FlowLearn: fast and precise identification and quality checking of cell populations in flow cytometry.

ABSTRACT:

Motivation

Identification of cell populations in flow cytometry is a critical part of the analysis and lays the groundwork for many applications and research discovery. The current paradigm of manual analysis is time consuming and subjective. A common goal of users is to replace manual analysis with automated methods that replicate their results. Supervised tools provide the best performance in such a use case, however they require fine parameterization to obtain the best results. Hence, there is a strong need for methods that are fast to setup, accurate and interpretable.

Results

flowLearn is a semi-supervised approach for the quality-checked identification of cell populations. Using a very small number of manually gated samples, through density alignments it is able to pre

SUBMITTER: Lux M 

PROVIDER: S-EPMC6022609 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature