Automated subset identification and characterization pipeline for multidimensional flow and mass cytometry data clustering and visualization.

When examining datasets of any dimensionality, researchers frequently aim to identify individual subsets (clusters) of objects within the dataset. The ubiquity of multidimensional data has motivated the replacement of user-guided clustering with fully automated clustering. The fully automated methods are designed to make clustering more accurate, standardized and faster.

QFMatch: multidimensional flow and mass cytometry samples alignment.

Part of the flow/mass cytometry data analysis process is aligning (matching) cell subsets between relevant samples. Current methods address this cluster-matching problem in ways that are either computationally expensive, affected by the curse of dimensionality, or fail when population patterns significantly vary between samples. Here, we introduce a quadratic form (QF)-based cluster matching algorithm (QFMatch) that is computationally efficient and accommodates cases where population locations differ significantly (or even disappear or appear) from sample to sample.

A Quantitative Method for Comparing the Brightness of Antibody-dye Reagents and Estimating Antibodies Bound per Cell.

We present a quantitative method for comparing the brightness of antibody-dye reagents and estimating antibodies bound per cell. The method is based on complementary binding of test and fill reagents to antibody capture microspheres. Several aliquots of antibody capture beads are stained with varying amounts of the test conjugate.

Earth Mover's Distance (EMD): A True Metric for Comparing Biomarker Expression Levels in Cell Populations.

Changes in the frequencies of cell subsets that (co)express characteristic biomarkers, or levels of the biomarkers on the subsets, are widely used as indices of drug response, disease prognosis, stem cell reconstitution, etc. However, although the currently available computational "gating" tools accurately reveal subset frequencies and marker expression levels, they fail to enable statistically reliable judgements as to whether these frequencies and expression levels differ significantly between/among subject groups. Here we introduce flow cytometry data analysis pipeline which includes the Earth Mover's Distance (EMD) metric as solution to this problem.

Cocrystalline Copolyimides of Poly(ethylene 2,6-naphthalate).

Copolycondensation of ,'-bis(2-hydroxyethyl)-biphenyl-3,4,3',4'-tetracarboxylic diimide (5-25 mol %) with bis(2-hydroxyethyl)-2,6-naphthalate affords a series of cocrystalline, poly(ethylene 2,6-naphthalate) (PEN)-based poly(ester imide)s. The glass transition temperature rises with the level of comonomer, from 118 °C for PEN itself to 148 °C for the 25% diimide copolymer. X-ray powder and fiber diffraction studies show that, when 5 mol % or more of diimide is present, the α-PEN crystal structure is replaced by a new crystalline phase arising from isomorphic substitution of biphenyldiimide for PEN residues in the polymer crystal lattice.

AutoGate: automating analysis of flow cytometry data.

Nowadays, one can hardly imagine biology and medicine without flow cytometry to measure CD4 T cell counts in HIV, follow bone marrow transplant patients, characterize leukemias, etc. Similarly, without flow cytometry, there would be a bleak future for stem cell deployment, HIV drug development and full characterization of the cells and cell interactions in the immune system. But while flow instruments have improved markedly, the development of automated tools for processing and analyzing flow data has lagged sorely behind.

Automatic clustering of flow cytometry data with density-based merging.

The ability of flow cytometry to allow fast single cell interrogation of a large number of cells has made this technology ubiquitous and indispensable in the clinical and laboratory setting. A current limit to the potential of this technology is the lack of automated tools for analyzing the resulting data. We describe methodology and software to automatically identify cell populations in flow cytometry data.

Knowledge acquisition and visualization for biomedical research.

The TreeTableWidget is a user interface component that allows instances in a knowledge-base to be sorted on the value of one or more of its attributes. Any combination of attributes can be sorted simultaneously by assigning a precedence to each sort. This results in a hierarchy of attributes such that instances can be grouped and visualized according to shared attribute values in a tree view.