Welcome to the Nature Biotechnology and The Pharmacogenomics Journal joint Web Focus on MAQC II papers.

This Web Focus contains articles on best practices for developing and validating predictive models based on data from gene expression and genotyping microarrays. These report the second phase of a collaboration between industry, academic and US government researchers as part of the MicroArray Quality Control (MAQC) consortium.


Editorial

Of genomics and bioinformatics

W Slikker Jr

doi:10.1038/tpj.2010.59

The Pharmacogenomics Journal 10, 245-246 (2010)

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News & Views

Microarrays in the clinic

Guy W Tillinghast

doi:10.1038/nbt0810-810

Nature Biotechnology 28, 810-812 (2010)

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Original Articles

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

MAQC Consortium

doi:10.1038/nbt.1665

Nature Biotechnology 28, 827-838 (2010)

Consistency of predictive signature genes and classifiers generated using different microarray platforms

X Fan, E K Lobenhofer M Chen, W Shi, J Huang, J Luo, J Zhang, S J Walker, T-M Chu, L Li, R Wolfinger, W Bao, R S Paules, P R Bushe, J Li, T Shi, T Nikolskaya, Y Nikolsky, H Hong, Y Deng1, Y Cheng, H Fang, L Shi and W Tong

doi:10.1038/tpj.2010.34

The Pharmacogenomics Journal 10, 247-257 (2010)

Comparison of performance of one-color and two-color gene-expression analyses in predicting clinical endpoints of neuroblastoma patients

A Oberthuer, D Juraeva, L Li, Y Kahlert, F Westermann, R Eils, F Berthold, L Shi, R D Wolfinger, M Fischer and B Brors

doi:10.1038/tpj.2010.53

The Pharmacogenomics Journal 10, 258-266 (2010)

Genomic indicators in the blood predict drug-induced liver injury

J Huang, W Shi, J Zhang, J W Chou, R S Paules, K Gerrish, J Li, J Luo, R D Wolfinger, W Bao, T-M Chu, Y Nikolsky, T Nikolskaya, D Dosymbekov, M O Tsyganova, L Shi, X Fan, J C Corton, M Chen, Y Cheng, W Tong, H Fang and P R Bushel

doi:10.1038/tpj.2010.33

The Pharmacogenomics Journal 10, 267-277 (2010)

A comparison of batch effect removal methods for enhancement of prediction performance using MAQC-II microarray gene expression data

J Luo, M Schumacher, A Scherer, D Sanoudou, D Megherbi, T Davison, T Shi, W Tong, L Shi, H Hong, C Zhao, F Elloumi, W Shi, R Thomas, S Lin, G Tillinghast, G Liu, Y Zhou, D Herman, Y Li, Y Deng, H Fang, P Bushel, M Woods and J Zhang

doi:10.1038/tpj.2010.57

The Pharmacogenomics Journal 10, 278-291 (2010)

k-Nearest neighbor models for microarray gene expression analysis and clinical outcome prediction

R M Parry, W Jones, T H Stokes, J H Phan, R A Moffitt, H Fang, L Shi, A Oberthuer, M Fischer, W Tong and M D Wang

doi:10.1038/tpj.2010.56

The Pharmacogenomics Journal 10, 292-309 (2010)

Functional analysis of multiple genomic signatures demonstrates that classification algorithms choose phenotype-related genes

W Shi, M Bessarabova, D Dosymbekov, Z Dezso, T Nikolskaya, M Dudoladova, T Serebryiskaya, A Bugrim, A Guryanov, R J Brennan, R Shah, J Dopazo, M Chen, Y Deng, T Shi, G Jurman, C Furlanello, R S Thomas, J C Corton, W Tong, L Shi and Y Nikolsky

doi:10.1038/tpj.2010.35

The Pharmacogenomics Journal 10, 310-323 (2010)

Variability in GWAS analysis: the impact of genotype calling algorithm inconsistencies

K Miclaus, M Chierici, C Lambert, L Zhang, S Vega, H Hong, S Yin, C Furlanello, R Wolfinger and F Goodsaid

doi:10.1038/tpj.2010.46

The Pharmacogenomics Journal 10, 324-335 (2010)

Batch effects in the BRLMM genotype calling algorithm influence GWAS results for the Affymetrix 500K array

K Miclaus, R Wolfinger, S Vega, M Chierici, C Furlanello, C Lambert, H Hong, Li Zhang, S Yin and F Goodsaid

doi:10.1038/tpj.2010.36

The Pharmacogenomics Journal 10, 336-346 (2010)

Assessment of variability in GWAS with CRLMM genotyping algorithm on WTCCC coronary artery disease

L Zhang, S Yin, K Miclaus, M Chierici, S Vega, C Lambert, H Hong, R D Wolfinger, C Furlanello and F Goodsaid

doi:10.1038/tpj.2010.27

The Pharmacogenomics Journal 10, 347-354 (2010)

An interactive effect of batch size and composition contributes to discordant results in GWAS with the CHIAMO genotyping algorithm

M Chierici, K Miclaus, S Vega and C Furlanello

doi:10.1038/tpj.2010.47

The Pharmacogenomics Journal 10, 355-363 (2010)

Assessing sources of inconsistencies in genotypes and their effects on genome-wide association studies with HapMap samples

H Hong, L Shi, Z Su, W Ge, W D Jones, W Czika, K Miclaus, C G Lambert, S C Vega, J Zhang, B Ning, J Liu, B Green, L Xu, H Fang, R Perkins, S M Lin, N Jafari, K Park, T Ahn, M Chierici, C Furlanello, L Zhang, R D Wolfinger, F Goodsaid and W Tong

doi:10.1038/tpj.2010.24

The Pharmacogenomics Journal 10, 364-374 (2010)

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