https://www.science.org/doi/10.1126/science.abj6987
Congratulations. Looking forward to mapping trillions of reads against CHM13!
https://www.science.org/doi/10.1126/science.abj6987
Congratulations. Looking forward to mapping trillions of reads against CHM13!
Neural Distance Embeddings for Biological Sequences
Gabriele Corso, Rex Ying, Michal Pándy, Petar Veličković, Jure Leskovec, Pietro Liò
abs: https://arxiv.org/abs/2109.09740
github: https://github.com/gcorso/NeuroSE
https://arxiv.org/pdf/2109.09740.pdf
https://proceedings.neurips.cc/paper/2021/file/9a1de01f893e0d2551ecbb7ce4dc963e-Paper.pdf
Liked the extensive scATAC-seq analysis. We discussed this in a journal club.
https://www.nature.com/articles/s41586-021-03209-8
Single-cell epigenomics reveals mechanisms of human cortical development
Ryan S. Ziffra, Chang N. Kim, Jayden M. Ross, Amy Wilfert, Tychele N. Turner, Maximilian Haeussler, Alex M. Casella, Pawel F. Przytycki, Kathleen C. Keough, David Shin, Derek Bogdanoff, Anat Kreimer, Katherine S. Pollard, Seth A. Ament, Evan E. Eichler, Nadav Ahituv & Tomasz J. Nowakowski
Nature volume 598, pages 205–213 (2021)
eQTLs paper is out in Nature Genetics:
Zeng, B., Bendl, J., Kosoy, R. et al. [Panos R] Multi-ancestry eQTL meta-analysis of human brain identifies candidate causal variants for brain-related traits. Nat Genet (2022).
https://doi.org/10.1038/s41588-021-00987-9
https://www.nature.com/articles/s41586-021-04064-3
some focus on its main method
MR-MEGA
https://academic.oup.com/hmg/article/26/18/3639/3976569