MACA: Marker-based automatic cell-type annotation for single cell expression data

bioRxiv (Cold Spring Harbor Laboratory)

Abstract

Abstract Summary Accurately identifying cell-types is a critical step in single-cell sequencing analyses. Here, we present marker-based automatic cell-type annotation (MACA), a new tool for annotating single-cell transcriptomics datasets. We developed MACA by testing 4 cell-type scoring methods with 2 public cell-marker databases as reference in 6 single-cell studies. MACA compares favorably to 4 existing marker-based cell-type annotation methods in terms of accuracy and speed. We show that MACA can annotate a large single-nuclei RNA-seq study in minutes on human hearts with ~290k cells. MACA scales easily to large datasets and can broadly help experts to annotate cell types in single-cell transcriptomics datasets, and we envision MACA provides a new opportunity for integration and standardization of cell-type annotation across multiple datasets. Availability and implementation MACA is written in python and released under GNU General Public License v3.0. The source code is available at https://github.com/ImXman/MACA . Contact Yang Xu ( yxu71@vols.utk.edu ), Sikander Hayat ( hayat221@gmail.com )

Authors 4

1. Yang Xu

   Oak Ridge National Laboratory · University of Tennessee at Knoxville

   Affiliation as printed

   Bayer-Broad Joint Precision Cardiology Lab, Cambridge, MA, USA

   UT-ORNL Graduate School of Genome Science and Technology, The University of Tennessee, Knoxville, TN, USA

2. Simon J. Baumgart

   Novo Nordisk (Denmark)

   Affiliation as printed

   Bayer-Broad Joint Precision Cardiology Lab, Cambridge, MA, USA

   Novo Nordisk, Data Mining and Bioinformatics, Copenhagen, Denmark

3. Christian M. Stegmann
   Affiliation as printed

   Bayer-Broad Joint Precision Cardiology Lab, Cambridge, MA, USA

4. Sikander Hayat corresponding Aachen Institute of Experimental Medicine and Systems Biology

   RWTH Aachen University

   Affiliation as printed

   Bayer-Broad Joint Precision Cardiology Lab, Cambridge, MA, USA

   Institute of Experimental Medicine and Systems Biology, RWTH Aachen University, Aachen, Germany