Data analysis made easy. For biologists, especially.
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 […]
“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 […]
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 […]
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 […]
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 […]
We showed a quick and easy way to compare box plots in previous post. Let’s dig deeper into what information you can use to compare two box plots. Overlapping boxes and medians It gets tricky when the boxes overlap and their median lines are inside the overlap range. As always, math comes to […]
Box plots, a.k.a. box-and-whiskers plots, are an excellent way to visualize differences among groups. They manage to carry a lot of statistical details — medians, ranges, outliers — without looking intimidating. But box plots are not always intuitive to read. How do you compare two box plots? The key information […]
1. Violin graph is like box plot, but better Box-and-whisker plots are great. They show medians, ranges and variabilities effectively. They allow comparing groups of different sizes. They are super simple to create and read, so naturally, they are all over the place. But box plots can be misleading. They are not […]
Box plots, a.k.a box-and-whisker plots, are an excellent way to compare groups. They are intuitive: viewers can see samples’ medians, distribution, and variabilities with a quick glance. They allow comparing samples of different sizes; for example, a set of 50 data points with a set of 30. They don’t even […]
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 […]
Writing a scientific paper? Preparing for publication? Making a poster for a conference tomorrow? Let’s face it: People will skim through the body text of your paper/poster, and only look at the figures. We all love figures. They catch eyes, they deliver information effectively, they highlight your results. Figures are […]
