Peer review process
Not revised: This Reviewed Preprint includes the authors’ original preprint (without revision), an eLife assessment, and public reviews.
Read more about eLife’s peer review process.Editors
- Reviewing EditorSeunghee HongYonsei University, Seoul, Republic of Korea
- Senior EditorSatyajit RathIndian Institute of Science Education and Research (IISER), Pune, India
Reviewer #1 (Public Review):
Summary:
This manuscript presented a useful toolkit designed for CyTOF data analysis, which integrates 5 key steps as an analytical framework. A semi-supervised clustering tool was developed, and its performance was tested in multiple independent datasets. The tool was compared to human experts as well as supervised and unsupervised methods.
Strengths:
The study employed multiple independent datasets to test the pipeline. A new semi-supervised clustering method was developed.
Weaknesses:
The examination of the whole pipeline is incomplete. Lack of descriptions or justifications for some analyses.
Reviewer #2 (Public Review):
Summary:
The authors have developed marker selection and k-means (k=2) based binary clustering algorithm for the first-level supervised clustering of the CyTOF dataset. They built a seamless pipeline that offers the multiple functionalities required for CyTOF data analysis.
Strengths:
The strength of the study is the potential use of the pipeline for the CyTOF community as a wrapper for multiple functions required for the analysis. The concept of the first line of binary clustering with known markers can be practically powerful.
Weaknesses:
The weakness of the study is that there's little conceptual novelty in the algorithms suggested from the study and the benchmarking is done in limited conditions.
Reviewer #3 (Public Review):
Summary:
ImmCellTyper is a new toolkit for Cytometry by time-of-flight data analysis. It includes BinaryClust, a semi-supervised clustering tool (which takes into account prior biological knowledge), designed for automated classification and annotation of specific cell types and subpopulations. ImmCellTyper also integrates a variety of tools to perform data quality analysis, batch effect correction, dimension reduction, unsupervised clustering, and differential analysis.
Strengths:
The proposed algorithm takes into account the prior knowledge.
The results on different benchmarks indicate competitive or better performance (in terms of accuracy and speed) depending on the method.
Weaknesses:
The proposed algorithm considers only CyTOF markers with binary distribution.