DEPIB
DEPIB analyzes bulk RNA sequencing (RNAseq) data using a Snakemake workflow to identify differentially expressed genes across experimental conditions for studies such as pesticide-induced senescence in human mesenchymal stem cells (MSCs) and temozolomide resistance in glioblastoma (GBM).
Key Features:
- Pipeline Automation: Implements a Snakemake workflow to automate reproducible RNAseq processing steps.
- Differential Expression Analysis: Identifies genes with significant changes in expression across experimental conditions or treatments.
- Bulk RNAseq Processing: Processes bulk RNA sequencing data to compare gene expression profiles between samples.
- Integration with Metabolic and Immune Markers: Integrates transcriptomic results with protein expression analyses of metabolic markers such as MDH1, GOT, and SIRT3 and with immune function assessments.
- Secretome Functional Analysis: Supports analysis of secretome effects on cellular properties, including immunomodulation.
- Longitudinal and Integrative Analyses: Facilitates longitudinal comparisons and integration of RNAseq with other analyses to detect tolerant-like cell populations and chromatin remodeling signatures.
Scientific Applications:
- Environmental Contaminant Impact on Cellular Aging: Analyzes effects of environmental contaminants, including low-dose exposure to a mixture of seven common pesticides, on MSC transcriptomes to identify oxidative stress–induced senescence, shifts toward adipogenesis, and deterioration of immunosuppressive properties compared with aged donor samples.
- Cancer Drug Resistance Mechanisms: Characterizes gene expression changes associated with temozolomide (TMZ) resistance in glioblastoma (GBM), enabling identification of tolerant-like cell populations, chromatin remodeling events, and potential therapeutic targets.
Methodology:
DEPIB uses a Snakemake workflow to process bulk RNAseq data for differential expression analysis and integrates transcriptomic results with protein-level metabolic marker analyses and functional secretome assessments.
Topics
Details
- Maturity:
- Emerging
- Cost:
- Free of charge
- Tool Type:
- workflow
- Programming Languages:
- R, Python
- Added:
- 9/24/2019
- Last Updated:
- 11/24/2024
Operations
Data Inputs & Outputs
RNA-Seq quantification
Outputs
Publications
Leveque X, Hochane M, Geraldo F, Dumont S, Gratas C, Oliver L, Gaignier C, Trichet V, Layrolle P, Heymann D, Herault O, Vallette FM, Olivier C. Low-Dose Pesticide Mixture Induces Accelerated Mesenchymal Stem Cell Aging In Vitro. Stem Cells. 2019;37(8):1083-1094. doi:10.1002/stem.3014. PMID:30977188. PMCID:PMC6850038.
Rabé M, Dumont S, Álvarez-Arenas A, Janati H, Belmonte-Beitia J, Calvo GF, Thibault-Carpentier C, Séry Q, Chauvin C, Joalland N, Briand F, Blandin S, Scotet E, Pecqueur C, Clairambault J, Oliver L, Perez-Garcia V, Nadaradjane A, Cartron P, Gratas C, Vallette FM. Identification of a transient state during the acquisition of temozolomide resistance in glioblastoma. Cell Death & Disease. 2020;11(1). doi:10.1038/s41419-019-2200-2. PMID:31907355. PMCID:PMC6944699.