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Life
NESCENT: EDUCATION & OUTREACH: MINORITY SERVING Minority Serving Institutions and Other Institutions with Significant Minority Enrollment. Click on the header of any column to change the listing order. If you would like to add or change information in the chart, please contact eog@nescent.org . Institution. City. POPULATION GENETICS IN R Publication. An overview of and a detailed rationale for the building blocks of this resource and how they click together are described in our publication for the Molecular Ecology Resources special issue, Population Genomics with R: Kamvar, Z. N., López-Uribe, M. M., Coughlan, S., Grünwald, N. J., Lapp, H., & Manel, S. (2016).Developing
NESCENT: EDUCATION & OUTREACH: ARCHIVED NEWS NESCent Catalysis Meeting. Drs. Anne Yoder and Claire Kremen, Coordinators. June 13-17, 2006. In 2003, the President of Madagascar, Marc Ravalomanana, announced plans to increase protected lands in Madagascar to 10% of the country. This would be remarkable under any circumstances but becomes even more important in light of the factthat
CALCULATING BASIC POPULATION GENETIC STATISTICS FROM SNP DATA Import data. The data are stored in a text file (genotype=AA..). We will import the dataset into R as a data frame, and then convert the SNP data file into a “genind” object. The dataset “Master_Pinus_data_genotype.txt” can be downloaded here.. The textfile is
POPULATION DIFFERENTIATION FOR SEQUENCE DATA Introduction. Now, we will discuss in more detail how to assess population genetic structure from sequence data. Assuming that you have a priori information about how the individuals are grouped in subpopulations, one can do the following analyses: 1) quantify pairwise subpopulation structure and their significance, 2) test for hierarchical structure among groups of subpopulations, and 3) use NEXUS: AN EXTENSIBLE FILE FORMAT FOR SYSTEMATIC … 3 A BSTRACT.— NEXUS is a file format designed to contain systematic data for use by com-puter programs. The goals of the format are to allow future expansion, to include diverse kinds of CALCULATING BASIC POPULATION GENETIC STATISTICS FROM Section 3: Basic statistics with hierfstat. The function basic.stats () provides the observed heterozygosity ( H o ), mean gene diversities within population ( H s ), F i s, and F s t. The function boot.ppfis () provides confidence interval for F i s. The function indpca () does a PCA on the centered matrix of individuals’ allele frequencies. INDIVIDUAL BASED GENETIC DISTANCE FOR SNP DATA Section 3. Individual genetic distance: number of loci for which individuals differ (dist.gene {ape})The option pairwise.deletion = FALSE in the command dist.gene() removes all loci with one missing values : you an see on the histogram that we get a maximum distance of 3 loci out of 100.. We can see that we get 98 loci with at least onesample missing.
DETECTION OF THE SIGNAL OF SELECTION FROM GENOME SCAN Section 2: PCAdapt To run the function pcadapt(), the user should specify the number K of principal components (PC) to work with: first perform with a large number of principal components (e.g. higher than the number of populations), then use the ‘scree plot’ to chose the value of K.It displays the percentage of variance that is explained byeach PC.
NESCENT: THE NATIONAL EVOLUTIONARY SYNTHESIS CENTERABOUTPEOPLENEWSCONTACT Short-term Sabbatical Scholar Douglas Soltis (University of Florida), Pamela Soltis (University of Florida) Reconstructing the Great Tree ofLife
NESCENT: EDUCATION & OUTREACH: MINORITY SERVING Minority Serving Institutions and Other Institutions with Significant Minority Enrollment. Click on the header of any column to change the listing order. If you would like to add or change information in the chart, please contact eog@nescent.org . Institution. City. POPULATION GENETICS IN R Publication. An overview of and a detailed rationale for the building blocks of this resource and how they click together are described in our publication for the Molecular Ecology Resources special issue, Population Genomics with R: Kamvar, Z. N., López-Uribe, M. M., Coughlan, S., Grünwald, N. J., Lapp, H., & Manel, S. (2016).Developing
NESCENT: EDUCATION & OUTREACH: ARCHIVED NEWS NESCent Catalysis Meeting. Drs. Anne Yoder and Claire Kremen, Coordinators. June 13-17, 2006. In 2003, the President of Madagascar, Marc Ravalomanana, announced plans to increase protected lands in Madagascar to 10% of the country. This would be remarkable under any circumstances but becomes even more important in light of the factthat
CALCULATING BASIC POPULATION GENETIC STATISTICS FROM SNP DATA Import data. The data are stored in a text file (genotype=AA..). We will import the dataset into R as a data frame, and then convert the SNP data file into a “genind” object. The dataset “Master_Pinus_data_genotype.txt” can be downloaded here.. The textfile is
POPULATION DIFFERENTIATION FOR SEQUENCE DATA Introduction. Now, we will discuss in more detail how to assess population genetic structure from sequence data. Assuming that you have a priori information about how the individuals are grouped in subpopulations, one can do the following analyses: 1) quantify pairwise subpopulation structure and their significance, 2) test for hierarchical structure among groups of subpopulations, and 3) use NEXUS: AN EXTENSIBLE FILE FORMAT FOR SYSTEMATIC … 3 A BSTRACT.— NEXUS is a file format designed to contain systematic data for use by com-puter programs. The goals of the format are to allow future expansion, to include diverse kinds of CALCULATING BASIC POPULATION GENETIC STATISTICS FROM Section 3: Basic statistics with hierfstat. The function basic.stats () provides the observed heterozygosity ( H o ), mean gene diversities within population ( H s ), F i s, and F s t. The function boot.ppfis () provides confidence interval for F i s. The function indpca () does a PCA on the centered matrix of individuals’ allele frequencies. INDIVIDUAL BASED GENETIC DISTANCE FOR SNP DATA Section 3. Individual genetic distance: number of loci for which individuals differ (dist.gene {ape})The option pairwise.deletion = FALSE in the command dist.gene() removes all loci with one missing values : you an see on the histogram that we get a maximum distance of 3 loci out of 100.. We can see that we get 98 loci with at least onesample missing.
