effects with BEclear as a command line tool
RZiMM: A Regularized Zero-inflated Mixture Model for scRNA-seq Data
Batch effect adjustment based on negative binomial regression for RNA sequencing count data. Credits: https://github.com/zhangyuqing/ComBat-seq
Correction of batch effects in DNA methylation data
batchtma: R package to adjust for batch effects, for example between tissue microarrays
Analyzing batch effects in single cell RNA sequencing (scRNA-seq) analysis and predicting their impact on downstream analysis.
Unbiased integration of single cell transcriptomes.
Mitigating the adverse impact of batch effects in sample pattern detection
Code accompanying batch effects processing workflow for "omic" data, mainly targeted for proteomics
Detecting hidden batch factors through data adaptive adjustment for biological effects
Tools for Batch Effects Diagnostics and Correction
BEER: Batch EffEct Remover for single-cell data
Batch Effect Correction of RNA-seq Data through Sample Distance Matrix Adjustment
Batch effect adjustment based on negative binomial regression for RNA sequencing count data
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