ArticleLife science alliance2022
Resolution of the curse of dimensionality in single-cell RNA sequencing data analysis.
Article in Life science alliance, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed, 30 citations in OpenAlex.
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- Identity crisis: exploring the boundaries of cell type identification in the age of single-cell transcriptomics.Frontiers in cellular neuroscience · 2026Article
- Graph Topology Reframes the Coherence of Cell-State Manifold Inference under Heterogeneous Single-Cell Observations.Computational and structural biotechnology journal · 2026Article
- Early determination of the dorsal-ventral axis in endochondral ossification in mice.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2025Article
- The mitotic STAG3-cohesin complex shapes male germline nucleome.Nature structural & molecular biology · 2025Article
- Comprehensive noise reduction in single-cell data with the RECODE platform.Cell reports methods · 2025Article
- T cell receptor associated transmembrane adaptor 1 (TRAT1) modulates human Th17 and Treg responses via PI3-kinase and STAT dependent mechanisms.Cell communication and signaling : CCS · 2025Article
- Artificial Intelligence and Neuroscience: Transformative Synergies in Brain Research and Clinical Applications.Journal of clinical medicine · 2025Review
- Biomarker research for Henoch-Schönlein purpura nephritis based on "omics" techniques.Frontiers in medicine · 2025Review
- scEGOT: single-cell trajectory inference framework based on entropic Gaussian mixture optimal transport.BMC bioinformatics · 2024Article
- Fine construction of gene coexpression network analysis using GTOM and RECODE detected a critical module of neuroblastoma stages 4 and 4S.Hereditas · 2024Article
- Single-cell RNA sequencing technology in human spermatogenesis: Progresses and perspectives.Molecular and cellular biochemistry · 2024Review
- Integrated multi-omics with machine learning to uncover the intricacies of kidney disease.Briefings in bioinformatics · 2024Review
- Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-cell RNA sequencing (scRNA-seq) can determine gene expression in numerous individual cells simultaneously, promoting progress in the biomedical sciences. However, scRNA-seq data are high-dimensional with substantial technical noise, including dropouts. During analysis of scRNA-seq data, such noise engenders a statistical problem known as the curse of dimensionality (COD). Based on high-dimensional statistics, we herein formulate a noise reduction method, RECODE (resolution of the curse of dimensionality), for high-dimensional data with random sampling noise. We show that RECODE consistently resolves COD in relevant scRNA-seq data with unique molecular identifiers. RECODE does not involve dimension reduction and recovers expression values for all genes, including lowly expressed genes, realizing precise delineation of cell fate transitions and identification of rare cells with all gene information. Compared with representative imputation methods, RECODE employs different principles and exhibits superior overall performance in cell-clustering, expression value recovery, and single-cell-level analysis. The RECODE algorithm is parameter-free, data-driven, deterministic, and high-speed, and its applicability can be predicted based on the variance normalization performance. We propose RECODE as a powerful strategy for preprocessing noisy high-dimensional data.
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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.