Author: sisi

Check out the new paper here! https://www.nature.com/articles/s43588-022-00263-8

Xiaoqiao’s method assembles minimal lists of highly informative genes using an iterative SVM approach. Each iteration uses only a small numbers of cells and genes for computation. She uses a clever ‘active’ strategy to prioritize cells and genes that are most commonly misclassified, thus ensuring that selected genes improve classification on outliers. Because only a small number of cells and genes are used at each step, the process is very memory efficient, and allows her to compute over huge datasets (>1M cells) in a little over an hour (compared to days for other algorithms).

Paper can be found at: https://www.frontiersin.org/articles/10.3389/fimmu.2021.730825/full

What’s cool about this paper: They developed a single-cell RNA sequencing (scRNA-seq) pipeline for in vivo characterization of barcoded rAAV pools at high resolution. They were able to faithfully identify cell-type specific tropisms in a pool of up to 7 variants simultaneously, paving the way for future highly multiplexed screens.

Fresh off the press at Scientific Reports!  https://www.nature.com/articles/s41598-020-77073-3

What’s cool about this paper: capillary blood sampling devices (TAP devices) allowed the team to collect blood at high temporal frequencies (morning and nigh). They used this system to study diurnal variability in a cell type-specific and patient-specific manner.