This README.txt file was generated on 2022-03-16 by Dominik Saul GENERAL INFORMATION 1. Title of Dataset: Data from: Modulation of fracture healing by the transient accumulation of senescent cells 2. Author Information Corresponding Investigator Name: Sundeep Khosla Institution: Division of Endocrinology, Mayo Clinic, Rochester, United States Email: Khosla.Sundeep@mayo.edu Corresponding Investigator Name: Joshua N. Farr Institution: Division of Endocrinology, Mayo Clinic, Rochester, United States Email: Farr.Joshua@mayo.edu Co-investigator 1 Name: Dominik Saul Institution: Division of Endocrinology, Mayo Clinic, Rochester, United States Co-investigator 2 Name: David G. Monroe Institution: Division of Endocrinology, Mayo Clinic, Rochester, United States Co-investigator 3 Name: Jennifer L. Rowsey Institution: Division of Endocrinology, Mayo Clinic, Rochester, United States Co-investigator 4 Name: Robyn Laura Kosinsky Institution: Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, United States Co-investigator 5 Name: Stephanie J Vos Institution: Division of Endocrinology, Mayo Clinic, Rochester, United States Co-investigator 5 Name: Madison L. Doolittle Institution: Division of Endocrinology, Mayo Clinic, Rochester, United States 3. Data of data collection: 2020-2021 4. Geographic location of data collection: Rochester, MN, United States 5. Funding sources that supported the collection of the data: P01 AG062413, R21 AG065868, R01 AG063707, R01 DK128552, 413501650 6. Recommended citation for this dataset: Saul, D., Monroe, D. G., Rowsey, J. L., Kosinsky, R. L., Vos, S. J., Doolittle, M. L., Farr, J. N., & Khosla, S. (2021). Modulation of fracture healing by the transient accumulation of senescent cells. eLife, 10, e69958. https://doi.org/10.7554/eLife.69958 Add to Citavi project by DOI DATA & FILE OVERVIEW 1. Description of dataset Clinical and demographic data have not been included in the dataset as they contain sensitive and potentially identifying information. METHODOLOGICAL INFORMATION The RNA-seq data were generated to investigate the fracture healing process in mice. To evaluate transcriptome-wide changes underlying the different stages of fracture healing, we analyzed publicly available mRNA-seq data of murine femoral fracture sites as well as intact control femora at five specific time points (Coates et al., 2019). The DE genes are depicted in these *.csv files: RNA-Seq raw results: 2. File list: res_intactvs7d.csv res_intactvs14d.csv res_intactvs1d.csv res_intactvs4hr.csv res_intactvs3d.csv All figures raw data: raw_data.xlsx For a detailed descripton on the methods, please see our manuscript: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8526061/