DETECTION OF THE SIGNAL OF SELECTION FROM GENOME SCAN Section 2: PCAdapt To run the function pcadapt(), the user should specify the number K of principal components (PC) to work with: first perform with a large number of principal components (e.g. higher than the number of populations), then use the ‘scree plot’ to chose the value of K.It displays the percentage of variance that is explained byeach PC.
NESCENT: EDUCATION & OUTREACH: EXAMPLES OF EVOLUTION Examples of Evolution: Selective Pressures. and Adaptation. Natural selection works on individuals within a population, with the end result that a variation that provides benefit to the individual will become more prevalent in the population. Natural selection is onevariable in
PHYLOINFORMATICS
A new NESCent working group called Hackathons, Interoperability, Phylogenies (HIP), has so far staged two hackathons under the Phylotastic brand, one held June 4 to 8, 2012 at NESCent, and another one Jan 28 - Feb 1, 2013, at iPlant in Tucson, AZ.Participants built a web-services implementation of the pruning, grafting, name-reconciliation and other functionalities necessary forresearchers to
NESCENT: EDUCATION & OUTREACH: MINORITY SERVING Minority Serving Institutions and Other Institutions with Significant Minority Enrollment. Click on the header of any column to change thelisting order.
CALCULATING BASIC POPULATION GENETIC STATISTICS FROM Section 3: Basic statistics with hierfstat. The function basic.stats () provides the observed heterozygosity ( H o ), mean gene diversities within population ( H s ), F i s, and F s t. The function boot.ppfis () provides confidence interval for F i s. The function indpca () does a PCA on the centered matrix of individuals’ allele frequencies. LINEAR MIXED-EFFECTS MODELS TO CONTROL FOR THE VARIABILITY Data. As an example we’ll use the comparison in Allelic Richness among populations of the orchid bee Euglossa dilemma in the Yucatan peninsula (Soro et al. submitted). Specifically we ask whether the magnitute of isolation could affect the genetic diversity of E. dilemma.The 24 sites where populations were sampled were assigned to 4 categories corresponding to different habitats: CALCULATING GENETIC DIFFERENTIATION AND CLUSTERING METHODS The data are stored in a text file (genotype=AA..). We will import the dataset in R as a data frame, and then convert the SNP data file into a “ genind ” object. The dataset “Master_Pinus_data_genotype.txt” can be downloaded here. The text file is a matrix of (550 rows x 3086 columns). It contains 4 extra columns: first column is the CALCULATING GENETIC DIFFERENTIATION FROM SSR DATA Data. We are going to use the microbov data set from the adegenet package. This data set consists of 704 bovine samples over 30 microsatellite loci (Laloe et al., 2007). We will also need information about the Species, Breed, and Country/Region of origin foreach sample.
