https://www.sciencedirect.com/science/article/abs/pii/S0262407921005704
Found the cartoon description of the immune system quite illuminating. Always wondered how neutrophils fit in!
https://www.sciencedirect.com/science/article/abs/pii/S0262407921005704
Found the cartoon description of the immune system quite illuminating. Always wondered how neutrophils fit in!
A gene sequence-to-expression machine learning model achieves improved accuracy by incorporating information about potential long-range interactions.
Yang Young Lu and William Staford Noble
Liked this @KharchenkoLab review – in particular, the descriptions of the various low-dimensional approximations & the simple motivation for these using PCA. Also, found the step-by-step workflow in the text & figures helpful.
Note also the reference to expression entropy for determining the direction in trajectories.
Review Article
Published: 21 June 2021
The triumphs and limitations of computational methods for scRNA-seq
Peter V. Kharchenko
Nature Methods volume 18, pages723–732 (2021)
Article
Published: 18 October 2021
Exome sequencing and analysis of 454,787 UK Biobank participants
Joshua D. Backman, Alexander H. Li, Anthony Marcketta, Dylan Sun, Joelle Mbatchou, Michael D. Kessler, Christian Benner, Daren Liu, Adam E. Locke, Suganthi Balasubramanian, Ashish Yadav, Nilanjana Banerjee, Christopher Gillies, Amy Damask, Simon Liu, Xiaodong Bai, Alicia Hawes, Evan Maxwell, Lauren Gurski, Kyoko Watanabe, Jack A. Kosmicki, Veera Rajagopal, Jason Mighty, Regeneron Genetics Center, DiscovEHR, Marcus Jones, Lyndon Mitnaul, Eli Stahl, Giovanni Coppola, Eric Jorgenson, Lukas Habegger, William J. Salerno, Alan R. Shuldiner, Luca A. Lotta, John D. Overton, Michael N. Cantor, Jeffrey G. Reid, George Yancopoulos, Hyun M. Kang, Jonathan Marchini, Aris Baras, Gonçalo R. Abecasis & Manuel A. Ferreira -Show fewer authors
Nature (2021)
https://www.nature.com/articles/s41586-021-04103-z
seems to be an incredible data set – 450K exomes!