Literature DB >> 19759808

Identification of differentially expressed spatial clusters using humoral response microarray data.

Jincao Wu1, Tasneem H Patwa, David M Lubman, Debashis Ghosh.   

Abstract

The antibody microarray is a powerful chip-based technology for profiling hundreds of proteins simultaneously and is used increasingly nowadays. To study humoral response in pancreatic cancers, Patwa et al. (2007) developed a two-dimensional liquid separation technique and built a two-dimensional antibody microarray. However, identifying differential expression regions on the antibody microarray requires the use of appropriate statistical methods to fairly assess the large amounts of data generated. In this paper, we propose a permutation-based test using spatial information of the two-dimensional antibody microarray. By borrowing strength from the neighboring differentially expressed spots, we are able to detect the differential expression region with very high power controlling type I error at 0.05 in our simulation studies. We also apply the proposed methodology to a real microarray dataset.

Entities:  

Year:  2009        PMID: 19759808      PMCID: PMC2685285          DOI: 10.1016/j.csda.2008.04.026

Source DB:  PubMed          Journal:  Comput Stat Data Anal        ISSN: 0167-9473            Impact factor:   1.681


  5 in total

1.  A test for spatial disease clustering adjusted for multiple testing.

Authors:  T Tango
Journal:  Stat Med       Date:  2000-01-30       Impact factor: 2.373

2.  Global, voxel, and cluster tests, by theory and permutation, for a difference between two groups of structural MR images of the brain.

Authors:  E T Bullmore; J Suckling; S Overmeyer; S Rabe-Hesketh; E Taylor; M J Brammer
Journal:  IEEE Trans Med Imaging       Date:  1999-01       Impact factor: 10.048

3.  A class of multiplicity adjusted tests for spatial clustering based on case-control point data.

Authors:  Toshiro Tango
Journal:  Biometrics       Date:  2007-03       Impact factor: 2.571

4.  Analysis of functional signaling domains from fluorescence imaging and the two-dimensional continuous wavelet transform.

Authors:  Donald E Mager; Evgeny Kobrinsky; Amirali Masoudieh; Anna Maltsev; Darrell R Abernethy; Nikolai M Soldatov
Journal:  Biophys J       Date:  2007-06-22       Impact factor: 4.033

5.  HBM functional imaging analysis contest data analysis in wavelet space.

Authors:  John A D Aston; Federico E Turkheimer; Matthew Brett
Journal:  Hum Brain Mapp       Date:  2006-05       Impact factor: 5.038

  5 in total
  1 in total

Review 1.  Overview of techniques to account for confounding due to population stratification and cryptic relatedness in genomic data association analyses.

Authors:  M J Sillanpää
Journal:  Heredity (Edinb)       Date:  2010-07-14       Impact factor: 3.821

  1 in total

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