cKBET: assessing goodness of batch effect correction for single-cell RNA-seq
Por um escritor misterioso
Last updated 01 agosto 2024
![cKBET: assessing goodness of batch effect correction for single-cell RNA-seq](https://academic.hep.com.cn//article/2024/2095-2228/2095-2228-18-1-181901/thumbnail/FCS-22111-YZ-tu1.png)
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](https://i1.rgstatic.net/publication/335133517_BERMUDA_A_novel_deep_transfer_learning_method_for_single-cell_RNA_sequencing_batch_correction_reveals_hidden_high-resolution_cellular_subtypes/links/5d5448a092851c93b6309037/largepreview.png)
PDF) BERMUDA: A novel deep transfer learning method for single-cell RNA sequencing batch correction reveals hidden high-resolution cellular subtypes
![cKBET: assessing goodness of batch effect correction for single-cell RNA-seq](https://www.researchgate.net/publication/338632187/figure/fig5/AS:963543042109453@1606737971536/Quantitative-evaluation-of-14-batch-effect-correction-methods-using-the-four-assessment_Q320.jpg)
PDF) A benchmark of batch-effect correction methods for single-cell RNA sequencing data
![cKBET: assessing goodness of batch effect correction for single-cell RNA-seq](https://d3i71xaburhd42.cloudfront.net/8aa789a968df640af09d8637e45e1faa55d464dd/12-Figure3-1.png)
PDF] On the widespread and critical impact of systematic bias and batch effects in single-cell RNA-Seq data
![cKBET: assessing goodness of batch effect correction for single-cell RNA-seq](https://www.rna-seqblog.com/wp-content/uploads/2017/04/batch.png)
Removal of Batch Effects from Single-cell RNA-Seq
![cKBET: assessing goodness of batch effect correction for single-cell RNA-seq](https://i1.rgstatic.net/publication/329811560_A_test_metric_for_assessing_single-cell_RNA-seq_batch_correction/links/5c7906bba6fdcc4715a47112/largepreview.png)
A test metric for assessing single-cell RNA-seq batch correction
![cKBET: assessing goodness of batch effect correction for single-cell RNA-seq](https://www.mdpi.com/cancers/cancers-15-03615/article_deploy/html/images/cancers-15-03615-g001.png)
Cancers, Free Full-Text
![cKBET: assessing goodness of batch effect correction for single-cell RNA-seq](https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41467-023-36635-5/MediaObjects/41467_2023_36635_Fig2_HTML.png)
Batch alignment of single-cell transcriptomics data using deep metric learning
![cKBET: assessing goodness of batch effect correction for single-cell RNA-seq](https://media.springernature.com/full/springer-static/image/art%3A10.1038%2Fs41467-023-36635-5/MediaObjects/41467_2023_36635_Fig1_HTML.png)
Batch alignment of single-cell transcriptomics data using deep metric learning
![cKBET: assessing goodness of batch effect correction for single-cell RNA-seq](https://www.biorxiv.org/content/biorxiv/early/2017/10/09/200345/F2.large.jpg)
Assessment of batch-correction methods for scRNA-seq data with a new test metric
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