adacgh   -  


ADaCGH2: analysis of data from aCGH

ADaCGH2 is a web tool for the analysis of aCGH data sets. We focus on calling gains and losses and estimating the number of copy changes.

This version of ADaCGH2 uses, underneath, the ADaCGH2 BioConductor package by R.Diaz-Uriarte (2014) and presents several key changes and simplifications with respect to the original web-based application. Many methods (that are slow for large data sets ---see the 2014 paper and its supplementary material) are no longer provided in the web application (but they are available from the BioConductor pakage) and we do not offer the option to find common regions as those were obsolte (see our review, Rueda and Diaz-Uriarte, 2010).

This web-based application is provided as a convenience. However, you are strongly suggested to use the BioConductor package as it allows you, for instance, to deal with missing values and analyze much larger samples than we can afford to upload via the internet.

To use ADaCGH provide either one or two files. If you only provide one file, that file must contain also coordinates (location information) of each of the genes/clones. If you provide two different files, one must contain the the aCGH data themselves and another one the mapping of those genes/clones to positions in chromosomes.

Input files (help)

Two files: (aCGH data + coordinates)
Genomic data file:
Coordinate/position information file:

One file (First column are names, next three columns are coordinates.)

Genomic data + coordinate information file:


Median centering Mean centering None

Centering is done on a per-array basis. Some methods do require that data be centered, and for others centering simplifies interpretation. See further details in the help

Method (help)

CBS: Olshen & Venkatraman's circular binary segmentation (CBS).

HaarSeg: a wavelet-based approach by Ben-Yaacov & Eldat

Click "Submit" to send the data to the server and start execution. If the servers are too busy, you will be asked to try again later.


Citing this web application

We ask that, if you use this web application, you give credit both to the original application (Diaz-Uriarte and Rueda, 2007), on which this builds uppon, and the new BioConductor package ADaCGH2 (Diaz-Uriarte, 2014).

Diaz-Uriarte, R. "ADaCGH2: parallelized analysis of (big) CNA data", Bioinformatics, 2014, 30: 1759-1761.

Diaz-Uriarte, R and Rueda, OM. "ADaCGH: A Parallelized Web-Based Application and R Package for the Analysis of aCGH Data", PLoS ONE, 2007, 2 (8): e737.

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