Computational biology and genomics
A quick guide to organizing computational biology projects has been published over 8 years ago but the main messages are still very relevant (perhaps even more so nowadays given the exponential increase in biological data). In a nutshell, computational biology projects need to be organised so that we can share and reproduce our work in…
Updated 2018 March 23rd for R-3.4.4 I use a lot of shortcuts provided by GNU Readline. I recently compiled R without Readline support and it was almost unusable! This was because I ran into the error: configure: error: –with-readline=yes (default) and headers/libs are not available To circumvent this I compiled R by running: ./configure –with-readline=no…
I was going to write a post on using the Seurat alignment method as a batch correction tool but as it turned out the two datasets that I chose didn’t seem to have strong batch effects! I heard about the alignment method sometime last year but was motivated to try it out after listening to…
From the original paper describing the Gene Set Enrichment Analysis: The goal of GSEA is to determine whether members of a gene set S tend to occur toward the top (or bottom) of the list L, in which case the gene set is correlated with the phenotypic class distinction.
The Variant Effect Predictor (VEP) tool can be used for annotating variants with respect to custom annotation sources. This is useful if gene models of interest are not represented in the Ensembl or RefSeq databases. To get started, first install VEP since it takes some time.
A popular toolset used for analysing RNA-seq data is the tuxedo suite, which consists of TopHat and Cufflinks. The suite provided a start to finish pipeline that allowed users to map reads, assemble transcripts, and perform differential expression analyses. A newer “tuxedo suite” has been developed and is made up of three tools: HISAT, StringTie,…
I reached a million views on 2017 September 27th. Near the start of September, I had wondered if I would reach a million before my 7th anniversary, which is today. I used the traffic to this site to predict when I would hit the mark. Not the best fit. Use only 2017 data to predict….
Monocle is an R package developed for analysing single cell gene expression data. Specifically, the package provides functionality for clustering and classifying single cells, conducting differential expression analyses, and constructing and investigating inferred developmental trajectories. The toolkit provides various alternative approaches for each analysis, hence your workflow may differ from the approach I’ve taken in…
I wrote about the Rand Index (RI) and the Adjusted Rand Index (ARI) in the last two posts but how do we interpret the indices and how are they different? The RI is: where $$a$$ and $$b$$ are the number of times a pair of items was clustered concordantly in two different sets. I wrote…
In my last post, I wrote about the Rand index. This post will be on the Adjusted Rand index (ARI), which is the corrected-for-chance version of the Rand index: