How to Make Sense of Single-cell RNA Sequencing Data? Less is More Thanks to single-cell RNA sequencing (scRNA-seq), researchers are blessed with a trove of information. Yet, this blessing is also a curse in data visualization and further analysis! Since each cell is described by its gene expression profile, our […]
Spatial Transcriptomics Brain Data Is In Demand The spatial gene expression contributes significantly to brain morphology, physiology, and connectivity. However, obtaining spatial transcriptomics brain data has long been a technical challenge. Recently, with continuous breakthroughs in spatial transcriptomics sequencing technique and data analysis tools, spatial human brain single cell RNA-Seq […]
Introduction Why are tumors so resilient against available cancer therapies? One answer lies in intratumoral heterogeneity. Intratumoral heterogeneity describes the diversity in tumor cell populations. Cancer cells exhibit startling distinctions in their types, shape, metabolic activities, transcriptomic profiles, and more. The causes of intratumoral heterogeneity are both heritable (clonal expansion […]
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 […]
Principal component analysis (PCA) has been gaining popularity as a tool to bring out strong patterns from complex biological datasets. We have answered the question “What is a PCA?” in this jargon-free blog post — check it out for a simple explanation of how PCA works. In a nutshell, PCA capture […]
As we are entering the era of Big Data, everyone and their moms seem to be talking about PCA. All the papers you read mention PCA (with lots of jargon, of course). Half of the seminars you’ve been to this month touch on PCA. Your boss/collaborators suggest trying PCA on your data. “What […]
