CONICS integrates scRNA-seq with DNA sequencing to map gene expression to tumor sub-clones
Open accessAbstract
Motivation: Single-cell RNA-sequencing (scRNA-seq) has enabled studies of tissue composition at unprecedented resolution. However, the application of scRNA-seq to clinical cancer samples has been limited, partly due to a lack of scRNA-seq algorithms that integrate genomic mutation data. Results: To address this, we present CONICS: COpy-Number analysis In single-Cell RNA-Sequencing. CONICS is a software tool for mapping gene expression from scRNA-seq to tumor clones and phylogenies, with routines enabling: the quantitation of copy-number alterations in scRNA-seq, robust separation of neoplastic cells from tumor-infiltrating stroma, inter-clone differential-expression analysis and intra-clone co-expression analysis. Availability and implementation: CONICS is written in Python and R, and is available from https://github.com/diazlab/CONICS. Supplementary information: Supplementary data are available at Bioinformatics online.
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Integration of lpWGS CNV profiles with single-cell RNA-seq enables researchers to correlate structural variants with gene-expression changes in cell-line sub-clones, organoids or primary tissue samples.
“This enables researchers to correlate structural variants with gene-expression changes in cell-line sub-clones, organoids or primary tissue samples [52,53].”
From Genetic Insights into the Economic Toll of Cell Line Misidentification: A Comprehensive Review (2026) · cites this paper as [52]
Section 2.1 reports combining scRNA-seq with exome sequencing from a glioblastoma biopsy and examining correlations between CNV status and gene expression. Section 2.3 describes comparing expression networks between inferred tumor clones. Our copy does not establish the claim specifically for lpWGS CNV profiles, cell-line sub-clones, or organoids. (LLM, conf=0.87)
Experimental — accuracy not yet measuredTools like CONICSmat first infer large-scale copy-number states from the expression matrix and then overlay these states onto the corresponding UMAP/t-SNE plots.
“For example, tools like CONICSmat first infer large-scale copy-number states from the expression matrix and then overlay these states onto the corresponding UMAP/t-SNE plots.”
From Genetic Insights into the Economic Toll of Cell Line Misidentification: A Comprehensive Review (2026) · cites this paper as [52]
Section 1 (Introduction) says CONICS identifies large-scale copy-number variants in scRNA-seq, and Section 2.1 identifies CONICSmat as a related package that can be used without DNA-sequencing data. Our copy does not say that CONICSmat overlays inferred states on UMAP or t-SNE plots, so that part of the attributed workflow is unsupported. (LLM, conf=0.83)
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- Authors
- Müller, S., Cho, A., Liu, S. J., Lim, D. A., & Diaz, A.
- Affiliations
- University of California, San Francisco (US)
- Corresponding author
- Diaz, Aaron
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-04-20
- Volume
- 34
- Issue
- 18
- Pages
- 3217-3219
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC7190654
- OpenAlex
- W2802963454
- Cited by
- 117
- References
- 7
- Citations by year
- 2026: 12 · 2025: 18 · 2024: 10 · 2023: 10 · 2022: 28 · 2021: 18 · 2020: 12 · 2019: 6 · 2018: 3
- FWCI
- 3.47
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Bioinformatics (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- Cancer League Research
- NCI Helen Diller Family Comprehensive Cancer Center (P30-CA82103-18)
- UCSF Brain Tumor SPORE Career Development Award (P50-CA097257-13: 7017)
- Dabbiere Family
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- single-cell RNA sequencing, tumor subclones, tumor phylogeny, copy number alterations, gene expression mapping, cancer genomics
- MeSH terms
- Algorithms, Humans, Neoplasms, Software, Sequence Analysis, DNA, Sequence Analysis, RNA, RNA, Small Cytoplasmic, Gene Expression Profiling, Single-Cell Analysis
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