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020 _a9781071601990
_9978-1-0716-0199-0
024 7 _a10.1007/978-1-0716-0199-0
_2doi
050 4 _aQH324.2-324.25
072 7 _aUY
_2bicssc
072 7 _aPS
_2bicssc
072 7 _aCOM082000
_2bisacsh
072 7 _aPSAX
_2thema
082 0 4 _a570.285
_223
245 1 0 _aStatistical Population Genomics
_h[electronic resource] /
_cedited by Julien Y. Dutheil.
250 _a1st ed. 2020.
264 1 _aNew York, NY :
_bSpringer US :
_bImprint: Humana,
_c2020.
300 _aXII, 468 p. 203 illus., 98 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aMethods in Molecular Biology,
_x1940-6029 ;
_v2090
505 0 _aA Population Genomics Lexicon -- Processing and Analyzing Multiple Genomes Alignments with MafFilter -- Data Management and Summary Statistics with PLINK -- Exploring Population Structure with Admixture Models and Principal Components Analysis -- Detecting Positive Selection in Populations using Genetic Data -- polyDFE: Inferring the Distribution of Fitness Effects and Properties of Beneficial Mutations from Polymorphism Data -- MSMC and MSMC2: The Multiple Sequentially Markovian Coalescent.-Ancestral Population Genomics with Jocx, A Coalescent Hidden Markov Model -- Coalescent Simulation with sprime -- Inference of Ancestral Recombination Graphs using ARGweaver -- Population Genomics of Transitions to Selfing in Brassicaceae Model Systems -- Genomics of Long- and Short- Term Adaptation in Maize and Teosinte -- Neurospora from Natural Populations: Population Genomics Insights Into the Life History of a Model Microbial Eukaryote -- Population Genomics of Fungal Plant Pathogens and the Analyses of Rapidly Evolving Genome Compartments -- Population Genomics on the Fly: Recent Advances in Drosophila -- Genomic Access to the Diversity of Fishes -- Avian Population Genomics Taking Off: Latest Findings and Future Prospects -- Population Genomics of the House Mouse and the Brown Rat -- Population Genomics in the Great Apes.
506 0 _aOpen Access
520 _aThis open access volume presents state-of-the-art inference methods in population genomics, focusing on data analysis based on rigorous statistical techniques. After introducing general concepts related to the biology of genomes and their evolution, the book covers state-of-the-art methods for the analysis of genomes in populations, including demography inference, population structure analysis and detection of selection, using both model-based inference and simulation procedures. Last but not least, it offers an overview of the current knowledge acquired by applying such methods to a large variety of eukaryotic organisms. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, pointers to the relevant literature, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Statistical Population Genomics aims to promote and ensure successful applications of population genomic methods to an increasing number of model systems and biological questions.
650 0 _aBioinformatics.
650 0 _aGenetics.
650 1 4 _aBioinformatics.
650 2 4 _aGenetics and Genomics.
700 1 _aDutheil, Julien Y.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9781071601983
776 0 8 _iPrinted edition:
_z9781071602003
776 0 8 _iPrinted edition:
_z9781071602010
830 0 _aMethods in Molecular Biology,
_x1940-6029 ;
_v2090
856 4 0 _uhttps://doi.org/10.1007/978-1-0716-0199-0
912 _aZDB-2-PRO
912 _aZDB-2-SOB
999 _c80339
_d80339
945 _a1
_bMadushi Gamage
_c1
_dMadushi Gamage