Speaker
Description
Flow cytometry is a technique used to analyze individual cells or particles contained in a biological sample. The sample passes through a cytometer, where the cells are irradiated by a laser, causing them to scatter and emit fluorescent light. A number of detectors then collect and analyze the scattered and emitted light, producing a wealth of quantitative information about each cell (cell size, granularity, expression of particular proteins or other markers…). This technique produces high dimensional multiparametric observations.
We considered here flow cytometry data, obtained from blood samples, in the context of a specific severe disorder. For each of the n patients, p variables were measured on around 10 000 cells. The information for each patient can be considered like a p-dimensional distribution. Usually, with such data, dimension reduction is based on the distance matrix between these distributions. We propose in this work to reduce the size of the data by calculating deciles and correlation between variables. These method allows to keep more variables (around several hundred) to use classification methods.
| Type of presentation | Talk |
|---|---|
| Classification | Both methodology and application |
| Keywords | Cytometry, Classification |