ArticleNature communications2023
Accurate integration of single-cell DNA and RNA for analyzing intratumor heterogeneity using MaCroDNA.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Cancer Heterogeneity and Cancer Cell Plasticity: Molecular Mechanisms and Precision Therapy.MedComm · 2026Review
- Single-cell aneuploidy and chromosomal arm imbalances define subclones with divergent transcriptomic phenotypes.NAR genomics and bioinformatics · 2025Article
- Dissecting microbial communities with single-cell transcriptome analysis.Science (New York, N.Y.) · 2025Review
- Deconvolution and Phylogeny Inference of Diverse Variant Types Integrating Bulk DNA-seq with Single-cell RNA-seq.bioRxiv : the preprint server for biology · 2025Article
- Deconvolution and phylogeny inference of diverse variant types integrating bulk DNA-seq with single-cell RNA-seq.Bioinformatics advances · 2025Article
- Review
- Joint inference of clonal structure using single-cell genome and transcriptome sequencing data.NAR genomics and bioinformatics · 2024Article
- Unraveling the pathogenesis of Barrett's esophagus and esophageal adenocarcinoma: the "omics" era.Frontiers in oncology · 2024Review
- Accurate integration of single-cell DNA and RNA for analyzing intratumor heterogeneity using MaCroDNA.Nature communications · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Cancers develop and progress as mutations accumulate, and with the advent of single-cell DNA and RNA sequencing, researchers can observe these mutations and their transcriptomic effects and predict proteomic changes with remarkable temporal and spatial precision. However, to connect genomic mutations with their transcriptomic and proteomic consequences, cells with either only DNA data or only RNA data must be mapped to a common domain. For this purpose, we present MaCroDNA, a method that uses maximum weighted bipartite matching of per-gene read counts from single-cell DNA and RNA-seq data. Using ground truth information from colorectal cancer data, we demonstrate the advantage of MaCroDNA over existing methods in accuracy and speed. Exemplifying the utility of single-cell data integration in cancer research, we suggest, based on results derived using MaCroDNA, that genomic mutations of large effect size increasingly contribute to differential expression between cells as Barrett's esophagus progresses to esophageal cancer, reaffirming the findings of the previous studies.
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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.