🚨 Dealing with sparse, noisy single-cell DNA methylation data (scBS-seq)? Check out #scDMV. It uses a zero-one inflated beta mixture model to tackle the excess of 0s/1s and low coverage, boosting accuracy in identifying differentially methylated regions (DMRs).

On the art of great article titles: this one’s dedicated to all the Reviewer 2s out there. 🔗 onlinelibrary.wiley.com/doi/10.1111/...

❓ How do you know if a gene is expressed or not in a certain tissue/organ? 👉 If you are interested in animals, #Bgee database is the first place to go. 52 species, several tissues/organs... www.bgee.org

Before running your statistical test, double-check that its assumptions hold. Violations can lead to misleading results. Here's a handy tool to help: 🔗 ahmed-bargheet.shinyapps.io/AssumpSure ℹ️ github.com/Ahmedbarghee... #rstats #shiny #r

"A drunk man will find his way home, but a drunk bird may get lost forever." -Shizuo Kakutani

🚨Our latest: HIF1α mediates circadian regulation of skeletal muscle metabolism and substrate preference in response to time-of-day exercise ⏰💪 📄 www.pnas.org/doi/10.1073/...

A nice #R package to visualize #bullseye plots: 🔗 cran.r-project.org/web/packages... ❓ Did you notice the Simpson's paradox?

Are you developing an R package? Great tips ahead ⬇️ journals.plos.org/ploscompbiol...

📢 RNA-seq users! RPKM/TPM are NOT always comparable across samples/projects. They're relative within a sample. rnajournal.cshlp.org/content/26/8...