Single-cell RNA-seq tutorials Archives - BioTuring's Blog
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Category Archives: Single-cell RNA-seq tutorials

Explore 10X Visium Spatial Transcriptomics data at ease with BioTuring Browser

Cells don’t function independently. They belong to a complex and interconnected network. This makes gene expression profiling of individual cells not enough for understanding their activities and crosstalk in the tissue context.  Like a marriage between imaging and RNA sequencing, Spatial Transcriptomics is a revolutionized method to map gene activity […]

A tiny world inside non-small cell lung cancer revealed by single-cell omics: 35 cell types, and their marker genes

Take a non-small cell lung tumor. What do we see? To answer this challenging question, a lot of single-cell omics experiments have been conducted, yielding significant insights into the heterogeneity of non-small cell lung cancer (NSCLC) microenvironment. While each successfully characterizes a facet of this ecosystem, until now no work […]

Immunoglobulin genes up-regulated in lung adenocarcinoma infiltrating T cells: A report from BioTuring lung cancer single cell database

Highlights: In every biology textbook, expression of the B cell receptor (BCR) defines B cells, and the T cell receptor (TCR) defines T cells. However, in 2019, Ahmed et al. discovered a strange cell population in Type I Diabetes that coexpresses the BCR and TCR, and key lineage markers of […]

How to explore “Characterizing smoking-induced transcriptional heterogeneity in the human bronchial epithelium at single-cell resolution” (Duclos et. al 2019) | BioTuring Cellpedia

Multiple studies have shown smoking’s effects on the human bronchi. However, few have characterized its precise impact at cellular resolution. Published recently on Science Advances, a study by Duclos and colleagues has employed single-cell RNA sequencing into exploring the cellular changes in the human bronchial epithelium between current and never […]

A sub-clustering tutorial: explore T cell subsets with BioTuring Single-cell Browser

Single-cell RNA sequencing technologies have enabled many exciting discoveries of novel cell types and sub-types, such as the rosehip neurons (Boldog et al., 2018), disease-associated microglia (Keren-Shaul et al., 2017) and lipid-associated macrophages (Jaitin, Adlung, Thaiss, Weiner and Li et al., 2019). While sub-clustering cell populations is essential to find […]

A new tool to interactively visualize single-cell objects (Seurat, Scanpy, SingleCellExperiments, …)

Seurat (Butler et. al 2018) and Scanpy (Wolf et. al 2018) are two great analytics tools for single-cell RNA-seq data due to their straightforward and simple workflow. However, for those who want to interact with their data, and flexibly select a cell population outside a cluster for analysis, it is […]

4 simple steps to perform differential expression analysis in single-cell data using BioTuring Browser

In single-cell data analysis, it is critical to understand how gene expression varies among different cell types, tissue compartments, conditions, or different patients. Although many tools and methods have been developed to support single-cell differential expression analysis, they all require some basic coding skills. In this blog, we show you […]