Separating the signal from the noise in scRNA-Seq data (new paper!)
We’ve developed a smoothing algorithm that makes the analysis of high-throughput single-cell RNA-Seq a lot easier. The algorithm effectively removes technical noise while largely preserving biological heterogeneity. You can read the paper on bioRxiv and find reference implementations in Python/R/Matlab on github. In the YanaiLab, we love single-cell RNA-Seq data, and we’re proud of our…
Read more Separating the signal from the noise in scRNA-Seq data (new paper!)
Computational biologists: moving to the driver’s seat
Computational biologists: moving to the driver’s seat Itai Yanai and Eva Chmielnicki Genome Biology201718:223 https://doi.org/10.1186/s13059-017-1357-1 Published: 23 November 2017 Abstract The recent shift of computational biologists from bioinformatics service providers to leaders of cutting-edge programs highlights the accompanying cultural and conceptual changes that should be implemented by funding bodies and academic institutions.
Read more Computational biologists: moving to the driver’s seat
scDual-Seq
scDual-Seq: mapping the gene regulatory program of Salmonella infection by host and pathogen single-cell RNA-sequencing. Genome Biol. 2017 Oct 27;18(1):200. doi: 10.1186/s13059-017-1340-x Avital G1,2, Avraham R3,4, Fan A3, Hashimshony T2, Hung DT3,5,6, Yanai I7. The interaction between a pathogen and a host is a highly dynamic process in which both agents activate complex programs. Here, we introduce a single-cell RNA-sequencing method,…
Development and evolution through the lens of global gene regulation
Trends in Genetics has published this review on the Yanai lab’s contributions to evo-devo. Evolution and development are two inherently intertwined processes. As the embryo develops it does so in ways that both reflect past constraints and bias the future evolution of the species. While research exploiting this insight typically studies individual genes, transcriptomic analyses have sparked…
Read more Development and evolution through the lens of global gene regulation
BLIND
Several years ago, we presented the BLIND method which is able to determine the temporal order of transcriptomes in large datasets, thus allowing for the massive collection of samples, to be ordered at the analysis stage: Anavy L, Levin M, Khair S, Nakanishi N, Valverde SF, Degnan BM, and Yanai I. BLIND ordering of large-scale…