SUPPORTING NEXUS
NEXUS (Maddison, et al., 1997) is a data exchange file format for systematic data, designed for use in comparative evolutionary analysis (see NEXUS Specification ). NEXUS is a de facto standard among researchers who focus on phylogenetic inference and hypothesis-testingusing models of
PACKAGES AVAILABLE IN R Packages available in R. Population and Evolutionary Genetics Analysis System. Genetic Analysis of Populations with Mixed Reproduction. Summaries and Population Structure Analyses of Haplotypic and Genotypic Data. An Individual-Based Population Genetic Simulation Environment. Principal Component Analysis for Outlier Detection. CDAO - EVOLUTIONARY INFORMATICS WORKING GROUP The current version of CDAO allows a clear representation of the character-state data matrix, phylogenetic tree topology and character modifications. The users are able to use our ontology terms to describe a complex pattern of characters, including sequence NESCENT: THE NATIONAL EVOLUTIONARY SYNTHESIS CENTERABOUTPEOPLENEWSCONTACTCALENDARSOFTWARE AND DATABASES Catalysis Meeting. Eric Crandall (University of California-Santa Cruz) An integrative understanding of the evolution of genomic imprinting. Working Group. Doris Bachtrog (University of California, Berkeley) The tree of sex – a comprehensive synthesis of sex determination systems in eukaryotes. Working Group. NESCENT: EDUCATION & OUTREACH: MINORITY SERVING Minority Serving Institutions and Other Institutions with Significant Minority Enrollment. Click on the header of any column to change the listing order. If you would like to add or change information in the chart, please contact eog@nescent.org . Institution. City. PHYLOINFORMATICSSEE MORE ON INFORMATICS.NESCENT.ORG CALCULATING BASIC POPULATION GENETIC STATISTICS FROM SNP DATA Import data. The data are stored in a text file (genotype=AA..). We will import the dataset into R as a data frame, and then convert the SNP data file into a “genind” object. The dataset “Master_Pinus_data_genotype.txt” can be downloaded here.. The textfile is
POPULATION GENETICS IN R Publication. An overview of and a detailed rationale for the building blocks of this resource and how they click together are described in our publication for the Molecular Ecology Resources special issue, Population Genomics with R: Kamvar, Z. N., López-Uribe, M. M., Coughlan, S., Grünwald, N. J., Lapp, H., & Manel, S. (2016).Developing
NEXUS: AN EXTENSIBLE FILE FORMAT FOR SYSTEMATIC … 3 A BSTRACT.— NEXUS is a file format designed to contain systematic data for use by com-puter programs. The goals of the format are to allow future expansion, to include diverse kinds of CALCULATING BASIC POPULATION GENETIC STATISTICS FROM Section 3: Basic statistics with hierfstat. The function basic.stats () provides the observed heterozygosity ( H o ), mean gene diversities within population ( H s ), F i s, and F s t. The function boot.ppfis () provides confidence interval for F i s. The function indpca () does a PCA on the centered matrix of individuals’ allele frequencies. POPULATION DIFFERENTIATION FOR SEQUENCE DATA Analysis of Molecular Variance (AMOVA) is a method for estimating population differentiation from molecular data taking into account the mutational distance between alleles. Unlike F s t, which quantifies genetic differentiation based on allele frequencies, AMOVA treats molecular data as vectors and estimates Euclidean distances betweenalleles
DETECTION OF THE SIGNAL OF SELECTION FROM GENOME SCAN Section 2: PCAdapt To run the function pcadapt(), the user should specify the number K of principal components (PC) to work with: first perform with a large number of principal components (e.g. higher than the number of populations), then use the ‘scree plot’ to chose the value of K.It displays the percentage of variance that is explained byeach PC.
PHYLOSOC:TREE AND DATA PLOTTING IN THE PHYLOBASE PROJECTSEE MORE ON INFORMATICS.NESCENT.ORG NESCENT: THE NATIONAL EVOLUTIONARY SYNTHESIS CENTERABOUTPEOPLENEWSCONTACTCALENDARSOFTWARE AND DATABASES Catalysis Meeting. Eric Crandall (University of California-Santa Cruz) An integrative understanding of the evolution of genomic imprinting. Working Group. Doris Bachtrog (University of California, Berkeley) The tree of sex – a comprehensive synthesis of sex determination systems in eukaryotes. Working Group. NESCENT: EDUCATION & OUTREACH: MINORITY SERVING Minority Serving Institutions and Other Institutions with Significant Minority Enrollment. Click on the header of any column to change the listing order. If you would like to add or change information in the chart, please contact eog@nescent.org . Institution. City. PHYLOINFORMATICSSEE MORE ON INFORMATICS.NESCENT.ORG CALCULATING BASIC POPULATION GENETIC STATISTICS FROM SNP DATA Import data. The data are stored in a text file (genotype=AA..). We will import the dataset into R as a data frame, and then convert the SNP data file into a “genind” object. The dataset “Master_Pinus_data_genotype.txt” can be downloaded here.. The textfile is
POPULATION GENETICS IN R Publication. An overview of and a detailed rationale for the building blocks of this resource and how they click together are described in our publication for the Molecular Ecology Resources special issue, Population Genomics with R: Kamvar, Z. N., López-Uribe, M. M., Coughlan, S., Grünwald, N. J., Lapp, H., & Manel, S. (2016).Developing
NEXUS: AN EXTENSIBLE FILE FORMAT FOR SYSTEMATIC … 3 A BSTRACT.— NEXUS is a file format designed to contain systematic data for use by com-puter programs. The goals of the format are to allow future expansion, to include diverse kinds of CALCULATING BASIC POPULATION GENETIC STATISTICS FROM Section 3: Basic statistics with hierfstat. The function basic.stats () provides the observed heterozygosity ( H o ), mean gene diversities within population ( H s ), F i s, and F s t. The function boot.ppfis () provides confidence interval for F i s. The function indpca () does a PCA on the centered matrix of individuals’ allele frequencies. POPULATION DIFFERENTIATION FOR SEQUENCE DATA Analysis of Molecular Variance (AMOVA) is a method for estimating population differentiation from molecular data taking into account the mutational distance between alleles. Unlike F s t, which quantifies genetic differentiation based on allele frequencies, AMOVA treats molecular data as vectors and estimates Euclidean distances betweenalleles
DETECTION OF THE SIGNAL OF SELECTION FROM GENOME SCAN Section 2: PCAdapt To run the function pcadapt(), the user should specify the number K of principal components (PC) to work with: first perform with a large number of principal components (e.g. higher than the number of populations), then use the ‘scree plot’ to chose the value of K.It displays the percentage of variance that is explained byeach PC.
