Group Leader, Genome Institute of Singapore. Working on computational methods for long read RNA-Seq. The team tweets from @goekelab
Nov 11, 2022 • 11 tweets • 5 min read
Identification of m6A has been possible for some time using @nanopore direct RNA-Seq. Today we published m6Anet, achieving high accuracy single base, single molecule resolution nature.com/articles/s4159…
What is m6Anet, and why this makes a big difference🧵#biodata22@naturemethods
m6ANet (github.com/GoekeLab/m6anet) implements a supervised machine learning appraoch, i.e. it uses labeled data (direct RNA-Seq data at known m6A sites) for training a model that then makes predictions in the absence of any labels
Apr 23, 2021 • 10 tweets • 5 min read
The preprint from the Singapore Nanopore Expression Project (SG-NEx) is online! The SG-NEx data is a systematic resource for @nanopore long read RNA-Sequencing, including direct RNA, cDNA, and PCR cDNA with matched short read data and spike-in RNAs. 1/n biorxiv.org/content/10.110…
First of all, if you want to study the transcriptome, you want to use long reads (they are designed for this). Sometimes that is not possible (throughput, RNA input requirements, and no experience in data processing and analysis are the most obvious reasons).
