Luckau Protocols:STRUCTURE

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STRUCTURE

Tara K. Luckau's Home Page

Conservation Genetics Lab Notebook

Tara's Protocols


Contents

Purpose

The software program STRUCTURE is "a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations."


Protocol

  • Structure 2.3.3 for MacOS


Formatting Data

MS Excel

  • ROW 1 = marker names (structure term = "Marker Name")
    • since diploid, leave an extra column for the second allele between markers
  • COLUMN 1 = sample names (structure term = "Label")
  • COLUMN 2 = population designation (structure term = "PopData", in integer form)
Tara's thesis = county area
    • 1 = Camp Pendleton
    • 2 = Rancho Jamul / Hollenbeck
    • 3 = Point Loma / Cabrillo National Monument
    • 4 = Santa Ysabel Open Space Preserve
    • 5 = Torrey Pines State Natural Reserve
  • COLUMN 3 = location designation (structure term = "LocData", in integer form)
Tara's thesis = array cluster
    • 1 = red cluster
    • 2 = green cluster
    • 3 = blue cluster



MS Word

  • copy data from Excel, Paste Special into Word
    • as Unformatted Text
  • Save As ...
    • Plain Text (.txt)
    • File Conversion: Latin-US (DOS), CR/LF


Structure

New Project

  • File: New Project
  • Step 1
    • Name the project: 20111106AXRJ
    • Select directory: Research/Structure/StructureDirectory
    • Choose data file: browse to the .txt file you just made (from Excel and Word)
  • Step 2
    • Number of individuals: 93
    • Ploidy of data: 2
    • Number of loci: 10
    • Missing data value: 0
  • Step 3
    • Row of marker names - check
    • Data file stores data for individuals in a single line - check
  • Step 4
    • Individual ID for each individual - check
    • Putative population origin for each individual - check
    • Sampling location information - check


New Parameter Set

  • Parameter Set: New...
  • Run Length: 10,000 and 10,000
  • Ancestry Model
Admixture
Independent (we expect allele frequencies in different populations to be reasonably different from each other; works well for many data sets (strong structure))
  • Allele Frequency Model: Correlated (frequencies in the different populations are likely to be similar, due to migration or shared ancestry; improves clustering for closely related populations (subtle structure), but may increase the risk of overestimating K)
  • Advanced: unclick "Compute probability of data (for estimating K)" to make program run faster


Run Project

  • Parameter Set: Run
  • K=1 through K=number of sampling sites
  • to determine the most likely K,



Literature and Supporting Information

  • Pritchard J, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959.
  • Falush D, Stephens M, Pritchard JK (2003) Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164:1567–1587.
  • Falush D, Stephens M, Pritchard JK (2007) Inference of population structure using multilocus genotype data: dominant markers and null alleles. Molecular Ecology Notes 7:574–578.
  • Hubisz MJ, Falush D, Stephens M, Pritchard JK (2009) Inferring weak population structure with the assistance of sample group information. Molecular Ecology Resources 9:1322–1332.
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