PyInfinityFlow: optimized imputation and analysis of high-dimensional flow cytometry data for millions of cells.

ABSTRACT:

Motivation

While conventional flow cytometry is limited to dozens of markers, new experimental and computational strategies, such as Infinity Flow, allow for the generation and imputation of hundreds of cell surface protein markers in millions of cells. Here, we describe an end-to-end analysis workflow for Infinity Flow data in Python.

Results

pyInfinityFlow enables the efficient analysis of millions of cells, without down-sampling, through direct integration with well-established Python packages for single-cell genomics analysis. pyInfinityFlow accurately identifies both common and extremely rare cell populations which are challenging to define from single-cell genomics studies alone. We demonstrate that this workflow can nominate novel markers to design new flow cytometry

SUBMITTER: Ferchen K 

PROVIDER: S-EPMC10166583 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature