Single-cell transcriptomics reveals gene expression heterogeneity but suffers from stochastic dropout and characteristic bimodal expression distributions in which expression is either strongly non-zero or non-detectable. We propose a two-part, generalized linear model for such bimodal data that parameterizes both of these features. We argue that the cellular detection rate, the fraction of genes expressed in a cell, should be adjusted for as a source of nuisance variation. Our model provides gene set enrichment analysis tailored to single-cell data. It provides insights into how networks of co-expressed genes evolve across an experimental treatment. MAST is available at https://github.com/RGLab/MAST.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-015-0844-5) contains supplementary material, which is available to authorized users.

Plasma levels of high density lipoprotein cholesterol (HDL-C) are inversely proportional to the incidence of cardiovascular disease. Recent applications of modern proteomic technologies have identified upward of 50 distinct proteins associated with HDL particles with many of these newly discovered proteins implicating HDL in nonlipid transport processes including complement activation, acute phase response and innate immunity. However, almost all MS-based proteomic studies on HDL to date have utilized density gradient ultracentrifugation techniques for HDL isolation prior to analysis. These involve high shear forces and salt concentrations that can disrupt HDL protein interactions and alter particle function. Here, we used high-resolution size exclusion chromatography to fractionate normal human plasma to 17 phospholipid-containing subfractions. Then, using a phospholipid binding resin, we identified proteins that associate with lipoproteins of various sizes by electrospray ionization mass spectrometry. We identified 14 new phospholipid-associated proteins that migrate with traditionally defined HDL, several of which further support roles for HDL in complement regulation and protease inhibition. The increased fractionation inherent to this method allowed us to visualize HDL protein distribution across particle size with unprecedented resolution. The observed heterogeneity across subfractions suggests the presence of HDL particle subpopulations each with distinct protein components that may prove to impart distinct physiological functions.

A remarkable feature of development is its reproducibility, the ability to correct embryo-to-embryo variations and instruct precise patterning. In Drosophila, embryonic patterning along the anterior-posterior axis is controlled by the morphogen gradient Bicoid (Bcd). In this report, we describe quantitative studies of the native Bcd gradient and its target Hunchback (Hb). We show that the native Bcd gradient is highly reproducible and is itself scaled with embryo length. While a precise Bcd gradient is necessary for precise Hb expression, it still has positional errors greater than Hb expression. We describe analyses further probing mechanisms for Bcd gradient scaling and correction of its residual positional errors. Our results suggest a simple model of a robust Bcd gradient sufficient to achieve scaled and precise activation of its targets. The robustness of this gradient is conferred by its intrinsic properties of "self-correcting" the inevitable input variations to achieve a precise and reproducible output.