Kathleen F Kerr

Summary

Affiliation: University of Washington
Country: USA

Publications

  1. ncbi request reprint What is the best reference RNA? And other questions regarding the design and analysis of two-color microarray experiments
    Kathleen F Kerr
    Department of Biostatistics, University of Washington, Seattle, Washington 98195, USA
    OMICS 11:152-65. 2007
  2. pmc Genetics of coronary artery calcification among African Americans, a meta-analysis
    Mary K Wojczynski
    Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO, USA
    BMC Med Genet 14:75. 2013
  3. pmc Further insight into the incremental value of new markers: the interpretation of performance measures and the importance of clinical context
    Kathleen F Kerr
    Department of Biostatistics, University of Washington, Seattle, USA
    Am J Epidemiol 176:482-7. 2012
  4. pmc Evaluation of methods for oligonucleotide array data via quantitative real-time PCR
    Li Xuan Qin
    Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
    BMC Bioinformatics 7:23. 2006
  5. pmc Evaluating the incremental value of new biomarkers with integrated discrimination improvement
    Kathleen F Kerr
    Department of Biostatistics, School of Public Health, University of Washington, Seattle, USA
    Am J Epidemiol 174:364-74. 2011
  6. pmc Comments on the analysis of unbalanced microarray data
    Kathleen F Kerr
    Department of Biostatistics, Box 357232, University of Washington, Seattle, WA 98195, USA
    Bioinformatics 25:2035-41. 2009
  7. ncbi request reprint Design considerations for efficient and effective microarray studies
    M Kathleen Kerr
    Department of Biostatistics, University of Washington, Box 357232, Seattle, Washington, USA
    Biometrics 59:822-8. 2003
  8. pmc Extended analysis of benchmark datasets for Agilent two-color microarrays
    Kathleen F Kerr
    Department of Biostatistics, University of Washington, Seattle, Washington, USA
    BMC Bioinformatics 8:371. 2007
  9. ncbi request reprint Linear models for microarray data analysis: hidden similarities and differences
    M Kathleen Kerr
    Department of Biostatistics, University of Washington, Seattle, Washington 98195, USA
    J Comput Biol 10:891-901. 2003
  10. pmc Joint modeling, covariate adjustment, and interaction: contrasting notions in risk prediction models and risk prediction performance
    Kathleen F Kerr
    Department of Biostatistics and Fred Hutchinson Cancer Research Center, University of Washington, Seattle, WA 98195, USA
    Epidemiology 22:805-12. 2011