PHYLOSOC:TREE AND DATA PLOTTING IN THE PHYLOBASE PROJECTSEE MORE ON INFORMATICS.NESCENT.ORG NESCENT: NEWS: DARWIN'S BIRTHDAY Celebrating Darwin's Birthday. Charles Darwin was born February 12, 1809 and every year NESCent and other groups celebrate his birthday with a variety of public events. INDIVIDUAL BASED GENETIC DISTANCE FOR SNP DATA Section 3. Individual genetic distance: number of loci for which individuals differ (dist.gene {ape})The option pairwise.deletion = FALSE in the command dist.gene() removes all loci with one missing values : you an see on the histogram that we get a maximum distance of 3 loci out of 100.. We can see that we get 98 loci with at least onesample missing.
DATA CLASSES
The following table describes specialized objects to store data represented in population genetics packages. Conversion between alltypes is possible.
PACKAGES AVAILABLE IN R Packages available in R. Population and Evolutionary Genetics Analysis System. Genetic Analysis of Populations with Mixed Reproduction. Summaries and Population Structure Analyses of Haplotypic and Genotypic Data. An Individual-Based Population Genetic Simulation Environment. Principal Component Analysis for Outlier Detection. LINEAR MIXED-EFFECTS MODELS TO CONTROL FOR THE VARIABILITY Data. As an example we’ll use the comparison in Allelic Richness among populations of the orchid bee Euglossa dilemma in the Yucatan peninsula (Soro et al. submitted). Specifically we ask whether the magnitute of isolation could affect the genetic diversity of E. dilemma.The 24 sites where populations were sampled were assigned to 4 categories corresponding to different habitats: PHYLOSOC:TREE AND DATA PLOTTING IN THE PHYLOBASE PROJECT Project description and timeline Tree and data plotting in the phylobase project My interest in the project. I am interested in this particular proposal because I have been frustrated by the lack of good links between R’s excellent data plotting ability and tree plottingabilities.
SUPPORTING NEXUS
NEXUS (Maddison, et al., 1997) is a data exchange file format for systematic data, designed for use in comparative evolutionary analysis (see NEXUS Specification ). NEXUS is a de facto standard among researchers who focus on phylogenetic inference and hypothesis-testingusing models of
CALCULATING GENETIC DIFFERENTIATION AND CLUSTERING METHODS The data are stored in a text file (genotype=AA..). We will import the dataset in R as a data frame, and then convert the SNP data file into a “ genind ” object. The dataset “Master_Pinus_data_genotype.txt” can be downloaded here. The text file is a matrix of (550 rows x 3086 columns). It contains 4 extra columns: first column is the CDAO - EVOLUTIONARY INFORMATICS WORKING GROUP The current version of CDAO allows a clear representation of the character-state data matrix, phylogenetic tree topology and character modifications. The users are able to use our ontology terms to describe a complex pattern of characters, including sequence CALCULATING GENETIC DIFFERENTIATION FROM SSR DATA Data. We are going to use the microbov data set from the adegenet package. This data set consists of 704 bovine samples over 30 microsatellite loci (Laloe et al., 2007). We will also need information about the Species, Breed, and Country/Region of origin foreach sample.
