19352488

Source:http://linkedlifedata.com/resource/pubmed/id/19352488

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Predicate	Object
rdf:type	pubmed:Citation
lifeskim:mentions	umls-concept:C0012632, umls-concept:C0026986, umls-concept:C0032863, umls-concept:C0752046, umls-concept:C0936012, umls-concept:C1510941, umls-concept:C1527178, umls-concept:C1705938, umls-concept:C2603343
pubmed:issue	4
pubmed:dateCreated	2009-4-8
pubmed:abstractText	Copy Number Aberration (CNA) in myelodysplastic syndromes (MDS) study using single nucleotide polymorphism (SNP) arrays have been received increasingly attentions in the recent years. In the current study, a new Constraint Moving Average (CMA) algorithm is adopted to determine the regions of CNA regions first. In addition to large regions of CNA, using the proposed CMA algorithm, small regions of CNA can also be detected. Real-time Polymerase Chain Reaction (qPCR) results prove that the CMA algorithm presents an insightful discovery of both large and subtle regions. Based on the results of CMA, two independent applications are studied. The first one is power analysis for sample estimation. An accurate estimation of sample size needed for the desired purpose of an experiment will be important for effort-efficiency and cost-effectiveness. The power analysis is performed to determine the minimum sample size required for ensuring at least (0<lambda <or=) detected regions statistically different from normal references. As expected, power increase with increasing sample size for a fixed significance level. The second application is the distinguishment of high-grade MDS patients from low-grade ones. We propose to calculate the General Variant Level (GVL) score to integrate the general information of each patient at genotype level, and use it as the unified measurement for the classification. Traditional MDS classifications usually refer to cell morphology and The International Prognostic Scoring System (IPSS), which belongs to the classification at the phenotype level. The proposed GVL score integrates the information of CNA region, the number of abnormal chromosomes and the total number of the altered SNPs at the genotype level. Statistical tests indicate that the high and low grade MDS patients can be well separated by GVL score, which appears to correlate better with clinical outcome than the traditional classification approaches using morphology and IPSS sore at the phenotype level.
pubmed:grant	http://linkedlifedata.com/resource/pubmed/grant/R01 LM010185-03
pubmed:commentsCorrections	http://linkedlifedata.com/resource/pubmed/commentcorrection/19352488-10521349, http://linkedlifedata.com/resource/pubmed/commentcorrection/19352488-11134512, http://linkedlifedata.com/resource/pubmed/commentcorrection/19352488-11435405, http://linkedlifedata.com/resource/pubmed/commentcorrection/19352488-11532216, http://linkedlifedata.com/resource/pubmed/commentcorrection/19352488-11943347, http://linkedlifedata.com/resource/pubmed/commentcorrection/19352488-14502253, http://linkedlifedata.com/resource/pubmed/commentcorrection/19352488-14745424, http://linkedlifedata.com/resource/pubmed/commentcorrection/19352488-15126342, http://linkedlifedata.com/resource/pubmed/commentcorrection/19352488-16024607, http://linkedlifedata.com/resource/pubmed/commentcorrection/19352488-16131523, http://linkedlifedata.com/resource/pubmed/commentcorrection/19352488-16154839, http://linkedlifedata.com/resource/pubmed/commentcorrection/19352488-17634407, http://linkedlifedata.com/resource/pubmed/commentcorrection/19352488-17726160, http://linkedlifedata.com/resource/pubmed/commentcorrection/19352488-17920760, http://linkedlifedata.com/resource/pubmed/commentcorrection/19352488-7748962, http://linkedlifedata.com/resource/pubmed/commentcorrection/19352488-9058730
pubmed:language	eng
pubmed:journal	http://linkedlifedata.com/resource/pubmed/journal/101285081
pubmed:citationSubset	IM
pubmed:status	MEDLINE
pubmed:issn	1932-6203
pubmed:author	pubmed-author:ChangChung-CheCC, pubmed-author:HuangWan-TingWT, pubmed-author:MonzonFederico AFA, pubmed-author:WongStephen T CST, pubmed-author:WuLingyunL, pubmed-author:YangXiaorongX, pubmed-author:ZhouXiaoboX
pubmed:issnType	Electronic
pubmed:volume	4
pubmed:owner	NLM
pubmed:authorsComplete	Y
pubmed:pagination	e5054
pubmed:dateRevised	2011-8-11
pubmed:meshHeading	pubmed-meshheading:19352488-Algorithms, pubmed-meshheading:19352488-Gene Dosage, pubmed-meshheading:19352488-Humans, pubmed-meshheading:19352488-Myelodysplastic Syndromes, pubmed-meshheading:19352488-Polymerase Chain Reaction, pubmed-meshheading:19352488-Polymorphism, Single Nucleotide
pubmed:year	2009
pubmed:articleTitle	Pattern-selection based power analysis and discrimination of low- and high-grade myelodysplastic syndromes study using SNP arrays.
pubmed:affiliation	Department of Radiology, The Methodist Hospital Research Institute, Weill Medical College, Cornell University, Center for Biotechnology & Informatics, Houston, Texas, United States of America.
pubmed:publicationType	Journal Article, Research Support, Non-U.S. Gov't