It is the end of 2019. How time flies! It is a good time to reflect what I have achieved during the past year and what to look forward in 2020. I wrote a post for 2018 here. I am not the only one who has impostor syndrome :) It is important to celebrate your small successes/achievements by writing them down.
I taught a snakemake and scRNAseq workshop during the FAS informatics 2-week nanocourse. I love teaching biologists computing skills that I have learned from scratch. Nowadays, almost every biology is computational biology. I also helped/taught lab members in Dulac lab with programming.
I had my first R package scclusteval for estimating cluster stability in single-cell RNAseq data in github and am writing it up for a small paper. I had some changes that have not been committed to github yet. I presented it in the 2019 bioconductor annual meeting which was held in NYC. I met many wonderful tweeps during the conference including Rob Patro, Mike Love, Ansul kundaje, Qian liu (congrats for the new professorship!), Lihua Zhu, Dave Tang, Avi Srivastava and many others. Thanks bioconductor for the travel award! bioconductor 2020 will be in local Boston, so I will see everyone here!
My first co-first author computational paper is still under review after revision. I have my fingers crossed for the reviewers’ comments back. It has tons of experimental data and computational analysis of both in-house and public data. You can have a look in biorxiv https://www.biorxiv.org/content/10.1101/507202v1. I promise to update the README and pipeline once it is accepted :) https://github.com/crazyhottommy/pyflow-ChIPseq.
I started working on scATACseq in March 2019. It is a brand new field and I have learned quite a bit during the journey. I learned the sparsity of the matrix (more sparse than scRNAseq given the nature of the experiment: we only 2 copies of diploid DNA). I wrote some blog posts on it. I am developing an R/bioconductor package to deal with scATACseq data https://github.com/crazyhottommy/scATACutils. I plan to add more functions and improve the documentations. I presented it in the cold spring harbor Single Cell Analyses meeting.It is amazing to see the development of the single-cell field in the past 10 years! I met some awesome people there including Luciano Martelotto and got to see some of my old MD Anderson Colleagues.
I said I would start learning some deep learning in 2019. That did not happen much. Instead, I started watching some linear algebra courses by MIT Gilbert Strang 18.06 and 18.065. I have finished watching 70% of the videos and really enjoyed them. I got a much better idea of matrix dimentionality (along with space and subspace) and matrix factorization(e.g. SVD). I highly recommend youtube videos from 3blue1brown: Essense of linear algebra as well. Thanks Yi Zhang for recommending. At the same time, I slowly picked up Deep learning with R.
I started using docker and singularity for reproducible computing. It is a life-saver for me. Thanks Nathan for helping me along the way.
I finally met Jason Willimas in person together with Damien. Jason is a very nice person. Next time we will treat you when you are in Boston again. I am sure this is in the right category of my success list :)
I am grateful that I am in a such supporting position and I have been learning new things. Thanks everyone who has helped me along the way.
In the coming 2020, I should
learn more stats. I registered one class from Harvard Extension school and will see how it goes. Lacking statistics background hurts me.
do better in data and project management. I will start using dtool.
write some papers up. A good paper is a finished paper. I hear you.
try to be a better human, a better husband and father and then a better researcher.