Leverage Machine Learning for High Content Analysis
Traditional High Content Analysis relies heavily on the user to devise an analysis strategy for identifying phenotypic subpopulations. Manually choosing measurements and setting thresholds that are phenotypically selective is tedious, sensitive to user bias, and is often poor at differentiating subtle phenotypic differences. The Phenoglyphs module for IN Carta automates and simplifies this complex process with the use of machine learning.
Phenoglyphs machine learning classification module analyzes multiple measures at once to uncover phenotypic differences in your cell population. This can lead to identification of unexpected subpopulations that never would have been detected by manual object classification methods.
Manual classifiers can be time-consuming and prone to significant bias. With Phenoglyphs, you can perform more complex object classification, faster, and without human bias.
Easy to Use. Expert Results.
Automatic when you want it to be, manual when you need it to be—Phenoglyphs uses a unique combination of supervised and unsupervised algorithms to put the power of machine learning at your fingertips without surrendering control.