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Analysis of the short heterodimeric partner (SHP/Nr0b2) and SHP/Lep-regulated transcriptomes in mouse liver

Overview

Dataset Name :

Analysis of the short heterodimeric partner (SHP/Nr0b2) and SHP/Lep-regulated transcriptomes in mouse liver

Description :

Livers were removed from 12 week old male mice in the following backgrounds: (1) wild type; (2) SHP/Nr0b2 KO; and (3) SHP/Nr0b2-Lep double KO.

Dataset Type :

Transcriptomic

Release Date :

March 27, 2015

DOI :

10.1621/datasets.04009

Version :

This is Version 1.0 of an annotated derivative of the original dataset, which can be found in GSE40775

Dataset Citation :

Dataset has incomplete record (Missing Pubmed Information)

Download Citation :

Associated Article :

View Abstract | View PubMed | View Article

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Experiments

There are 2 Experiments for this dataset. Up to the 50 up and down p < 0.05 FDR data points are displayed for each. Please download the dataset to view all data points.

1 | SHP/Nr0b2-Lep DKO vs WT
2 | SHP/Nr0b2 KO vs WT

Gene List

Scatter Plot
Conditions

Experiment Information

Name :	SHP/Nr0b2-Lep DKO vs WT
Description :	Livers were removed from 12 week old SHP/Nr0b2 null/leptin null (Lep KO) mutant male mice and wild-type male mice.
Tissue/Cell line :	whole liver
Species :	House Mouse

Fold Change Information x

Additional Information

Annotation :

Note that the fold changes in SPP transcriptomic datasets may differ from those in the associated published article. This is because published articles rarely contain a description of how the fold changes were calculated from the normalized intensity values. As a result, SPP curators are unable to exactly recapitulate this step. In the absence of this information, and in the interests of transparency and consistency, SPP curator-calculated gene fold changes are generated solely by applying an industry standard procedure to the investigator-provided normalized array feature expression intensities in the original dataset deposition. While we do our best to minimize differences, and always cross-check the fold changes we generate with those of selected genes reported in the associated article, some small discrepancies are inevitable. For more information on the SPP transcriptomic dataset processing pipeline, click here.

Licensing :

Use of this dataset is governed by a Creative Commons Attribution 3.0 license, which provides for sharing, adaptation and both non-commercial and commercial re-use, as long as this dataset is cited.

Persistence :

The SPP is committed to maintaining persistent identifiers that will continue to resolve to a landing page providing metadata describing the data, including elements of stewardship, provenance, and availability.

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To reduce the number of data points, please increase the stringency of the p-value from its default setting (e.g. Select “Other”, then enter 0.01, 0.001, etc), or narrow your search to a specific biosample category (e.g. Metabolic…Liver).

Alternatively the data points can be downloaded in Excel.

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To reduce the number of data points, please increase the stringency of the p-value cut-off from its default setting (e.g. Select “Other”, then enter 0.01, 0.001, etc), or narrow your search to a specific biosample category (e.g. Metabolic…Liver).

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NURSA Retirement Notice!

NURSA

Nuclear Receptor Signaling Atlas

After more than 15 years of support from NIDDK, and as announced in our last newsletter, the NURSA website as it currently exists is being retired in March 2020. We would like to place on record our deep appreciation of the support of NIDDK over the 15 years of NURSA's existence, as well as from our community of users.

Please note the following important announcements:

NURSA is succeeded by the Signaling Pathways Project (SPP), an integrated transcriptomic/ChIP-Seq knowledgebase for mammalian cellular signaling pathways. An article on SPP was recently published in Nature Scientific Data.
All NURSA-biocurated transcriptomic datasets have been preserved for data mining in SPP through an enhanced and expanded version of Transcriptomine named Ominer.
SPP is supported by NIDDK through dkNET, and will be powering a planned hypothesis generation environment on dkNET, the Hypothesis Center. All non-transcriptomic dataset NURSA content will be transferred to dkNET, with whom we are evaluating options for archiving this content. Please sign up on the dkNET and SPP Twitter feeds for future updates on archiving of this content.
Please direct any questions to support@signalingpathways.org