We’re hiring a Postdoctoral Research Fellow! Join a dynamic and collaborative team working on impactful research at the intersection of biostatistics and genomics. If you’re passionate about discovery, innovation, and translating ideas into real-world impact, I’d love to connect.
Excited to share that I've joined @UTHealthHouston as an associate professor in the Department of Biostatistics & Data Science! Grateful for the warm welcome and looking forward to new collaborations, ideas, and adventures ahead. #Biostatistics#NewBeginnings
A recent estimate by a team of Stanford economists attributes almost a quarter of all US innovation since 1976 to high-skilled, foreign-born individuals. This is despite a difficult immigration system.
Let's accelerate innovation!
Check out our new tool 'cypress', the first R/Bioconductor package for the power assessment and experimental design for cell-type-specific differential expression (csDE) analysis. https://t.co/AWLSfOueFv
SSGG hosted its second annual social event at #JSM! Participants enjoyed a 1.5-mile walk, jog, or run along the Williamnette River, finishing at Audrey McCall Beach. Great to see everyone!
Excited to share our recent publication on @GenomeMedicine demonstrating the merits of personalized reference panels in signal deconvolution. Our software ISLET is on @Bioconductor. Big congrats to my PhD student Leslie Meng who led the project.
Meng and colleagues present a novel algorithm to deconvolute cell composition of bulk RNA data using personalised reference panels @HHarryFeng:
Find the paper at Genome Medicine:
https://t.co/DDN9ttW8eH
We are excited to share our most recent work on making cell type composition deconvolution more accurate by using personalized reference panels. Guanqun (Leslie) Meng, a PhD student in my lab, took a lead in this project.
Excited to share our new @GenomeBiology
paper on personalized gene expression reference in deconvolution. Our method ISLET will help retrieve individual-specific reference panel, and conduct accurate differential expression analysis, at cell type level: https://t.co/smfu2dJUrV