PhenoGen Website Overview

The PhenoGen website shares experimental data with a worldwide community of investigators and provides a flexible, integrated, multi-resolution repository of neuroscience transcriptomic genetic data for collaborative research on genomic disorders.

The website provides a comprehensive system to organize, query, analyze, and retrieve high-throughput gene expression data, as well as providing users with computational tools for integrated analysis of neuroscience data, biomedical literature, gene functional annotations, and Quantitative Trait Loci (QTLs).

The PhenoGen website allows data to be classified as "Semi-public" or "Open Access". All of the information about the data uploaded at the PhenoGen website is visible to every registered user (see "Registering an Account" for details). Registered users have full access to data that is classified as "Open Access" and do not need to obtain permission from the curator (Principal Investigator) of the data. "Semi-public" data can only be accessed and downloaded after the curator of the data grants a user permission to do so. Registered users can use the data for "in-silico" analysis or can download the data for analysis with their own statistical software.

The website also has nine pre-compiled “Public” microarray datasets that can be used and downloaded by all registered users for gene expression analysis, including correlating with user-provided phenotype data. These datasets include inbred and recombinant inbred mice and rat strains.

The PhenoGen website allows you to:

Upload microarray raw data into a MIAME-compliant database.
Upload gene lists.
Share data with other investigators around the world.
Search literature and save results.
Translate gene identifiers to and from multiple databases.
Determine phenotypic QTLs using BXD recombinant inbred mice, HXB/BXH recombinant inbred rats, or LXS recombinant inbred mice.
Match physical location of genes of interest and their eQTL to phenotypic QTLs.
Correlate gene expression with a phenotype.

You can also perform:

Microarray data quality control analysis and normalization.
Data filtering (noise filtering).
Statistical analyses, including the most common statistical tests and permutations.
Promoter analysis (transcription factors).
Queries about genetic variations (e.g. SNPs or polymorphisms) in the transcripts of interest.

Website Process Flow for Microarray Analyses

Analyze Microarray Data

The process flow for a microarray analysis is:

Dataset Creation

Upload microarray data. If you have microarray data from a lab experiment, you can upload it into a MIAME-compliant database that is part of the PhenoGen website.

Retrieve arrays.
Select and merge arrays from the data repository.
Finalize dataset.
Run quality control measures on the merged arrays.
Review quality control results.

Dataset Preparation

Group the arrays based on your hypothesis (e.g., disease vs. control).
Normalize the dataset.

Dataset Analysis

Select a single normalized version.
Select analysis type.
Filter genes.
Perform statistical analysis.
Perform a multiple testing adjustment
Save gene lists.

Research Gene Lists

Do one of the following to enter a gene list in PhenoGen:

Generate a gene list from microarray analysis (see the preceding Analyze Microarray Data section.)

Upload a gene list if you have an existing gene list to interpret.

When your gene list is on the website, use the annotation, QTL, literature search, and promoter analysis tools to help interpret your list of candidate genes.