ArticleNature communications2023
Comparative analysis of dimension reduction methods for cytometry by time-of-flight data.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 25 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
25 citing papers in PubMed.
- Weighted sliced inverse regression for scalable supervised dimensionality reduction of spatial transcriptomics data.Nature communications · 2026Article
- Bonsai reconstructs tree representations for distortion-free visualization and exploration of high-dimensional data.Nature biotechnology · 2026Article
- Progress and new challenges in image-based profiling.Molecular systems biology · 2026Review
- Automatic computational classification of bone marrow cells for B cell pediatric leukemia using UMAP.BioData mining · 2025Article
- Unifying equivalences across unsupervised learning, network science, and imaging/network neuroscience.ArXiv · 2025Article
- scRL: Utilizing Reinforcement Learning to Evaluate Fate Decisions in Single-Cell Data.Biology · 2025Article
- Isobaric Labeling Update in MaxQuant.Journal of proteome research · 2025Article
- From High Dimensions to Human Insight: Exploring Dimensionality Reduction for Chemical Space Visualization.Molecular informatics · 2025Article
- Structure preserving t-SNE of matrix framed data.Computational and structural biotechnology journal · 2025Article
- Predicting Stroke Risk Using Machine Learning: A Data-Driven Approach to Early Detection and Prevention.Stroke research and treatment · 2025Article
- Clinical and mechanistic relevance of high-dimensionality analysis of the paediatric sepsis immunome.Frontiers in immunology · 2025Article
- Unlocking the Heterogeneity in Acute Leukaemia: Dissection of Clonal Architecture and Metabolic Properties for Clinical Interventions.International journal of molecular sciences · 2024Review
- Mapping cellular interactions from spatially resolved transcriptomics data.Nature methods · 2024Article
- The art of seeing the elephant in the room: 2D embeddings of single-cell data do make sense.PLoS computational biology · 2024Article
- Metal-detection based techniques and their applications in metallobiology.Chemical science · 2024Review
- AI-Enhanced evaluation of YouTube content on post-surgical incontinence following pelvic cancer treatment.SSM - population health · 2024Article
- Ly6CCells · 2024Article
- Automated Cytometric Gating with Human-Level Performance Using Bivariate Segmentation.bioRxiv : the preprint server for biology · 2024Article
- Approaching Mass Cytometry Translational Studies by Experimental and Data Curation Settings.Methods in molecular biology (Clifton, N.J.) · 2024Review
- Seeing or believing in hyperplexed spatial proteomics via antibodies: New and old biases for an image-based technology.Biological imaging · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
Abstract
While experimental and informatic techniques around single cell sequencing (scRNA-seq) are advanced, research around mass cytometry (CyTOF) data analysis has severely lagged behind. CyTOF data are notably different from scRNA-seq data in many aspects. This calls for the evaluation and development of computational methods specific for CyTOF data. Dimension reduction (DR) is one of the critical steps of single cell data analysis. Here, we benchmark the performances of 21 DR methods on 110 real and 425 synthetic CyTOF samples. We find that less well-known methods like SAUCIE, SQuaD-MDS, and scvis are the overall best performers. In particular, SAUCIE and scvis are well balanced, SQuaD-MDS excels at structure preservation, whereas UMAP has great downstream analysis performance. We also find that t-SNE (along with SQuad-MDS/t-SNE Hybrid) possesses the best local structure preservation. Nevertheless, there is a high level of complementarity between these tools, so the choice of method should depend on the underlying data structure and the analytical needs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.