NESCENT: THE NATIONAL EVOLUTIONARY SYNTHESIS CENTERABOUTPEOPLENEWSCONTACTCALENDARSOFTWARE AND DATABASES Catalysis Meeting. Eric Crandall (University of California-Santa Cruz) An integrative understanding of the evolution of genomic imprinting. Working Group. Doris Bachtrog (University of California, Berkeley) The tree of sex – a comprehensive synthesis of sex determination systems in eukaryotes. Working Group. NESCENT: EDUCATION & OUTREACH: ARCHIVED NEWS NESCent Catalysis Meeting. Drs. Anne Yoder and Claire Kremen, Coordinators. June 13-17, 2006. In 2003, the President of Madagascar, Marc Ravalomanana, announced plans to increase protected lands in Madagascar to 10% of the country. This would be remarkable under any circumstances but becomes even more important in light of the factthat
POPULATION GENETICS IN R Publication. An overview of and a detailed rationale for the building blocks of this resource and how they click together are described in our publication for the Molecular Ecology Resources special issue, Population Genomics with R: Kamvar, Z. N., López-Uribe, M. M., Coughlan, S., Grünwald, N. J., Lapp, H., & Manel, S. (2016).Developing
CALCULATING BASIC POPULATION GENETIC STATISTICS FROM SNP DATA Import data. The data are stored in a text file (genotype=AA..). We will import the dataset into R as a data frame, and then convert the SNP data file into a “genind” object. The dataset “Master_Pinus_data_genotype.txt” can be downloaded here.. The textfile is
POPULATION DIFFERENTIATION FOR SEQUENCE DATA Analysis of Molecular Variance (AMOVA) is a method for estimating population differentiation from molecular data taking into account the mutational distance between alleles. Unlike F s t, which quantifies genetic differentiation based on allele frequencies, AMOVA treats molecular data as vectors and estimates Euclidean distances betweenalleles
CALCULATING BASIC POPULATION GENETIC STATISTICS FROM Section 3: Basic statistics with hierfstat. The function basic.stats () provides the observed heterozygosity ( H o ), mean gene diversities within population ( H s ), F i s, and F s t. The function boot.ppfis () provides confidence interval for F i s. The function indpca () does a PCA on the centered matrix of individuals’ allele frequencies. NEXUS: AN EXTENSIBLE FILE FORMAT FOR SYSTEMATIC … 3 A BSTRACT.— NEXUS is a file format designed to contain systematic data for use by com-puter programs. The goals of the format are to allow future expansion, to include diverse kinds of INDIVIDUAL BASED GENETIC DISTANCE FOR SNP DATA Section 3. Individual genetic distance: number of loci for which individuals differ (dist.gene {ape})The option pairwise.deletion = FALSE in the command dist.gene() removes all loci with one missing values : you an see on the histogram that we get a maximum distance of 3 loci out of 100.. We can see that we get 98 loci with at least onesample missing.
DETECTION OF THE SIGNAL OF SELECTION FROM GENOME SCAN Section 2: PCAdapt To run the function pcadapt(), the user should specify the number K of principal components (PC) to work with: first perform with a large number of principal components (e.g. higher than the number of populations), then use the ‘scree plot’ to chose the value of K.It displays the percentage of variance that is explained byeach PC.
CALCULATING GENETIC DIFFERENTIATION FROM SSR DATA First, we need to load our data. Since the data is distributed with adegenet, we can load it simply by using the function data (). Since we want to associate the different population strata with the data set, we also need to read in bovine_strata.csv as a data frame. The microbov data set is NESCENT: THE NATIONAL EVOLUTIONARY SYNTHESIS CENTERABOUTPEOPLENEWSCONTACTCALENDARSOFTWARE AND DATABASES Catalysis Meeting. Eric Crandall (University of California-Santa Cruz) An integrative understanding of the evolution of genomic imprinting. Working Group. Doris Bachtrog (University of California, Berkeley) The tree of sex – a comprehensive synthesis of sex determination systems in eukaryotes. Working Group. NESCENT: EDUCATION & OUTREACH: ARCHIVED NEWS NESCent Catalysis Meeting. Drs. Anne Yoder and Claire Kremen, Coordinators. June 13-17, 2006. In 2003, the President of Madagascar, Marc Ravalomanana, announced plans to increase protected lands in Madagascar to 10% of the country. This would be remarkable under any circumstances but becomes even more important in light of the factthat
POPULATION GENETICS IN R Publication. An overview of and a detailed rationale for the building blocks of this resource and how they click together are described in our publication for the Molecular Ecology Resources special issue, Population Genomics with R: Kamvar, Z. N., López-Uribe, M. M., Coughlan, S., Grünwald, N. J., Lapp, H., & Manel, S. (2016).Developing
CALCULATING BASIC POPULATION GENETIC STATISTICS FROM SNP DATA Import data. The data are stored in a text file (genotype=AA..). We will import the dataset into R as a data frame, and then convert the SNP data file into a “genind” object. The dataset “Master_Pinus_data_genotype.txt” can be downloaded here.. The textfile is
POPULATION DIFFERENTIATION FOR SEQUENCE DATA Analysis of Molecular Variance (AMOVA) is a method for estimating population differentiation from molecular data taking into account the mutational distance between alleles. Unlike F s t, which quantifies genetic differentiation based on allele frequencies, AMOVA treats molecular data as vectors and estimates Euclidean distances betweenalleles
CALCULATING BASIC POPULATION GENETIC STATISTICS FROM Section 3: Basic statistics with hierfstat. The function basic.stats () provides the observed heterozygosity ( H o ), mean gene diversities within population ( H s ), F i s, and F s t. The function boot.ppfis () provides confidence interval for F i s. The function indpca () does a PCA on the centered matrix of individuals’ allele frequencies. NEXUS: AN EXTENSIBLE FILE FORMAT FOR SYSTEMATIC … 3 A BSTRACT.— NEXUS is a file format designed to contain systematic data for use by com-puter programs. The goals of the format are to allow future expansion, to include diverse kinds of INDIVIDUAL BASED GENETIC DISTANCE FOR SNP DATA Section 3. Individual genetic distance: number of loci for which individuals differ (dist.gene {ape})The option pairwise.deletion = FALSE in the command dist.gene() removes all loci with one missing values : you an see on the histogram that we get a maximum distance of 3 loci out of 100.. We can see that we get 98 loci with at least onesample missing.
