Author Archives: biomembers

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… Read more »

Venice: a non-parametric test for finding marker genes in single-cell RNA-seq data

In this blog, we introduce Venice a non-parametric approach for finding marker genes in single-cell RNA-seq data. Using a widely adopted benchmarking approach (Wang et al. 2019), Venice obtains the best accuracy among 14 other tools. Venice is also the fastest tool among all the benchmarked methods. Venice is open-source,… Read more »

BioTuring Browser: making published single-cell data really accessible

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… Read more »

Exploring the single-cell atlas of mouse retinal development (Clark et al., 2019): interesting stories revealed

Tiny as they are, retinal cells are extremely abundant and complex. The total population of about 100 million rod photoreceptors is among the most numerous neuron populations in the human body, second to cerebellar granule cells (Masland et al., 2012). Forming a sheet of tissue that is only ~200 μm… Read more »

Single-cell News and Views: March 2019

1. An atlas of acute myeloid leukemia at single-cell resolution Adapted from Galan et. al., 2019 Acute myeloid leukemia (AML) is a cancer characterized by the accumulation of white blood cells in the bone marrow and blood. The disease has been notoriously challenging to study because of its extreme intratumoral… Read more »

A review of Haining Lab’s work: Loss of ADAR1 in tumors overcomes resistance to immune checkpoint blockade

Ever questioned why the immune system does not attack our own double-stranded RNA? Speaking of this, we should not ignore the role of ADAR, the gene that encodes Double-stranded RNA-specific adenosine deaminase enzyme, responsible for converting adenosines to inosines (A -> I editing) in double-stranded RNA (dsRNA) substrates. ADAR was… Read more »

BBrowser: 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… Read more »

k-means clustering algorithm and example

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“I’m clueless” You say, looking at an ocean of unlabeled data, waving in front of you. It is true that the lack of labels can sometimes freak us out, leaving us wondering how to group the data together. But luckily, k-means clustering algorithm is here to rescue, one of the… Read more »

Cell Ranger Problems and Hera-T

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Today we finished the first version of Hera-T, a new single-cell RNA-seq quantification algorithm. We developed Hera-T by improving challenging alignment errors that Cell Ranger has. As a result, Hera-T is more accurate than Cell Ranger. Hera-T is more than 10 times faster than Cell Ranger, while consuming just a small amount of… Read more »

Dos and don’ts for a heatmap color scale

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Heatmaps. We see them all over the scientific journals — the shading matrices that convey meaningful stories. Wanna interpret gene expressions? Draw a heatmap. Gotta examine the correlation among variables? Get it done with a heatmap. It seems that the shading has breathed such life into those cheerless matrices of… Read more »

Proportional Venn diagram in 1 minute with BioVinci

Venn diagram is an excellent tool to visualize the relationship among sets. Ideally, the sizes of the circles and their overlapping area should be proportional to the relationship they convey. It is, however, quite a challenge to create a proportional Venn diagram. No worries: With BioVinci, you can get this job done… Read more »

How to build a hierarchical clustering heatmap with BioVinci?

Heatmap, heatmap everywhere. They are an intuitive way to visualize information from complex data. You see them showing gene expression, phylogenetic distance, metabolomic profiles, and a whole lot more. In this tutorial, we will show you how to perform hierarchical clustering and produce a heatmap with your data using BioVinci. It’s… Read more »