Journal article
Mahmoud Ahmed, Do Sik Min, Deok Ryong Kim
Adipocyte, vol. 9(1), 2020, pp. 600-608
Adipocyte, vol. 9(1), 2020, pp. 600-608
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APA
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Ahmed, M., Min, D. S., & Kim, D. R. (2020). Curated gene expression dataset of differentiating 3T3-L1 adipocytes under pharmacological and genetic perturbations. Adipocyte, 9(1), 600–608. https://doi.org/10.1080/21623945.2020.1829852
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Ahmed, Mahmoud, Do Sik Min, and Deok Ryong Kim. “Curated Gene Expression Dataset of Differentiating 3T3-L1 Adipocytes under Pharmacological and Genetic Perturbations.” Adipocyte 9, no. 1 (2020): 600–608.
MLA
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Ahmed, Mahmoud, et al. “Curated Gene Expression Dataset of Differentiating 3T3-L1 Adipocytes under Pharmacological and Genetic Perturbations.” Adipocyte, vol. 9, no. 1, 2020, pp. 600–08, doi:10.1080/21623945.2020.1829852.
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@article{mahmoud2020a,
title = {Curated gene expression dataset of differentiating 3T3-L1 adipocytes under pharmacological and genetic perturbations},
year = {2020},
issue = {1},
journal = {Adipocyte},
pages = {600-608},
volume = {9},
doi = {10.1080/21623945.2020.1829852},
author = {Ahmed, Mahmoud and Min, Do Sik and Kim, Deok Ryong}
}
Abstract
The 3T3-L1 cell line is used as an adipocyte differentiation model for the analysis of genes specifically expressed during the differentiation course. This cell model has several applications in obesity and insulin resistance research. We built a data resource to model gene expression of differentiating and mature adipocytes in response to several drugs and gene manipulations. We surveyed the literature survey for microarray datasets of differentiating 3T3-L1 cell line sampled at one or more time points under genetic or pharmacological perturbations. Data and metadata were obtained from the gene expression omnibus. The metadata were manually curated using unified language across the studies. Probe intensities were mapped and collapsed to genes using a reproducible pipeline. Samples were classified into none, genetically or pharmacologically modified. In addition to the clean datasets, two aggregated sets were further homogenized for illustration purposes. The curated datasets are available as an R/Bioconductor experimental data package curatedAdipoArray. The package documents the source code of the data collection, curation and processing. Finally, we used a subset of the data to effectively remove batch effects and reproduce biological observations.