DETECTION OF THE SIGNAL OF SELECTION FROM GENOME SCAN Section 2: PCAdapt To run the function pcadapt(), the user should specify the number K of principal components (PC) to work with: first perform with a large number of principal components (e.g. higher than the number of populations), then use the ‘scree plot’ to chose the value of K.It displays the percentage of variance that is explained byeach PC.
CALCULATING GENETIC DIFFERENTIATION FROM SSR DATA First, we need to load our data. Since the data is distributed with adegenet, we can load it simply by using the function data (). Since we want to associate the different population strata with the data set, we also need to read in bovine_strata.csv as a data frame. The microbov data set is NESCENT: ABOUT THE CENTER The National Evolutionary Synthesis Center (NESCent) is a nonprofit science center dedicated to cross-disciplinary research in evolution. NESCent is jointly operated by Duke University, The University of North Carolina at Chapel Hill, and North Carolina State University,and
NESCENT: SCIENCE & SYNTHESIS: GRADUATE FELLOWSHIPS Graduate Fellowships. The National Evolutionary Synthesis Center is now including graduate training in its portfolio by offering one-semester fellowships for graduate students to pursue research with a NESCent Sabbatical Scholar, Postdoctoral Fellow, or Working Group.PHYLOINFORMATICS
A new NESCent working group called Hackathons, Interoperability, Phylogenies (HIP), has so far staged two hackathons under the Phylotastic brand, one held June 4 to 8, 2012 at NESCent, and another one Jan 28 - Feb 1, 2013, at iPlant in Tucson, AZ.Participants built a web-services implementation of the pruning, grafting, name-reconciliation and other functionalities necessary forresearchers to
LINEAR MIXED-EFFECTS MODELS TO CONTROL FOR THE VARIABILITY Data. As an example we’ll use the comparison in Allelic Richness among populations of the orchid bee Euglossa dilemma in the Yucatan peninsula (Soro et al. submitted). Specifically we ask whether the magnitute of isolation could affect the genetic diversity of E. dilemma.The 24 sites where populations were sampled were assigned to 4 categories corresponding to different habitats:DATA CLASSES
The following table describes specialized objects to store data represented in population genetics packages. Conversion between alltypes is possible.
DETECTION OF THE SIGNAL OF SELECTION FROM GENOME SCAN Section 2: PCAdapt To run the function pcadapt(), the user should specify the number K of principal components (PC) to work with: first perform with a large number of principal components (e.g. higher than the number of populations), then use the ‘scree plot’ to chose the value of K.It displays the percentage of variance that is explained byeach PC.
PACKAGES AVAILABLE IN R Packages available in R. Population and Evolutionary Genetics Analysis System. Genetic Analysis of Populations with Mixed Reproduction. Summaries and Population Structure Analyses of Haplotypic and Genotypic Data. An Individual-Based Population Genetic Simulation Environment. Principal Component Analysis for Outlier Detection.SUPPORTING NEXUS
NEXUS (Maddison, et al., 1997) is a data exchange file format for systematic data, designed for use in comparative evolutionary analysis (see NEXUS Specification ). NEXUS is a de facto standard among researchers who focus on phylogenetic inference and hypothesis-testingusing models of
CDAO - EVOLUTIONARY INFORMATICS WORKING GROUP The current version of CDAO allows a clear representation of the character-state data matrix, phylogenetic tree topology and character modifications. The users are able to use our ontology terms to describe a complex pattern of characters, including sequenceWRITING R PACKAGES
A word on modularity. R is an open source language with a strong community of developers contributing new methods and analyses. The population genetics community has worked hard to create data classes that can be used efficiently between packages, expanding the number of analyses that can be done by users in a reproducible manner. NESCENT: THE NATIONAL EVOLUTIONARY SYNTHESIS CENTERABOUTPEOPLENEWSCONTACTCALENDARSOFTWARE AND DATABASES Catalysis Meeting. Eric Crandall (University of California-Santa Cruz) An integrative understanding of the evolution of genomic imprinting. Working Group. Doris Bachtrog (University of California, Berkeley) The tree of sex – a comprehensive synthesis of sex determination systems in eukaryotes. Working Group. POPULATION GENETICS IN R Publication. An overview of and a detailed rationale for the building blocks of this resource and how they click together are described in our publication for the Molecular Ecology Resources special issue, Population Genomics with R: Kamvar, Z. N., López-Uribe, M. M., Coughlan, S., Grünwald, N. J., Lapp, H., & Manel, S. (2016).Developing
PHYLOINFORMATICSSEE MORE ON INFORMATICS.NESCENT.ORG CALCULATING BASIC POPULATION GENETIC STATISTICS FROM SNP DATA Import data. The data are stored in a text file (genotype=AA..). We will import the dataset into R as a data frame, and then convert the SNP data file into a “genind” object. The dataset “Master_Pinus_data_genotype.txt” can be downloaded here.. The textfile is
DATA CLASSES
The following table describes specialized objects to store data represented in population genetics packages. Conversion between alltypes is possible.
