Identification of humoral immune responses in protein microarrays using DNA microarray data analysis techniques. Export

@article{citeulike:1055068, abstract = {MOTIVATION: We present a study of antigen expression signals from a newly developed high-throughput protein microarray technique. These signals are a measure of antibody-antigen binding activity and provide a basis for understanding humoral immune responses to various infectious agents and supporting vaccine and diagnostic development. RESULTS: We investigate the characteristics of these expression profiles and show that noise models, normalization, variance estimation and differential expression analysis techniques developed in the context of DNA microarray analysis can be adapted and applied to these protein arrays. Using a high-dimensional dataset containing measurements of expression profiles of antibody reactivity against each protein (295 antigens and 9 controls) in 42 malaria (Plasmodium falciparum) protein arrays derived from 22 donors with various clinical presentations of malaria, we present a methodology for the analysis and identification of significantly expressed antigens targeted by immune responses for individual sera, groups of sera and across stages of infection. We also conduct a short study highlighting the top immunoreactive antigens where we identify three novel high priority antigens for future evaluation. AVAILABILITY: All software programs (in R) used for the analysis described in this paper are freely available for academic purposes at www.igb.uci.edu/servers/servers.html.}, address = {School of Information and Computer Sciences, University of California, Irvine, CA, USA.}, author = {Sundaresh, S. and Doolan, D. L. and Hirst, S. and Mu, Y. and Unal, B. and Davies, D. H. and Felgner, P. L. and Baldi, P.}, citeulike-article-id = {1055068}, citeulike-linkout-0 = {http://dx.doi.org/10.1093/bioinformatics/btl162}, citeulike-linkout-1 = {http://bioinformatics.oxfordjournals.org/cgi/content/abstract/22/14/1760}, citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/16644788}, citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=16644788}, day = {15}, doi = {10.1093/bioinformatics/btl162}, issn = {1460-2059}, journal = {Bioinformatics}, keywords = {antigen, microarray, stats}, month = {July}, number = {14}, pages = {1760--1766}, posted-at = {2007-01-20 06:45:43}, priority = {2}, title = {Identification of humoral immune responses in protein microarrays using DNA microarray data analysis techniques.}, url = {http://dx.doi.org/10.1093/bioinformatics/btl162}, volume = {22}, year = {2006} }

TY - JOUR ID - citeulike:1055068 L3 - citeulike-article-id:1055068 N2 - MOTIVATION: We present a study of antigen expression signals from a newly developed high-throughput protein microarray technique. These signals are a measure of antibody-antigen binding activity and provide a basis for understanding humoral immune responses to various infectious agents and supporting vaccine and diagnostic development. RESULTS: We investigate the characteristics of these expression profiles and show that noise models, normalization, variance estimation and differential expression analysis techniques developed in the context of DNA microarray analysis can be adapted and applied to these protein arrays. Using a high-dimensional dataset containing measurements of expression profiles of antibody reactivity against each protein (295 antigens and 9 controls) in 42 malaria (Plasmodium falciparum) protein arrays derived from 22 donors with various clinical presentations of malaria, we present a methodology for the analysis and identification of significantly expressed antigens targeted by immune responses for individual sera, groups of sera and across stages of infection. We also conduct a short study highlighting the top immunoreactive antigens where we identify three novel high priority antigens for future evaluation. AVAILABILITY: All software programs (in R) used for the analysis described in this paper are freely available for academic purposes at www.igb.uci.edu/servers/servers.html. IS - 14 JF - Bioinformatics SN - 1460-2059 AD - School of Information and Computer Sciences, University of California, Irvine, CA, USA. EP - 1766 TI - Identification of humoral immune responses in protein microarrays using DNA microarray data analysis techniques. VL - 22 SP - 1760 KW - antigen KW - microarray KW - stats AU - Sundaresh, S AU - Doolan, DL AU - Hirst, S AU - Mu, Y AU - Unal, B AU - Davies, DH AU - Felgner, PL AU - Baldi, P PY - 2006/07/15/ UR - http://dx.doi.org/10.1093/bioinformatics/btl162 ER -