vampireanalysis 3.2.19

Vampire Image Analysis Package

Vampire Analysis

Abstract

Cell morphology encodes essential information on many underlying biological processes, and is commonly employed by clinicians and researchers in the study, diagnosis, prognosis, and treatment of human diseases. Quantification of cell morphology has seen tremendous advances in recent years. However, effectively defining morphological shapes and evaluating the extent of morphological heterogeneity within a cell population remains a challenge. Here we present a protocol and software for the analysis of cell morphology data using the VAMPIRE algorithm. This algorithm enables cell profiling through the classification of cells based on equidistant points along cell and nuclear contours. Examining the distributions of cell morphologies across automatically identified classes, termed shape modes, provide an effective visualization scheme that relate cell shapes with cellular subtypes that are defined by endogenous and exogenous cellular conditions. In addition, these shape mode distributions offer a direct and quantitative way to measure the extent of morphological heterogeneity of cells. This protocol is highly automated and fast, taking less than 10 min to analyze 10,000 cells.

Kyu Sang Han Jude Phillip Pei-Hsun Wu Denis Wirtz