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Tag Archives: single cell analysis software

BioTuring Cell Search: a new tool to search for similar populations in public single-cell data sets

A machine learning model for cell type classification? When analyzing single-cell transcriptomic data, scientists often perform cell type annotations by checking individual marker genes. However, marker genes are not even consistent among different literature sources. Six months ago, armed with the largest curated single-cell transcriptomic data, BioTuring single-cell team naively […]

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 […]

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 […]

BioTuring Browser: the software to resolve major challenges in single-cell RNA-seq data analysis

Single-cell RNA-seq technologies have opened up a completely new era for transcriptomic studies. For the first time ever, scientists can look at individual transcriptomic profiles of millions of cells, and better understand how each cell functions in a tissue. Yet science is confronting bigger challenges analyzing these massive amounts of […]