Input for batch-corrected data using Harmony · Issue #10 · neurorestore/Augur · GitHub
scATAC-seq data integration • Signac
Single-cell integration benchmarking
Fast, sensitive and accurate integration of single-cell data with Harmony | Nature Methods
36. Batch correction — Single-cell best practices
about batch correction in scRNA-seq
Harmony single cell integration — RunHarmony • harmony
Quick start to Harmony • harmony
Fast, sensitive and accurate integration of single-cell data with Harmony | Nature Methods
A benchmark of batch-effect correction methods for single-cell RNA sequencing data | Genome Biology | Full Text
A benchmark of batch-effect correction methods for single-cell RNA sequencing data | Genome Biology | Full Text
Fast, sensitive and accurate integration of single-cell data with Harmony | Nature Methods
Single-cell RNA-seq Workshop: <b style="font-size:45px;">Dataset alignment and batch correction</b>
8 Batch effect correction | Analysis workflow for IMC data
Benchmarking atlas-level data integration in single-cell genomics | Nature Methods
7 Normalization, confounders and batch correction | Analysis of single cell RNA-seq data
Batch Effect Correction in Chromium Single Cell ATAC Data - 10x Genomics
A benchmark of batch-effect correction methods for single-cell RNA sequencing data | Genome Biology | Full Text
UMAPs before (a) and after batch correction using (b) Harmony, (c)... | Download Scientific Diagram
A benchmark of batch-effect correction methods for single-cell RNA sequencing data | Genome Biology | Full Text
A benchmark of batch-effect correction methods for single-cell RNA sequencing data | Genome Biology | Full Text
Are batch effects still relevant in the age of big data?: Trends in Biotechnology
Fast, Sensitive, and Accurate Integration of Single Cell Data • harmony
Quick start to Harmony • harmony
Genome Biology on X: "Tran, Ang, Chevrier, Zhang, Chen and co present a benchmark for batch effect correction methods for scRNA-seq data, to allow integration of different batches. Benchmarked on 10 datasets
