A dataset of chronic nicotine-induced genes in HCC38 breast cancer cells
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Description | Differentially Expressed Genes (DEG) – Excel spreadsheet listing the log2 fold changes (L2FC) and associated adjusted P-values for each downregulated gene in each cluster or the overall sample, comparing chronic nicotine to vehicle-treated cells. Gene names are listed in first column with the corresponding information found in the following columns. |
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- Cite This Work
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Mugisha, Samson; Labhsetwar, Shreyas; Dave, Devam; Klemke, Richard; Desgrosellier, Jay S. (2025). A dataset of chronic nicotine-induced genes in HCC38 breast cancer cells. UC San Diego Library Digital Collections. https://doi.org/10.6075/J04X585F
- Description
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PyDESeq2 and Velocyto (0.6) were used to generate differentially expressed genes (DEG) and identify the most dynamic genes in chronic nicotine-treated and control cells.
- Creation Date
- 2024
- Date Issued
- 2025
- Author
- Principal Investigator
- Analysts
- Technical Details
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For differential gene expression analysis, PyDESeq2 was used to estimate variance-mean dependence in count data from sequencing assays and test for differential expression based on a model using the negative binomial distribution. Velocyto (0.6) was used to estimate the spliced and unspliced counts from the pre-aligned bam files for the dynamic trajectory analysis.
- Funding
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This research was supported by funding from a Tobacco-Related Disease Research Program (TRDRP) High Impact Research Project Award 28IR-0054 (to J.S.D.) and a California Breast Cancer Research Program Grant B28IB5479 (to J.S.D.).
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- Language
- English
- Identifier
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Identifier: Samson Mugisha: https://orcid.org/0000-0003-1528-204X
- Related Resources
- Mugisha, S., Baba, S.A., Labhsetwar, S. et al. S100A8/A9 innate immune signaling as a distinct mechanism driving progression of smoking-related breast cancers. Oncogene (2025). https://doi.org/10.1038/s41388-025-03276-5
- 10x Genomics Single Cell Analysis (on GitHub): https://github.com/10XGenomics/cellranger
- DESeq2: http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html
- Implementation of the Leiden algorithm for various quality functions to be used with igraph in Python (on GitHib): https://github.com/vtraag/leidenalg
- velocyto (velocyto.org)
- RNA sequencing data that support the findings of this study have been deposited in the NCBI Sequence Read Archive (SRA) with the primary accession code PRJNA1145480. scRNA-seq of HCC38 Nicotine (nicotine-treated group): https://www.ncbi.nlm.nih.gov/sra/SRX25630994
- RNA sequencing data that support the findings of this study have been deposited in the NCBI Sequence Read Archive (SRA) with the primary accession code PRJNA1145480. scRNA-seq of HCC38 Vehicle (control group): https://www.ncbi.nlm.nih.gov/sra/SRX25630993
Primary associated publication
Software
Other version
- License
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Creative Commons Attribution 4.0 International Public License
- Rights Holder
- UC Regents
- Copyright
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Under copyright (US)
Use: This work is available from the UC San Diego Library. This digital copy of the work is intended to support research, teaching, and private study.
Constraint(s) on Use: This work is protected by the U.S. Copyright Law (Title 17, U.S.C.). Use of this work beyond that allowed by "fair use" or any license applied to this work requires written permission of the copyright holder(s). Responsibility for obtaining permissions and any use and distribution of this work rests exclusively with the user and not the UC San Diego Library. Inquiries can be made to the UC San Diego Library program having custody of the work.
- Digital Object Made Available By
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Research Data Curation Program, UC San Diego, La Jolla, 92093-0175 (https://lib.ucsd.edu/rdcp)
- Last Modified
2025-03-04