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Gene expression profiling in rats with depressive-like behavior
Individual differences indicate stronger phenotypes than model animals especially in behavioral studies, and some animals show unexpected behaviors in control and animal model groups. High-throughput analysis including cDNA microarray analysis are more affected by individual differences, because mor...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4583661/ https://www.ncbi.nlm.nih.gov/pubmed/26484268 http://dx.doi.org/10.1016/j.gdata.2015.04.030 |
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author | Yamamoto, Yuta Ueyama, Takashi Ito, Takao Tsuruo, Yoshihiro |
author_facet | Yamamoto, Yuta Ueyama, Takashi Ito, Takao Tsuruo, Yoshihiro |
author_sort | Yamamoto, Yuta |
collection | PubMed |
description | Individual differences indicate stronger phenotypes than model animals especially in behavioral studies, and some animals show unexpected behaviors in control and animal model groups. High-throughput analysis including cDNA microarray analysis are more affected by individual differences, because more samples are needed to reduce the difference in multiple factor analysis than single factor analysis such as real-time PCR. We measured the depressive-like behavior of over 100 normal rats in the forced swimming test and selected the rats for control and depression group from them to minimize the individual difference using data of force swimming test. Here, we provided the detail of methods and quality control parameters for the cDNA microarray data. This dataset can reflect the increase of depressive-like behavior. The dataset is deposited in the gene expression omnibus (GEO), series GSE63377. |
format | Online Article Text |
id | pubmed-4583661 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-45836612015-10-19 Gene expression profiling in rats with depressive-like behavior Yamamoto, Yuta Ueyama, Takashi Ito, Takao Tsuruo, Yoshihiro Genom Data Data in Brief Individual differences indicate stronger phenotypes than model animals especially in behavioral studies, and some animals show unexpected behaviors in control and animal model groups. High-throughput analysis including cDNA microarray analysis are more affected by individual differences, because more samples are needed to reduce the difference in multiple factor analysis than single factor analysis such as real-time PCR. We measured the depressive-like behavior of over 100 normal rats in the forced swimming test and selected the rats for control and depression group from them to minimize the individual difference using data of force swimming test. Here, we provided the detail of methods and quality control parameters for the cDNA microarray data. This dataset can reflect the increase of depressive-like behavior. The dataset is deposited in the gene expression omnibus (GEO), series GSE63377. Elsevier 2015-06-11 /pmc/articles/PMC4583661/ /pubmed/26484268 http://dx.doi.org/10.1016/j.gdata.2015.04.030 Text en © 2015 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Data in Brief Yamamoto, Yuta Ueyama, Takashi Ito, Takao Tsuruo, Yoshihiro Gene expression profiling in rats with depressive-like behavior |
title | Gene expression profiling in rats with depressive-like behavior |
title_full | Gene expression profiling in rats with depressive-like behavior |
title_fullStr | Gene expression profiling in rats with depressive-like behavior |
title_full_unstemmed | Gene expression profiling in rats with depressive-like behavior |
title_short | Gene expression profiling in rats with depressive-like behavior |
title_sort | gene expression profiling in rats with depressive-like behavior |
topic | Data in Brief |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4583661/ https://www.ncbi.nlm.nih.gov/pubmed/26484268 http://dx.doi.org/10.1016/j.gdata.2015.04.030 |
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