LINEAR MIXED-EFFECTS MODELS TO CONTROL FOR THE VARIABILITY Data. As an example we’ll use the comparison in Allelic Richness among populations of the orchid bee Euglossa dilemma in the Yucatan peninsula (Soro et al. submitted). Specifically we ask whether the magnitute of isolation could affect the genetic diversity of E. dilemma.The 24 sites where populations were sampled were assigned to 4 categories corresponding to different habitats: CDAO - EVOLUTIONARY INFORMATICS WORKING GROUPSEE MORE ONEVOINFO.NESCENT.ORG
SUPPORTING NEXUS
POPULATION DIFFERENTIATION FOR SEQUENCE DATA Analysis of Molecular Variance (AMOVA) is a method for estimating population differentiation from molecular data taking into account the mutational distance between alleles. Unlike F s t, which quantifies genetic differentiation based on allele frequencies, AMOVA treats molecular data as vectors and estimates Euclidean distances betweenalleles
CALCULATING BASIC POPULATION GENETIC STATISTICS FROM Section 3: Basic statistics with hierfstat. The function basic.stats () provides the observed heterozygosity ( H o ), mean gene diversities within population ( H s ), F i s, and F s t. The function boot.ppfis () provides confidence interval for F i s. The function indpca () does a PCA on the centered matrix of individuals’ allele frequencies. NESCENT: THE NATIONAL EVOLUTIONARY SYNTHESIS CENTERABOUTPEOPLENEWSCONTACTCALENDARSOFTWARE AND DATABASES Catalysis Meeting. Eric Crandall (University of California-Santa Cruz) An integrative understanding of the evolution of genomic imprinting. Working Group. Doris Bachtrog (University of California, Berkeley) The tree of sex – a comprehensive synthesis of sex determination systems in eukaryotes. Working Group. POPULATION GENETICS IN R Publication. An overview of and a detailed rationale for the building blocks of this resource and how they click together are described in our publication for the Molecular Ecology Resources special issue, Population Genomics with R: Kamvar, Z. N., López-Uribe, M. M., Coughlan, S., Grünwald, N. J., Lapp, H., & Manel, S. (2016).Developing
PHYLOINFORMATICSSEE MORE ON INFORMATICS.NESCENT.ORG CALCULATING BASIC POPULATION GENETIC STATISTICS FROM SNP DATA Import data. The data are stored in a text file (genotype=AA..). We will import the dataset into R as a data frame, and then convert the SNP data file into a “genind” object. The dataset “Master_Pinus_data_genotype.txt” can be downloaded here.. The textfile is
DATA CLASSES
The following table describes specialized objects to store data represented in population genetics packages. Conversion between alltypes is possible.
LINEAR MIXED-EFFECTS MODELS TO CONTROL FOR THE VARIABILITY Data. As an example we’ll use the comparison in Allelic Richness among populations of the orchid bee Euglossa dilemma in the Yucatan peninsula (Soro et al. submitted). Specifically we ask whether the magnitute of isolation could affect the genetic diversity of E. dilemma.The 24 sites where populations were sampled were assigned to 4 categories corresponding to different habitats: CDAO - EVOLUTIONARY INFORMATICS WORKING GROUPSEE MORE ONEVOINFO.NESCENT.ORG
SUPPORTING NEXUS
POPULATION DIFFERENTIATION FOR SEQUENCE DATA Analysis of Molecular Variance (AMOVA) is a method for estimating population differentiation from molecular data taking into account the mutational distance between alleles. Unlike F s t, which quantifies genetic differentiation based on allele frequencies, AMOVA treats molecular data as vectors and estimates Euclidean distances betweenalleles
CALCULATING BASIC POPULATION GENETIC STATISTICS FROM Section 3: Basic statistics with hierfstat. The function basic.stats () provides the observed heterozygosity ( H o ), mean gene diversities within population ( H s ), F i s, and F s t. The function boot.ppfis () provides confidence interval for F i s. The function indpca () does a PCA on the centered matrix of individuals’ allele frequencies. NESCENT: SCIENCE & SYNTHESIS Cephalopod genomics gets a boost. If octopuses, squids and cuttlefish are so cool, and so clever, how come there are no cephalopod genomesyet?
