I have 7 packages published within the Bioconductor project.
A new package meshes was included in BioC 3.4 release.
leading edge and core enrichment
Leading edge analysis reports Tags to indicate the percentage of genes contributing to the enrichment score, List to indicate where in the list the enrichment score is attained and Signal for enrichment signal strength.
It would also be very interesting to get the core enriched genes that contribute to the enrichment.
Now DOSE, clusterProfiler and ReactomePA all support leading edge analysis and report core enriched genes.
发现Youtube上有一个视频叫Evolution of clusterProfiler, 是Landon Wilkins用Gource做的。于是我也来玩一下，看一下自己这几年码代码的过程。
Today is my birthday and it happened to be the release day of Bioconductor 3.3. It’s again the time to reflect what I’ve done in the past year.
In BioC 3.2 release, all my packages including GOSemSim, clusterProfiler, DOSE, ReactomePA, and ChIPseeker switch from Sweave to R Markdown for package vignettes.
GOSemSim
To make it consistent between GOSemSim and clusterProfiler, ‘worm’ was deprecated and instead we should use ‘celegans’. As usual, information content data was updated.
The ENCODE consortium has recently published a great paper on Gene Expression from the GTEx dataset. A criticism raised on pubpeer is that the gene ontology enrichment analysis was done with DAVID which has not been updated in the last five years.
The result is shown below:
This is a feature request from clusterProfiler user. It’s similar to what I implemented in clusterProfiler for comparing biological themes. For comparing different enrichment results, the x-axis represent different gene clusters while for a single enrichment result, the x-axis can be gene count or gene ratio. This is actually similar to traditional barplot, with dot position as bar height and dot color as bar color. But dotplot can represent one more feature nicely by dot size and it can be a good alternative to barplot.
