Showing posts from 2017

Minitalk: on Excel Gene Name Errors

It was great to visit the Monash Clayton Bioinformatics team led by David Powell today to introduce myself and speak about a topic very close to my heart!

Slides below:

Also let me know what you think of the new theme of the blog in the comments below. BTW Just realised this is my 100th post! Yay for me! Thanks for reading!

How NGS is transforming medicine

Last month, I gave a talk at our departmental meeting, describing in general terms how high throughput sequencing technology was having real impacts in medicine and human health, as well as some emerging trends to watch out for in coming years.

Here's the link

Introducing the ENCODE Gene Set Hub

TL;DR We curated a bunch of ENCODE data into gene sets that is super useful in pathway analysis (ie GSEA).
Link to gene sets and data:
Poster presentation: DOI:10.13140/RG.2.2.34302.59208

Now for the longer version. Gene sets are wonderful resources. We use them to do pathway level analyses and identify trends in data that lead us to improved interpretation and new hypotheses. Most pathway analysis tools like GSEA allow us to use custom gene sets, this is really cool as you can start to generate gene sets based on your own profiling work and that of others.

There is huge value in curating experimental data into gene sets, as the MSigDB team have demonstrated. But overall, these data are under-shared. Even our group is guilty of not sharing the gene sets we've used in papers. There have been a few papers where we've used gene sets curated  from ENCODE transcription factor binding site (TFBS) data to understand which TFs were drivi…