Association between HTR2C gene polymorphisms and the metabolic syndrome in patients using antipsychotics: a replication study [0.03%]
五羟色胺2C受体基因多态性与抗精神病药物使用者的代谢综合征的关联：重复验证研究
A J Risselada,J Vehof,R Bruggeman et al.
A J Risselada et al.
In two previous studies we found an association between HTR2C polymorphisms and the prevalence of the metabolic syndrome in patients using antipsychotics. In this study, we set out to replicate our findings in a third separate sample of pat...
An interactive effect of batch size and composition contributes to discordant results in GWAS with the CHIAMO genotyping algorithm [0.03%]
批次大小和组成互作效应导致CHIAMO基因分型算法在GWAS中产生不一致结果
M Chierici,K Miclaus,S Vega et al.
M Chierici et al.
The discordance in results between independent genome-wide association studies (GWAS) indicates the potential for Type I and Type II errors. To identify the causes of variability underlying lack of reproducibility, here we present the resul...
Assessment of variability in GWAS with CRLMM genotyping algorithm on WTCCC coronary artery disease [0.03%]
冠心病WTCCC联盟的基因组范围关联研究中CRLMM算法分型结果的可重复性评估
L Zhang,S Yin,K Miclaus et al.
L Zhang et al.
The robustness of genome-wide association study (GWAS) results depends on the genotyping algorithms used to establish the association. This paper initiated the assessment of the impact of the Corrected Robust Linear Model with Maximum Likel...
Batch effects in the BRLMM genotype calling algorithm influence GWAS results for the Affymetrix 500K array [0.03%]
基因型呼叫算法中的批量效应影响AFFYMETRIX 500K芯片的GWAS结果
K Miclaus,R Wolfinger,S Vega et al.
K Miclaus et al.
The Affymetrix GeneChip Human Mapping 500K array is common for genome-wide association studies (GWASs). Recent findings highlight the importance of accurate genotype calling algorithms to reduce the inflation in Type I and Type II error rat...
Variability in GWAS analysis: the impact of genotype calling algorithm inconsistencies [0.03%]
基因分型算法不一致性对全基因组关联研究分析结果可变性的影响
K Miclaus,M Chierici,C Lambert et al.
K Miclaus et al.
The Genome-Wide Association Working Group (GWAWG) is part of a large-scale effort by the MicroArray Quality Consortium (MAQC) to assess the quality of genomic experiments, technologies and analyses for genome-wide association studies (GWASs...
Functional analysis of multiple genomic signatures demonstrates that classification algorithms choose phenotype-related genes [0.03%]
功能分析发现多个基因组标志物表明分类算法选择与表型相关的基因
W Shi,M Bessarabova,D Dosymbekov et al.
W Shi et al.
Gene expression signatures of toxicity and clinical response benefit both safety assessment and clinical practice; however, difficulties in connecting signature genes with the predicted end points have limited their application. The Microar...
k-Nearest neighbor models for microarray gene expression analysis and clinical outcome prediction [0.03%]
基于微阵列基因表达分析和临床结果预测的K最近邻模型
R M Parry,W Jones,T H Stokes et al.
R M Parry et al.
In the clinical application of genomic data analysis and modeling, a number of factors contribute to the performance of disease classification and clinical outcome prediction. This study focuses on the k-nearest neighbor (KNN) modeling stra...
Comparative Study
The pharmacogenomics journal. 2010 Aug;10(4):292-309. DOI:10.1038/tpj.2010.56 2010
A comparison of batch effect removal methods for enhancement of prediction performance using MAQC-II microarray gene expression data [0.03%]
基于MAQC-II微阵列基因表达数据改进预测性能的批次效应去除方法比较研究
J Luo,M Schumacher,A Scherer et al.
J Luo et al.
Batch effects are the systematic non-biological differences between batches (groups) of samples in microarray experiments due to various causes such as differences in sample preparation and hybridization protocols. Previous work focused mai...
Comparative Study
The pharmacogenomics journal. 2010 Aug;10(4):278-91. DOI:10.1038/tpj.2010.57 2010
J Huang,W Shi,J Zhang et al.
J Huang et al.
Genomic biomarkers for the detection of drug-induced liver injury (DILI) from blood are urgently needed for monitoring drug safety. We used a unique data set as part of the Food and Drug Administration led MicroArray Quality Control Phase-I...
Comparison of performance of one-color and two-color gene-expression analyses in predicting clinical endpoints of neuroblastoma patients [0.03%]
单通道和双通道基因表达分析预测神经母细胞瘤患者临床结果的比较性能分析
A Oberthuer,D Juraeva,L Li et al.
A Oberthuer et al.
Microarray-based prediction of clinical endpoints may be performed using either a one-color approach reflecting mRNA abundance in absolute intensity values or a two-color approach yielding ratios of fluorescent intensities. In this study, a...
Comparative Study
The pharmacogenomics journal. 2010 Aug;10(4):258-66. DOI:10.1038/tpj.2010.53 2010