Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

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SEQC Toxicogenomics Study: RNA-Seq data set


ABSTRACT: The comparative advantages of RNA-Seq and microarrays in transcriptome profiling were evaluated in the context of a comprehensive study design. Gene expression data from Illumina RNA-Seq and Affymetrix microarrays were obtained from livers of rats exposed to 27 agents that comprised of seven modes of action (MOAs); they were split into training and test sets and verified with real time PCR. 105 samples were selected from the DrugMatirx tissue/RNA bank that is now owned by the National Toxicology Program (NTP). The samples were split into 2 sets, training and test, to allow for the evaluation of classifiers derived from the data. There were 63 samples in the training set and 42 in the test set. Of the 63 samples in the training set 45 were derived from rats treated with test agent and 18 were control samples (3 sets of 6). 39 of the test set samples were derived from test agent treated animals and 6 were from vehicle and route matched controls. Five MOAs were represented in the training set and 4 MOAs were in the test set. Two of the MOAs were duplicated from the test set and two were without representation in the training set. For each test agent there were three rats treated, in accordance with the common practice in the field of toxicology. For each MOA there were three representative test agents to ensure adequate power for detecting the MOA signatures. 6 samples from the training set had duplicate libraries sequenced and duplicate sequencing runs for the first library. DrugMatrix, National Toxicology program (NTP) Sequencing was carried out in Dr. Charles Wang's Functional Genomics Core at City of Hope Comprehensive Cancer Center, Duarte, CA

ORGANISM(S): Rattus norvegicus

SUBMITTER: Leming Shi 

PROVIDER: E-GEOD-55347 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance.

Wang Charles C   Gong Binsheng B   Bushel Pierre R PR   Thierry-Mieg Jean J   Thierry-Mieg Danielle D   Xu Joshua J   Fang Hong H   Hong Huixiao H   Shen Jie J   Su Zhenqiang Z   Meehan Joe J   Li Xiaojin X   Yang Lu L   Li Haiqing H   Łabaj Paweł P PP   Kreil David P DP   Megherbi Dalila D   Gaj Stan S   Caiment Florian F   van Delft Joost J   Kleinjans Jos J   Scherer Andreas A   Devanarayan Viswanath V   Wang Jian J   Yang Yong Y   Qian Hui-Rong HR   Lancashire Lee J LJ   Bessarabova Marina M   Nikolsky Yuri Y   Furlanello Cesare C   Chierici Marco M   Albanese Davide D   Jurman Giuseppe G   Riccadonna Samantha S   Filosi Michele M   Visintainer Roberto R   Zhang Ke K KK   Li Jianying J   Hsieh Jui-Hua JH   Svoboda Daniel L DL   Fuscoe James C JC   Deng Youping Y   Shi Leming L   Paules Richard S RS   Auerbach Scott S SS   Tong Weida W  

Nature biotechnology 20140824 9


The concordance of RNA-sequencing (RNA-seq) with microarrays for genome-wide analysis of differential gene expression has not been rigorously assessed using a range of chemical treatment conditions. Here we use a comprehensive study design to generate Illumina RNA-seq and Affymetrix microarray data from the same liver samples of rats exposed in triplicate to varying degrees of perturbation by 27 chemicals representing multiple modes of action (MOAs). The cross-platform concordance in terms of di  ...[more]

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