Please RT Just two more days to apply for permanent bioinformatics position - use code to save lives in beautiful Copenhagen! Great collaborative team, diverse tasks, and meaningful outcomes
https://t.co/DNsraYZm3H
We are increasing our bioinformatics team with two permanent positions!
Come and work in an incredible team of developers and bioinformaticians at Genomic Medicine in charming Copenhagen.
Coding saves lives in personalised medicine!
https://t.co/g2s35p1FJF
pls. RT
We are increasing our bioinformatics team with two permanent positions!
Come and work in an incredible team of developers and bioinformaticians at Genomic Medicine in charming Copenhagen.
Coding saves lives in personalised medicine!
https://t.co/g2s35p1FJF
pls. RT
Top performance by Genomic Medicine dep @Rigshospitalet in @precisionfda challenge: https://t.co/bF6yh5lL6G
🥇in Somatic Variant Calling
🥈 in TMB Estimation
Bioinformatic pipeline based on @gatk_dev
We have two open permanent positions in my clinical team for bioinformaticians either with or without clinical experience. Great people, meaningful work and exciting challenges! Copenhagen is lovely. Deadline Tuesday https://t.co/FgKAGE320s
https://t.co/pPcnjbOixG
@kjhealy it’s a super beautiful data viz book! I suggest to add notes on Sina plot found in ggforce (which is also what you have on the cover, if I’m not mistaken?)
@alextuowang @jwbelmon It’s beautiful and well explained! I vote for also including the Sina Plot (ggforce), which would complement very well what you present.
@ngehlenborg@anshulkundaje@keller__mark Looks super nice! adding geom_sina() as an alternative to the violins, will provide an immediate feeling of the number of cells in each class. This can be very important information, and added with no extra inc
@larsjuhljensen @wolfgangkhuber I made the Sina plot exactly to avoid this binning - I think the bins suggests some artificial structure in the plot, which may not be in the data. Show us the data!
Hey single-cell folks. We are excited to share our work "TENET, single-cell gene regulatory reconstruction framework for single-cell transcriptomics" with @kjwonl lab, now out in @NAR_Open
https://t.co/TY19eQQaIX
We hope its useful to the community! 1/5
Brief summary below
Are you looking to start a #singlecell experiment?
Have a read:
#Benchmarking full-length transcript single cell mRNA sequencing protocols https://t.co/NcwtGJEILl