Forum:What are the major advances in Bioinformatics since 2016

Question

[Leendert]

Hi all,

I've been out of the field of Bioinformatics/Science since 2016 (decided to persue a career in agriculture; not a smart move), but have recently decided to move back over.

What have I missed? I have to get back up to speed quickly to at least sound interesting in interviews.

Any links to news posts/discussions/apps would be appreciated!

[ATpoint]

I guess not too much has changed. Single-cell is still a hype, multimodal (like scATAC + scRNA from the same cell) assays even more. Beyond that it is still the usual struggle with arbitrary cutoffs, lots of noise, inconclusive results, lack of biological verification and never ending editing of fasta headers. In which field do you work?

[Dunois]

Well AlphaFold2 has been released (here's the paper), so lots of "easy" structure prediction in the future, I guess? They've released a bunch of structures in collaboration with EMBL (here), and if you can get your hands on a good graphics card, you can run on your own sequences.

Answer 1

[Istvan Albert]

From the top of my head, I welcome additions to the list:

Technology

• Long read sequencing PacBio and Nanopore has greatly improved.
• Consensus calling sequencing runs with PacBio can give you near-perfect over 2-3KB long reads that allow you to assemble small genomes with ease.

Concepts

• RNA-Seq Velocity: https://pubmed.ncbi.nlm.nih.gov/30089906/

Improved tooling

• Minimap2: https://academic.oup.com/bioinformatics/article/34/18/3094/4994778
• Kraken2: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1891-0
• Salmon: https://combine-lab.github.io/salmon/

Answer 2

[GenoMax]

Are you primarily a biologist or a computer scientist? If latter you should be able to catch up with whatever you need on the job even if you missed it. If former then answer would be "depends". If you had enough expertise with topics that were around in 2016 then those would still be useful. Things that have taken off since 2016 are alignment free expression quantification, single cell + (any technique that was used for "bulk" samples) and Spatial transcriptomics that you will need to catch up on.