Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2006 Jan 1;34(Database issue):D613-6.
doi: 10.1093/nar/gkj022.

ITTACA: a new database for integrated tumor transcriptome array and clinical data analysis

Adil Elfilali  1 , Séverine Lair, Catia Verbeke, Philippe La Rosa, François Radvanyi, Emmanuel Barillot
Affiliations

ITTACA: a new database for integrated tumor transcriptome array and clinical data analysis

Adil Elfilali et al. Nucleic Acids Res. .

Abstract

Transcriptome microarrays have become one of the tools of choice for investigating the genes involved in tumorigenesis and tumor progression, as well as finding new biomarkers and gene expression signatures for the diagnosis and prognosis of cancer. Here, we describe a new database for Integrated Tumor Transcriptome Array and Clinical data Analysis (ITTACA). ITTACA centralizes public datasets containing both gene expression and clinical data. ITTACA currently focuses on the types of cancer that are of particular interest to research teams at Institut Curie: breast carcinoma, bladder carcinoma and uveal melanoma. A web interface allows users to carry out different class comparison analyses, including the comparison of expression distribution profiles, tests for differential expression and patient survival analyses. ITTACA is complementary to other databases, such as GEO and SMD, because it offers a better integration of clinical data and different functionalities. It also offers more options for class comparison analyses when compared with similar projects such as Oncomine. For example, users can define their own patient groups according to clinical data or gene expression levels. This added flexibility and the user-friendly web interface makes ITTACA especially useful for comparing personal results with the results in the existing literature. ITTACA is accessible online at http://bioinfo.curie.fr/ittaca.

PubMed Disclaimer

Figures

Figure 1
Figure 1
The workflow/outline of ITTACA. The first step (I, upper part of the figure) in ITTACA is the choice of the publication the user wishes to study. Then (step II, middle part of the figure) the user can define groups of tumors or select genes (or both). There are four methods for building tumor groups (represented by a right-angled box): manual choice from the list of tumors, selection based on clinical parameters or on survival time (Kaplan-Meier curve), or on a gene expression threshold. The ovals represent the different analyses that can be carried out with ITTACA (step III, bottom part of the figure): (A) KM is the Kaplan-Meier survival curve; it also includes a log-rank test to assess significance of different survival. (B) SAM (8) is a statistical method for finding significantly differentially expressed genes in a set of microarray experiments for a given FDR. (C) The differential expression tests used by ITTACA are the Wilcoxon (non-parametric) test and the Student's (parametric) t-test. ITTACA allows a descriptive analysis of the data, with a gene expression barplot (D) and/or the sample's frequency according to the expression level for a gene (E) (frequency distribution).
See this image and copyright information in PMC

References

    1. Brazma A., Hingamp P., Quackenbush J., Sherlock G., Spellman P., Stoecker C., Aach J., Ansorge W., Ball C.A., Causton H.C., et al. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nature Genet. 2001;29:365–371. - PubMed
    1. Ball C.A., Brazma A., Causton H., Chervitz S., Edgar R., Hingamp P., Matese J.C., Parkinson H., Quackenbush J., Ringwald M., et al. Submission of microarray data to public repositories. PLoS Biol. 2004;2:e317. - PMC - PubMed
    1. Barrett T., Suzek T.O., Troup D.B., Wilhite S.E., Ngau W.C., Ledoux P., Rudnev D., Lash A.E., Fujibuchi W., Edgar R. NCBI GEO: mining millions of expression profiles—database and tools. Nucleic Acids Res. 2005;33:D562–566. - PMC - PubMed
    1. Parkinson H., Sarkans U., Shojatalab M., Abeygunawardena N., Contrino S., Coulson R., Farne A., Lara G.G., Holloway E., Kapushesky M., et al. ArrayExpress: a public repository for microarray gene expression data at the EBI. Nucleic Acids Res. 2005;33:D553–D555. - PMC - PubMed
    1. Bussey K.J., Kane D., Sunshine M., Narasimhan S., Nishizuka S., Reinhold W.C., Zeeberg B., Ajay W., Weinstein J.N. MatchMiner: a tool for batch navigation among gene and gene product identifiers. Genome Biol. 2003;4:R27. - PMC - PubMed

Publication types