Robert B Scharpf
Affiliation: Johns Hopkins Bloomberg School of Public Health
- Cross-platform Comparison of Two Pancreatic Cancer PhenotypesRobert B Scharpf
Departments of Oncology
Cancer Inform 9:257-64. 2010..Using this approach, we identify several transcripts from the integrative analysis whose over-or under-expression in pancreatic cancer cell lines was validated by qPCR...
- A multilevel model to address batch effects in copy number estimation using SNP arraysRobert B Scharpf
Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
Biostatistics 12:33-50. 2011..The software is open source and implemented in the R package crlmm at Bioconductor (http:www.bioconductor.org)...
- When should one subtract background fluorescence in 2-color microarrays?Robert B Scharpf
Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
Biostatistics 8:695-707. 2007..Using these results, we develop recommendations for diagnostic visualizations that can help decisions about background subtraction...
- A genome-wide study of de novo deletions identifies a candidate locus for non-syndromic isolated cleft lip/palate riskSamuel G Younkin
Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore MD, USA
BMC Genet 15:24. 2014..We compare de novo deletion frequencies in children of European ancestry with an isolated, non-syndromic oral cleft to frequencies in children of European ancestry from randomly sampled trios...
- Pre-processing Agilent microarray dataMarianna Zahurak
Johns Hopkins University School of Medicine, Oncology Biostatistics, Baltimore, MD 21205, USA
BMC Bioinformatics 8:142. 2007..The larger goal is to define best study design and pre-processing practices for Agilent arrays, and we offer some suggestions...
- Fast detection of de novo copy number variants from SNP arrays for case-parent triosRobert B Scharpf
Department of Oncology, Johns Hopkins University, Baltimore, MD, USA
BMC Bioinformatics 13:330. 2012..We evaluate these issues in a study of oral cleft case-parent trios...
- R classes and methods for SNP array dataRobert B Scharpf
Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
Methods Mol Biol 593:67-79. 2010..This chapter highlights the advantages of adopting and extending Biobase class definitions through a working example of one implementation of classes for the analysis of high-throughput SNP arrays...
- Tackling the widespread and critical impact of batch effects in high-throughput dataJeffrey T Leek
Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205 2179, USA
Nat Rev Genet 11:733-9. 2010..We review experimental and computational approaches for doing so...
- SNPchip: R classes and methods for SNP array dataRobert B Scharpf
Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
Bioinformatics 23:627-8. 2007..bioconductor.org. SUPPLEMENTARY INFORMATION: The supplementary material as described in this article (case studies, installation guidelines and R code) is available from http://biostat.jhsph.edu/~iruczins/publications/sm/..
- Utility of whole blood hemostatometry using the clot signature analyzer for assessment of hemostasis in cardiac surgeryNauder Faraday
Department of Anesthesiology, Johns Hopkins Medical Institutions, Baltimore, Maryland 21287, USA
Anesthesiology 96:1115-22. 2002..The Clot Signature Analyzer is a hemostatometer that measures global hemostasis in whole blood. The authors hypothesized that point-of-care hemostatometry could detect a clinical coagulopathic state in cardiac surgical patients...