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Pierre R. Bushel

Researcher at National Institutes of Health

Publications -  131
Citations -  9825

Pierre R. Bushel is an academic researcher from National Institutes of Health. The author has contributed to research in topics: Gene & Gene expression. The author has an hindex of 46, co-authored 125 publications receiving 8980 citations. Previous affiliations of Pierre R. Bushel include North Carolina State University & Research Triangle Park.

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Assessing Gene Significance from cDNA Microarray Expression Data via Mixed Models

TL;DR: A statistical approach is presented that allows direct control over the percentage of false positives in such a list of differentially expressed genes and, under certain reasonable assumptions, improves on existing methods with respect to the percentages of false negatives.
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A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium

Zhenqiang Su, +164 more
- 01 Sep 2014 - 
TL;DR: The complete SEQC data sets, comprising >100 billion reads, provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings, and measurement performance depends on the platform and data analysis pipeline, and variation is large for transcript-level profiling.
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The Microarray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

Leming Shi, +201 more
- 01 Aug 2010 - 
TL;DR: P predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans are generated.
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Standardizing global gene expression analysis between laboratories and across platforms

TL;DR: In this paper, the authors proposed a method for standardizing global gene expression analysis between laboratories and across platforms, which can be found in Section 5.2.1.1].
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The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance

TL;DR: RNA-seq outperforms microarray in DEG verification as assessed by quantitative PCR, with the gain mainly due to its improved accuracy for low-abundance transcripts, and classifiers to predict MOAs perform similarly when developed using data from either platform.