Collaborators

Detail Information

Publications18

  1. ncbi request reprint What is the best reference RNA? And other questions regarding the design and analysis of two-color microarray experiments
    Kathleen F Kerr
    Department of Biostatistics, University of Washington, Seattle, Washington 98195, USA
    OMICS 11:152-65. 2007
    ..Finally, we evaluate the sensitivity and specificity of data quality filters, and we propose a new filter that can be applied to any experimental design and does not rely on replicate hybridizations...
  2. pmc Genetics of coronary artery calcification among African Americans, a meta-analysis
    Mary K Wojczynski
    Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO, USA
    BMC Med Genet 14:75. 2013
    ..African Americans (AA) have higher rates of CHD but are less well-studied in genomic studies. We assembled the largest AA data resource currently available with measured CAC to identify associated genetic variants...
  3. pmc Further insight into the incremental value of new markers: the interpretation of performance measures and the importance of clinical context
    Kathleen F Kerr
    Department of Biostatistics, University of Washington, Seattle, USA
    Am J Epidemiol 176:482-7. 2012
    ..If they did, researchers could use the measures directly and benchmarks would not be needed...
  4. pmc Evaluation of methods for oligonucleotide array data via quantitative real-time PCR
    Li Xuan Qin
    Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
    BMC Bioinformatics 7:23. 2006
    ..An advantage of our approach over spike-in studies is that methods are validated on a real dataset that was collected to address a scientific question...
  5. pmc Evaluating the incremental value of new biomarkers with integrated discrimination improvement
    Kathleen F Kerr
    Department of Biostatistics, School of Public Health, University of Washington, Seattle, USA
    Am J Epidemiol 174:364-74. 2011
    ..For investigators who find the IDI to be a useful measure, bootstrap methods may offer a reasonable option for inference when evaluating new predictors, as long as the added predictive capacity is large...
  6. pmc Comments on the analysis of unbalanced microarray data
    Kathleen F Kerr
    Department of Biostatistics, Box 357232, University of Washington, Seattle, WA 98195, USA
    Bioinformatics 25:2035-41. 2009
    ..However, combining these approaches may be problematic when sample sizes are unequal...
  7. ncbi request reprint Design considerations for efficient and effective microarray studies
    M Kathleen Kerr
    Department of Biostatistics, University of Washington, Box 357232, Seattle, Washington, USA
    Biometrics 59:822-8. 2003
    ..Specifically, this article 1) discusses the basic principles of design (randomization, replication, and blocking) as they pertain to microarrays, and 2) provides some general guidelines for statisticians designing microarray studies...
  8. pmc Extended analysis of benchmark datasets for Agilent two-color microarrays
    Kathleen F Kerr
    Department of Biostatistics, University of Washington, Seattle, Washington, USA
    BMC Bioinformatics 8:371. 2007
    ..It is also important to consider whether ERCs are representative of all the probes on a microarray...
  9. ncbi request reprint Linear models for microarray data analysis: hidden similarities and differences
    M Kathleen Kerr
    Department of Biostatistics, University of Washington, Seattle, Washington 98195, USA
    J Comput Biol 10:891-901. 2003
    ..This paper demonstrates the equivalence of some of these models. Attention is directed at choices in microarray data analysis that have a larger impact on the results than the choice of linear model...
  10. pmc Joint modeling, covariate adjustment, and interaction: contrasting notions in risk prediction models and risk prediction performance
    Kathleen F Kerr
    Department of Biostatistics and Fred Hutchinson Cancer Research Center, University of Washington, Seattle, WA 98195, USA
    Epidemiology 22:805-12. 2011
    ..We conclude with a discussion of the most appropriate methods for evaluating new biomarkers in the presence of existing predictors...
  11. doi request reprint Comparative transcriptome analysis of Agrobacterium tumefaciens in response to plant signal salicylic acid, indole-3-acetic acid and gamma-amino butyric acid reveals signalling cross-talk and Agrobacterium--plant co-evolution
    Ze Chun Yuan
    Department of Microbiology, University of Washington, Seattle, WA 98195, USA
    Cell Microbiol 10:2339-54. 2008
    ..The complex signalling interplay between Agrobacterium and its plant hosts reflects an exquisite co-evolutionary balance...
  12. doi request reprint Optimality criteria for the design of 2-color microarray studies
    Kathleen F Kerr
    University of Washington, USA
    Stat Appl Genet Mol Biol 11:Article 10. 2012
    ..We further disfavor E- and D-optimality (as defined in block design) because they are not attuned to scientific questions of interest...
  13. pmc Harborview burns--1974 to 2009
    Loren H Engrav
    Division of Plastic Surgery, Department of Surgery, University of Washington, Seattle, Washington, United States of America
    PLoS ONE 7:e40086. 2012
    ....
  14. ncbi request reprint The Arabidopsis thaliana transcriptome in response to Agrobacterium tumefaciens
    Renata F Ditt
    Department of Biology, University of Washington, Seattle 98195, USA
    Mol Plant Microbe Interact 19:665-81. 2006
    ..The regulated gene sets should be useful in dissecting the signaling pathways in this plant-pathogen interaction...
  15. pmc Functional genomics unique to week 20 post wounding in the deep cone/fat dome of the Duroc/Yorkshire porcine model of fibroproliferative scarring
    Loren H Engrav
    Department of Surgery, Division of Plastic Surgery, University of Washington, Seattle, Washington, United States of America
    PLoS ONE 6:e19024. 2011
    ....
  16. pmc Empirical evaluation of data transformations and ranking statistics for microarray analysis
    Li Xuan Qin
    Department of Biostatistics, University of Washington, F 600 Health Sciences Building 1705 NE Pacific Street, Box 357232, Seattle, WA 98195, USA
    Nucleic Acids Res 32:5471-9. 2004
    ..Finally, we find that choice of image analysis software can also substantially influence experimental conclusions...
  17. ncbi request reprint Multicenter study of acetaminophen hepatotoxicity reveals the importance of biological endpoints in genomic analyses
    Richard P Beyer
    University of Washington, and Fred Hutchinson Cancer Research Center, Seattle, Washington 98195, USA
    Toxicol Sci 99:326-37. 2007
    ..We show that phenotypic anchoring of gene expression data is required for biologically meaningful analysis of toxicogenomic experiments...
  18. ncbi request reprint Standardizing global gene expression analysis between laboratories and across platforms
    Theodore Bammler
    Nat Methods 2:351-6. 2005
    ..These findings indicate that microarray results can be comparable across multiple laboratories, especially when a common platform and set of procedures are used...