WIFA Wavelet-based Identification of DNA focal genomic aberrations


2011/06/17: New source codes and data sets are updated.
It integrates array CGH data sets from multiple cancer samples and detects consistent aberrations across multiple samples. The use of the wavelet analysis, being a multi-resolution approach, makes it possible to effectively identify focal genomic aberrations in the broadly aberrant regions.
Paper Hur, Y. and Lee, H. (2011) Wavelet-based identification of DNA focal genomic aberrations from single nucleotide polymorphism arrays. BMC Bioinformatics, 12:146
Source codes
Source codes are available here, and one example data can be downloaded from here. WIFAfunction is a main matlab function for WIFA, and diary_WIFA.m is an example file calling this function. (To run this matlab code, users need to download wavelab first.)
Data sets

WIFAfunction requires two input files. aCGHFile is a tab-separate file and each column contains the log2 intensity ratio of array CGH data of one sample. aCGHLocation is a comma-separate file with three columns of probe-id, chromosomes, and positions of probes. The sample files for aCGHFile and aCGHLocation are included in the source codes. Note that these are random subsets of CGH data files.

The data sets used in the WIFA paper can be found in Beroukhim et al., 2007, Kotliarov et al., 2006, and Weir et al., 2007.

hyunjulee at gist.ac.kr, hur at jhu.edu