Introduction to expO Land Content

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The mission of Expression Project for Oncology (expO) is to build on the technologies and outcomes of the Human Genome Project to accelerate improved clinical management of cancer patients. IGC's expO seeks to integrate longitudinal clinical annotation with gene expression data for a unique and powerful portrait of human malignancies, providing critical perspective on diagnostic markers, prognostic indicators, and therapeutic targets.

The goal of expO and its consortium supporters is to procure tissue samples under standard conditions and perform gene expression analyses on a clinically annotated set of de-identified tumor samples. The tumor data are updated with clinical outcomes and released into the public domain without intellectual property restriction.

Data Source


Land Version Genome Build Gene Model
expO_B37 Human.B37.3 OmicsoftGene20130723

Data Type

  • Expression Intensity Probes (Affymetrix)

Laboratory Methods

Affymetrix Expression Array

Processing Methods

Expression Data: Omicsoft Affymetrix Microarray Preprocessing

Key Meta Data Columns:

  • Land Tissue: is curated by Omicsoft Land cutation team using Omicsoft's control vocabularies. Allow users to easily merge the data with other Lands. - this is the primary grouping column in this land.
  • Histology: Histological types of cancer such as carcinoma, glioma and sarcoma. This is the secondary grouping column in this land.
  • DiseaseState (controlled vocabulary) : Curated at sample level from each project.
  • TissueCategory (controlled vocabulary) : Tissue category such as skin, muscle, heart, kidney etc.
  • SampleSource (controlled vocabulary) : Either cell type or tissue information. When a sample has cell type information, cell type is used. Otherwise, tissue category is used.
  • Land Sample Type: is curated by Omicsoft Land curation team using Omicsoft's control vocabularies. Allow users to easily merge the data with other Lands.
  • Tumor or Normal: indicates whether a sample is from tumor sample for normal sample. All GTEx data are normal samples.

Key Views

Gene Expression: expO Land currently only contains expression array data. The most common way to browse the data is to examine gene expression levels across sample meta data or clinical variables. expO Land provides a variety of clinical variables, allowing users to research differential expression among different clinical status.


Example: GATA3 gene expression levels grouped by ER Status. As we can see, ER positive samples has significant higher GATA3 expression, suggesting a correlation between ER Status and GATA3 expression in breast cancer.

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