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001 978-1-4614-9443-0
003 DE-He213
005 20140220082505.0
007 cr nn 008mamaa
008 131123s2014 xxu| s |||| 0|eng d
020 _a9781461494430
_9978-1-4614-9443-0
024 7 _a10.1007/978-1-4614-9443-0
_2doi
050 4 _aQA276-280
072 7 _aPBT
_2bicssc
072 7 _aMBNS
_2bicssc
072 7 _aMED090000
_2bisacsh
082 0 4 _a519.5
_223
100 1 _aStram, Daniel O.
_eauthor.
245 1 0 _aDesign, Analysis, and Interpretation of Genome-Wide Association Scans
_h[electronic resource] /
_cby Daniel O. Stram.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2014.
300 _aXV, 334 p. 39 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStatistics for Biology and Health,
_x1431-8776
505 0 _aIntroduction to Genome-Wide Association Studies -- Topics of Quantitative Genetics -- An Introduction to Association Studies -- Correcting for Hidden Population Structure in Single Marker Association Testing and Estimation -- Haplotype Imputation for Association Analysis -- SNP Imputation for Association Studies -- Design of Large-scale Genetic Association Studies, Sample Size and Power -- Post-GWAS Analyses.
520 _aThis book presents the statistical aspects of designing, analyzing and interpreting the results of genome-wide association scans (GWAS studies) for genetic causes of disease using unrelated subjects. Particular detail is given to the practical aspects of employing the bioinformatics and data handling methods necessary to prepare data for statistical analysis. The goal in writing this book is to give statisticians, epidemiologists, and students in these fields the tools to design a powerful genome-wide study based on current technology. The other part of this is showing readers how to conduct analysis of the created study. Design and Analysis of Genome-Wide Association Studies provides a compendium of well-established statistical methods based upon single SNP associations. It also provides an introduction to more advanced statistical methods and issues. Knowing that technology, for instance large scale SNP arrays, is quickly changing, this text has significant lessons for future use with sequencing data. Emphasis on statistical concepts that apply to the problem of finding disease associations irrespective of the technology ensures its future applications. The author includes current bioinformatics tools while outlining the tools that will be required for use with extensive databases from future large scale sequencing projects. The author includes current bioinformatics tools while outlining additional issues and needs arising from the extensive databases from future large scale sequencing projects.
650 0 _aStatistics.
650 0 _aHuman genetics.
650 0 _aMathematical statistics.
650 1 4 _aStatistics.
650 2 4 _aStatistics for Life Sciences, Medicine, Health Sciences.
650 2 4 _aHuman Genetics.
650 2 4 _aStatistical Theory and Methods.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781461494423
830 0 _aStatistics for Biology and Health,
_x1431-8776
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4614-9443-0
912 _aZDB-2-SMA
999 _c92378
_d92378