“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 »
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 »
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… Read more »
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… Read more »
