000 05283nam a22003855i 4500
001 279871
003 MX-SnUAN
005 20160429154001.0
007 cr nn 008mamaa
008 150903s2007 xxu| o |||| 0|eng d
020 _a9780387493176
_99780387493176
024 7 _a10.1007/9780387493176
_2doi
035 _avtls000331631
039 9 _a201509030733
_bVLOAD
_c201404121916
_dVLOAD
_c201404091644
_dVLOAD
_c201401311422
_dstaff
_y201401301214
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aQH324.2-324.25
100 1 _aDudoit, Sandrine.
_eautor
_9299892
245 1 0 _aMultiple Testing Procedures with Applications to Genomics /
_cby Sandrine Dudoit, Mark J. Laan.
264 1 _aNew York, NY :
_bSpringer New York,
_c2007.
300 _axxxiii, 590 páginas,
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
490 0 _aSpringer Series in Statistics,
_x0172-7397
500 _aSpringer eBooks
505 0 _aMultiple Hypothesis Testing -- Test Statistics Null Distribution -- Overview of Multiple Testing Procedures -- Single-Step Multiple Testing Procedures for Controlling General Type I Error Rates, ?(Fvn) -- Step-Down Multiple Testing Procedures for Controlling the Family-Wise Error Rate -- Augmentation Multiple Testing Procedures for Controlling Generalized Tail Probability Error Rates -- Resampling-Based Empirical Bayes multiple Testing Procedures for Controlling Generalized Tail Probability Error Rates -- Simulation Studies: Assessment of Test Statistics Null Distributions -- Identification of Differentially Expressed and Co-Expressed Genes in High-Throughput Gene Expression Experiments -- Multiple Tests of Association with Biological Annotation Metadata -- HIV-1 Sequence Variation and Viral Replication Capacity -- Genetic Mapping of Complex Human Traits Using Single Nucleotide Polymorphisms: The ObeLinks Project -- Software Implementation.
520 _aThis book establishes the theoretical foundations of a general methodology for multiple hypothesis testing and discusses its software implementation in R and SAS. The methods are applied to a range of testing problems in biomedical and genomic research, including the identification of differentially expressed and co-expressed genes in high-throughput gene expression experiments, such as microarray experiments; tests of association between gene expression measures and biological annotation metadata (e.g., Gene Ontology); sequence analysis; and the genetic mapping of complex traits using single nucleotide polymorphisms. The book is aimed at both statisticians interested in multiple testing theory and applied scientists encountering high-dimensional testing problems in their subject matter area. Specifically, the book proposes resampling-based single-step and stepwise multiple testing procedures for controlling a broad class of Type I error rates, defined as tail probabilities and expected values for arbitrary functions of the numbers of Type I errors and rejected hypotheses (e.g., false discovery rate). Unlike existing approaches, the procedures are based on a test statistics joint null distribution and provide Type I error control in testing problems involving general data generating distributions (with arbitrary dependence structures among variables), null hypotheses, and test statistics. The multiple testing results are reported in terms of rejection regions, parameter confidence regions, and adjusted p-values. Sandrine Dudoit is Associate Professor of Biostatistics and Statistics at the University of California, Berkeley (www.stat.berkeley.edu/~sandrine). Her research and teaching activities concern the development and application of statistical and computational methods for the analysis of high-dimensional biomedical and genomic data. She is a founding core developer of the Bioconductor Project and is an Associate Editor for six journals, including the Annals of Applied Statistics and Statistical Applications in Genetics and Molecular Biology. Mark J. van der Laan is Hsu/Peace Professor of Biostatistics and Statistics at the University of California, Berkeley (www.stat.berkeley.edu/~laan). His research concerns causal inference, adjusting for missing and censored data, and simultaneous estimation and testing based on high-dimensional observational and experimental biomedical and genomic data. He is co-author with James Robins of Unified Methods for Censored Longitudinal Data and Causality (Springer, 2003). He is a recipient of the 2005 COPSS Presidents' and Snedecor Awards and is an active Associate Editor for five journals, including the Annals of Statistics and the International Journal of Biostatistics.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700 1 _aLaan, Mark J.
_eautor
_9304434
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9780387493169
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-0-387-49317-6
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942 _c14
999 _c279871
_d279871