CALL FOR NESCENT COURSE PROPOSALS NESCent Short Courses - Request for Proposals . NESCent welcomes ideas and proposals for short courses (1-2 weeks) at the postgraduate level on topics of relevance to synthetic evolutionary science. NESCENT: SCIENCE & SYNTHESIS: GRADUATE FELLOWSHIPS Graduate Fellowships. The National Evolutionary Synthesis Center is now including graduate training in its portfolio by offering one-semester fellowships for graduate students to pursue research with a NESCent Sabbatical Scholar, Postdoctoral Fellow, or Working Group. NESCENT: SCIENCE & SYNTHESIS: CALL FOR PROPOSALS NESCent has transitioned to the Triangle Center for Evolutionary Medicine (TriCEM) as of June 2015; proposals for NESCent programs are no longer being accepted but see TriCEM.org. NESCent provides a range of support options for synthetic evolutionary research. NESCENT: NEWS: DARWIN'S BIRTHDAY Celebrating Darwin's Birthday. Charles Darwin was born February 12, 1809 and every year NESCent and other groups celebrate his birthday with a variety of public events.DATA CLASSES
The following table describes specialized objects to store data represented in population genetics packages. Conversion between alltypes is possible.
NEXUS: AN EXTENSIBLE FILE FORMAT FOR SYSTEMATIC INFORMATION 3 A BSTRACT.— NEXUS is a file format designed to contain systematic data for use by com-puter programs. The goals of the format are to allow future expansion, to include diverse kinds of PACKAGES AVAILABLE IN R Packages available in R. Population and Evolutionary Genetics Analysis System. Genetic Analysis of Populations with Mixed Reproduction. Summaries and Population Structure Analyses of Haplotypic and Genotypic Data. An Individual-Based Population Genetic Simulation Environment. Principal Component Analysis for Outlier Detection. DETECTION OF THE SIGNAL OF SELECTION FROM GENOME SCAN Section 2: PCAdapt To run the function pcadapt(), the user should specify the number K of principal components (PC) to work with: first perform with a large number of principal components (e.g. higher than the number of populations), then use the ‘scree plot’ to chose the value of K.It displays the percentage of variance that is explained byeach PC.
PHYLOSOC:TREE AND DATA PLOTTING IN THE PHYLOBASE PROJECT Project description and timeline Tree and data plotting in the phylobase project My interest in the project. I am interested in this particular proposal because I have been frustrated by the lack of good links between R’s excellent data plotting ability and tree plottingabilities.
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Kate Hertweck (University of Missouri) Comparative biology of transposable element proliferationPostdoctoral Fellow
Mira Han (Indiana University-Bloomington) Gene evolution in genomic context: Integrating genomic location into gene evolution modelsPostdoctoral Fellow
Tami Cruickshank (University of Indiana) Population genetics of maternal effects and their influence onmolecular evolution
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Robert Lanfear (Australian National University) Synthesising methods and data to understand the mutational processesthat shape genomes
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Elizabeth Sbrocco (Boston University) Exploring environmental correlates of range limits across a marine biodiveristy hotspotPostdoctoral Fellow
Adam Smith (University of Texas, Austin) Evaluating effects of temporal distribution of fossil calibrations ondivergence analyses
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Paul Harnik (Stanford University) Ecological controls on evolutionary rates in marine systemsCatalysis Meeting
David Liberles (University of Wyoming) Modeling protein structural and energetic constraints on sequenceevolution
Catalysis Meeting
Andrew Groover (US Forest Service and University of California-Davis) Evolutionary origins and development of woody plantsCatalysis Meeting
Jason Wolf (University of Bath, UK) An integrative understanding of the evolution of genomic imprintingCatalysis Meeting
Eric Crandall (University of California-Santa Cruz) An integrative understanding of the evolution of genomic imprintingWorking Group
Doris Bachtrog (University of California, Berkeley) The tree of sex – a comprehensive synthesis of sex determination systems in eukaryotesWorking Group
Jennifer Fewell (Arizona State University) Large-scale demographic, network and behavioral trait analyses ofsociality
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Arlin Stoltzfus (Center for Advanced Research in Biotechnology) HIP: Hackathons, Interoperability, Phylogenies Long-term Sabbatical Scholar Christina Caruso (University of Guelph, Canada) The evolutionary ecology of genetic conflict in plants Long-term Sabbatical Scholar Dena Smith (University of Colorado, Boulder) Evolution of the Coleoptera: A paleontological perspective Long-term Sabbatical Scholar Michael Wade (Indiana University, Bloomington) A critical synthesis of indirect genetic effects in adaptive evolution Short-term Sabbatical Scholar Douglas Soltis (University of Florida), Pamela Soltis (University ofFlorida)
Reconstructing the Great Tree of Life Short-term Sabbatical Scholar Rebecca Safran (University of Colorado) An integrative evolutionary approach to examine sexual selection as a mechanism of speciationTriangle Scholar
Tyler Curtain (University of North Carolina, Chapel Hill) Darwin and Nietzsche: evolutionary thought within literary theoryMAIN NAVIGATION
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