Knijnenburg TA, et al. (2011) A regression model approach to enable cell morphology correction in high-throughput flow cytometry. Mol Syst Biol 7():531
Abstract: Cells exposed to stimuli exhibit a wide range of responses ensuring phenotypic variability across the population. Such single cell behavior is often examined by flow cytometry; however, gating procedures typically employed to select a small subpopulation of cells with similar morphological characteristics make it difficult, even impossible, to quantitatively compare cells across a large variety of experimental conditions because these conditions can lead to profound morphological variations. To overcome these limitations, we developed a regression approach to correct for variability in fluorescence intensity due to differences in cell size and granularity without discarding any of the cells, which gating ipso facto does. This approach enables quantitative studies of cellular heterogeneity and transcriptional noise in high-throughput experiments involving thousands of samples. We used this approach to analyze a library of yeast knockout strains and reveal genes required for the population to establish a bimodal response to oleic acid induction. We identify a group of epigenetic regulators and nucleoporins that, by maintaining an 'unresponsive population,' may provide the population with the advantage of diversified bet hedging.FAU - Knijnenburg, Theo.
| Status: Published | Type: Journal Article | PubMed ID: 21952134 |
Topics addressed in this paper
Number of different genes curated to this paper: 21
- To find other papers on a gene and topic, click on the colored ball in the appropriate box.
- displays other papers with information about that topic for that gene.
- displays other papers in SGD that are associated with that topic.
The topic is addressed in these papers but does not describe a specific gene or chromosomal feature.
- To go to the Locus page for a gene, click on the gene name.
| Topics | Topics not linked to Genes | Genes linked to topics (#1 - 10 ) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| ADR1 | ARP6 | CHZ1 | HTL1 | HTZ1 | KAP114 | NUP120 | NUP133 | NUP84 | OAF1 | ||
| Additional Literature | | | | | | | | | | | |
| Computational analysis |
| ||||||||||
| Large-scale phenotype analysis |
| ||||||||||
| Mutants/Phenotypes | | | | | | | | | | | |
| Omics |
| ||||||||||
| Regulatory Role | | | | | | | | | | | |
| Techniques and Reagents |
| ||||||||||
| Topics | Genes linked to topics (#11 - 20 ) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| PIP2 | POT1 | SNF12 | SNF5 | SNF6 | SWC3 | SWC5 | SWI3 | SWR1 | TAF14 | |
| Additional Literature | | | | | | | | | | |
| Mutants/Phenotypes | | | | | | | | | | |
| Protein Processing/Modification/Regulation | | |||||||||
| Regulation of | | |||||||||
| Regulatory Role | | | | | | | | | | |
| Topics | Genes linked to topics (#21 ) |
|---|---|
| VPS75 | |
| Additional Literature | |
| Mutants/Phenotypes | |
| Regulatory Role | |





