Tao Liu is an Assistant Professor at the School of Medicine and Biomedical Sciences of the SUNY University of Buffalo, The State University of New York, the largest public university in the northeastern United States.
Dr. Liu received a PhD from the Institute of Biophysics at the Chinese Academy of Sciences in 2007, majoring in Bioinformatics. He followed that with a postdoctoral fellowship at the Dana-Farber Cancer Institute, Harvard School of Public Health (2012). While at Harvard Tao Liu created MACS - Model Based Analysics of Chip-Seq a tool to predict binding locations in chip-seq data.
While the application domain of peak calling for chip-seq data has no shortage of options MACS is a tool that excels where other options falter - usability - a recurrent theme when looking for patterns for what makes software successful. MACS is easy to install and run, performs well even when not tuned to a particular use case and produces simple outputs that are easy to interpret. It is one of the tools that ENCODE project selected for processing their chip-seq data.
The Github repository for MACS: https://github.com/taoliu/MACS
Tao Liu of MACS
What hardware do you use?
Macbook Air and iMac for development. Linux server of my own lab for the most of analysis. An University cluster. AWS.
What is your text editor?
What software do you use for your work?
Mainly linux command line tools. Besides my own tools, bedtools, UCSC toolkits and samtools are the most frequently used ones. By the way, I like Debian, since "APT has Super Cow Powers”.
What do you use to create plots and charts?
The ggplots2 library in R. I also write Python codes to generate R scripts. Use Adobe Illustrator for tweaking.
I use a Wacom Intuos 3 with Autodesk Sketchbook express for doodling.
What do you consider the best language to do bioinformatics with?
I recommend Python to anyone who begins programming. Python is elegant and easy to learn. But it’s fun to learn more programming languages just as natural languages. To choose one in real work, it depends on the actual project. Usually I write Python for algorithm prototyping, then code the most time consuming parts in cython or C. For mini projects, to write BASH and Perl/AWK is more convenient.
What bioinformatics tools/software do not get enough recognition?
In my point of view, bioinformatics field is full of redundant works so by average every work doesn’t get enough recognition :)
Just to avoid reinventing wheels, build your own racing car!
See all post in this series https://www.biostars.org/t/uses-this/
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