cKBET: assessing goodness of batch effect correction for single-cell RNA-seq
Descrição
lt;p>Single-cell RNA sequencing reveals the gene structure and gene expression status of a single cell, which can reflect the heterogeneity between cells. However, batch effects caused by non-biological factors may hinder data integration and downstream analysis. Although the batch effect can be evaluated by visualizing the data, which actually is subjective and inaccurate. In this work, we propose a quantitative method cKBET, which considers the batch and cell type information simultaneously. The cKBET method accesses batch effects by comparing the global and local fraction of cells of different batches in different cell types. We verify the performance of our cKBET method on simulated and real biological data sets. The experimental results show that our cKBET method is superior to existing methods in most cases. In general, our cKBET method can detect batch effect with either balanced or unbalanced cell types, and thus evaluate batch correction methods.</p>
cKBET: assessing goodness of batch effect correction for single-cell RNA-seq
Fast, sensitive and accurate integration of single-cell data with Harmony
A benchmark of batch-effect correction methods for single-cell RNA sequencing data, Genome Biology
cKBET: assessing goodness of batch effect correction for single-cell RNA-seq
A benchmark of batch-effect correction methods for single-cell RNA sequencing data
How to Batch Correct Single Cell. Comparing batch correction methods for…, by Nikolay Oskolkov
A benchmark of batch-effect correction methods for single-cell RNA sequencing data, Genome Biology
PDF) BEENE: Deep Learning based Nonlinear Embedding Improves Batch Effect Estimation
PDF) A benchmark of batch-effect correction methods for single-cell RNA sequencing data
A benchmark of batch-effect correction methods for single-cell RNA sequencing data, Genome Biology
PDF] Projected t-SNE for batch correction
A benchmark of batch-effect correction methods for single-cell RNA sequencing data, Genome Biology
PDF) A geometrical approach based on PCA to benchmark the algorithms of batch effect correction applied to the integration of RNA-Seq data
PDF) scBatch: Batch Effect Correction of RNA-seq Data through Sample Distance Matrix Adjustment
de
por adulto (o preço varia de acordo com o tamanho do grupo)
