After earning my PhD in bioinformatics/biostatistics from the National University of Singapore, I was happy with the successful completion of my two major projects. However, as a math graduate (my undergraduate major), I couldn’t shake the feeling that those projects may not have been as “mathematical” as I had initially anticipated. Much of my time was spent cleaning up raw omics datasets, including maf files, RNAseq counts data, LFQ and TMT proteomics quantifications.

My advisor, a brilliant statistical mind, reassured me that my skills were not to be compared with those of CS or math PhDs. Rather, my analytical eyes, honed over five years of working with a plethora of omics datasets, would allow me to make significant discoveries that even “smart” CS and math people might struggle to approach.

Encouraged by my advisor’s words, I applied for and landed a postdoctoral position at the University of Michigan. To my great fortune and gratitude, I was given the opportunity to lead a large tumor cohort study as the primary bioinformatician. Immediately, I was tasked with managing genomics, transcriptomics, proteomics, and metabolomics data from over 200 patient samples, which I had to filter, normalize, impute, and interpret.

Working closely with over 20 collaborators, I discovered that I had a natural talent for the job at hand. My analytical eyes proved to be an asset in navigating through the extensive and, at times, messy datasets. Through this experience, I found a newfound appreciation for my own abilities and grew to love myself more.

I always hoped to document what I have learned throughout the years, but was unsure of how to do so. As fate would have it, I met Tommy, a generous computational biologist who loves to share knowledge. He encouraged me to start my own blog, and so here am I, sharing my humble experience in bioinformatics with you.