The advent of DNA-microarrays spurred a vigorous effort to reverse engineer biological networks. Recently, these efforts have been reinvigorated by the availability of RNA-seq data from perturbed and unperturbed single cells. In the talk below, I discuss the opportunities and limitations of using such data for inferring networks of direct causal interactions, with emphasis...
slavovLabProteomics news examined our SCoPE2 data (available here: t.co/g2oQgxdkwI) and made many perceptive points: t.co/0V4A3KBVLU
Yes, we used QE Orbitrap, and one definitely does not need the latest instrument for SCoPE2. Our preptint describes more important factors.
slavovLab@KharchenkoLab Yes, these data do not allow to distinguish clearly between technical and biological variability. The total variability between the cells is better reflected in the distributions of pairwise correlations between the cells than in the embeddings. t.co/bEQHXBdjuA