@article {1077,
	title = {A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium.},
	journal = {Nature biotechnology},
	volume = {32},
	year = {2014},
	month = {2014 Aug 24},
	pages = {903{\textendash}914},
	abstract = {We present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the US Food and Drug Administration. Examining Illumina HiSeq, Life Technologies SOLiD and Roche 454 platforms at multiple laboratory sites using reference RNA samples with built-in controls, we assess RNA sequencing (RNA-seq) performance for junction discovery and differential expression profiling and compare it to microarray and quantitative PCR (qPCR) data using complementary metrics. At all sequencing depths, we discover unannotated exon-exon junctions, with >80\% validated by qPCR. We find that measurements of relative expression are accurate and reproducible across sites and platforms if specific filters are used. In contrast, RNA-seq and microarrays do not provide accurate absolute measurements, and gene-specific biases are observed for all examined platforms, including qPCR. Measurement performance depends on the platform and data analysis pipeline, and variation is large for transcript-level profiling. The complete SEQC data sets, comprising >100 billion reads (10Tb), provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings.},
	keywords = {NGS, RNA-seq, SEQC},
	issn = {1546-1696},
	doi = {10.1038/nbt.2957},
	url = {http://www.nature.com/nbt/journal/vaop/ncurrent/full/nbt.2957.html},
	author = {Su, Z. and Labaj, P.P. and .... and Dopazo, J. and .... and Mason, C.E. and Shi, L}
}
@article {542,
	title = {Functional analysis of multiple genomic signatures demonstrates that classification algorithms choose phenotype-related genes.},
	journal = {Pharmacogenomics J},
	volume = {10},
	year = {2010},
	month = {2010 Aug},
	pages = {310-23},
	abstract = {<p>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 Microarray Quality Control Consortium II (MAQCII) project generated 262 signatures for ten clinical and three toxicological end points from six gene expression data sets, an unprecedented collection of diverse signatures that has permitted a wide-ranging analysis on the nature of such predictive models. A comprehensive analysis of the genes of these signatures and their nonredundant unions using ontology enrichment, biological network building and interactome connectivity analyses demonstrated the link between gene signatures and the biological basis of their predictive power. Different signatures for a given end point were more similar at the level of biological properties and transcriptional control than at the gene level. Signatures tended to be enriched in function and pathway in an end point and model-specific manner, and showed a topological bias for incoming interactions. Importantly, the level of biological similarity between different signatures for a given end point correlated positively with the accuracy of the signature predictions. These findings will aid the understanding, and application of predictive genomic signatures, and support their broader application in predictive medicine.</p>},
	keywords = {Algorithms, Databases, Genetic, Endpoint Determination, Gene Expression Profiling, Genomics, Humans, Neural Networks, Computer, Oligonucleotide Array Sequence Analysis, Phenotype, Predictive Value of Tests, Proteins, Quality Control},
	issn = {1473-1150},
	doi = {10.1038/tpj.2010.35},
	author = {Shi, W and Bessarabova, M and Dosymbekov, D and Dezso, Z and Nikolskaya, T and Dudoladova, M and Serebryiskaya, T and Bugrim, A and Guryanov, A and Brennan, R J and Shah, R and Dopazo, J and Chen, M and Deng, Y and Shi, T and Jurman, G and Furlanello, C and Thomas, R S and Corton, J C and Tong, W and Shi, L and Nikolsky, Y}
}
