single-cell datasets Archives - BioTuring's Blog
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Tag Archives: single-cell datasets

BioTuring Data Science Platform: A Jupyter notebook library of latest methods for single-cell analysis in R and Python
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Did you know that by the end of 2021, the number of tools for single-cell RNA-sequencing (scRNA-seq) data analysis has passed 1,000? (Zappia and Theis, 2021) This massive resource accelerates the exploration of single-cell data. At the same time, the plethora of options poses several challenges for researchers, such as:   […]

The Maze of Differential Gene Expression Analysis in Single-cell RNA-Seq
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Single-cell RNA sequencing (scRNA-seq) unfolds biological processes at individual cell resolution. One key step that makes up the power of scRNA-seq is the spotting of differentially expressed (DE) genes. However, characteristics like high heterogeneity and data sparsity (high zero counts) are the main obstacles in finding DE genes in scRNA-seq […]

Batch Effect in Single-Cell RNA-Seq: Frequently Asked Questions and Answers
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One essential step in the preprocessing of single-cell RNA-Seq data (scRNA-seq) is batch effect correction. However, much confusion remained around this step. In this article, let’s address the most frequently asked questions about handling batch effect in single-cell RNA-Seq. .  What is Batch Effect in Single-cell RNA-Seq? Batch effect happens […]

scRNA-Seq Cell Type Annotation: Common Approaches and Tools
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Assigning cell type identity to cells is a basic yet vital step required in single-cell RNA Sequencing data analysis (scRNA-Seq), often done after dimensionality reduction and scRNA-Seq clustering . If you have successfully captured informative clusters, it’s time to face an even harder challenge: identify what cell type or cell […]

Interactive CITE-Seq data analysis with BioTuring Browser

Nominated as Method of the year by Nature in 2019, single-cell multimodal omics has enabled scientists to uncover many facets of the cells by simultaneously measuring multiple modalities in one single-cell experiment. One candidate for multimodal analysis is CITE-Seq, a technique that layers cell surface protein information on top of […]

Exploring “Dysfunctional CD8 T Cells Form a Proliferative, Dynamically Regulated Compartment within Human Melanoma” (Li et al., 2018) | BioTuring Cellpedia

Welcome to our new BioTuring Cellpedia series! We are excited to introduce a new blog series that provides you with an overview of some interesting datasets indexed in BioTuring Browser public repository, a platform for instant access and reanalysis of published single-cell RNA-seq data. Details on their experimental designs and […]

BioTuring Single-cell Browser: a modern interactive single-cell database with 3D visualizations and downstream analyses

Single-cell sequencing technologies have brought up an unprecedented level of resolution to omics studies with extremely detailed views into individual cells’ expression patterns. With the emergence of drop-based sequencing methods, the resolution now even comes with scale and efficiency. In a single experiment, scientists can now profile hundreds of thousands […]