Masterarbeit, Heidi Lischer

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====== Geneland ======
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**[[http://www2.imm.dtu.dk/~gigu/Geneland/|Geneland]]**\\
[[http://www2.imm.dtu.dk/~gigu/Geneland/Geneland-Doc.pdf|manual]]


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Geneland (12. April 2011)\\
Geneland is a computer program whose main goal is to process individual multilocus genetic data to detect population structure, i.e sub-populations at (or close to) Hardy-Weinberg and linkage equilibrium. Although the concept of population refers here to genetic structure only, it is often realistic to assume that populations are spatially organised. Toward this aim, Geneland is based on a spatially explicit model that can make use of both geographic and genetic informations to estimate the number of populations in a dataset and delineate their spatial organisation. 
Important areas of application include landscape genetics, conservation genetics, human genetics and epidemiology. 

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===== Program information =====
The program is released as an add-on to the free statistical program R and is currently available for Linux, Mac-OS and Windows. It includes a fully clickable user interface requiring no particular knowledge of R. 

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===== Data type handled =====
  * Microsatellites
  * SNPs
  * AFLP
  * DNA 

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===== Input Files =====
  * Genotypes file: contains the genotypes of n haploid or diploid individuals at L co-dominant markers
  * Coordinates file (optional): contains the spatial coordinates representative of each individual.




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==== Genotypes file ====
Assuming that you have data for n individuals genotyped at L loci, the data must be arranged in
  * a plain ascii file
  * without any extra invisible characters (like in MS-Word .doc files)
  * with one line per individual
  * each allele must be coded by an integer
  * the number of digits of each field is arbitrary and can vary across loci
  * extra header lines are not allowed 
  * missing data are allowed and can be coded by any arbitrary character string, (e.g. 000, 00, NA or -999). By default, it is assumed that missing data are coded as NA.
  * for haploid organisms with L loci, the genotype file must have L columns.

=== diploid data: ===
  * Codominant data (SNP or Microsat):
    * one line and 2x L columns per individual
    * Example (2 individuals with 10 loci, missing data are coded as 000):
<code>
198 000 358 362 141 141 179 000 208 224 243 243 278 284 86 88 120 124 238 244
200 202 000 358 141 141 183 183 218 224 237 243 276 278 88 88 120 124 240 244
</code>

  * Dominant data (AFLP):
    * one line and L columns per individual
    * absence/presence of the allele is coded as 0/1
    * Example (2 individuals with 10 loci, missing data are coded as 000):
<code>
0 1 1 1 0 1 0 0 0
1 0 0 1 1 0 0 1 000
</code>

=== haploid data: ===
  * for Microsat, SNP or mtDNA data
  * one line and L columns per individual
  * Example (2 individuals with 10 loci, missing data are coded as 000):
<code>
198 000 358 362 141 141 179 000 208 224
200 202 000 358 141 141 183 183 218 224
</code>


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==== Coordinates file ====
  * one line per individual and two columns (x-axis and y-axis coordinate)
  * the units do not matter
  * coordinates are planar coordinates such as UTM coordinates. Coordinates given as spherical coordinates will be interpreted as planar coordinates.
  * extra header lines are not allowed
  * missing data are not allowed. If some coordinates are missing, you can either substitute an estimated value or do the analysis without spatial coordinates at all using the non spatial model.
  * Example (2 individuals):
<code>
25.6 745.2
54.1 827.8
</code>

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===== How to cite =====
  * G. Guillot and F. Santos Using AFLP markers and the Geneland program for the inference of population genetic structure. Molecular Ecology Resources, 2010
  * G. Guillot and F. Santos A computer program to simulate multilocus genotype data with spatially auto-correlated allele frequencies. Molecular Ecology Resources, 9(4), 1112-1120, 2009. 
  * G. Guillot. Inference of structure in subdivided populations at low levels of genetic differentiation. The correlated allele frequencies model revisited. Bioinformatics, 24:2222-2228, 2008. 
  * G. Guillot, F. Santos and A. Estoup. Analysing georeferenced population genetics data with Geneland:  a new algorithm to deal with null alleles and a friendly graphical user interface. Bioinformatics, 24(11):1406-1407, 2008. 
  * G. Guillot, Mortier, F., Estoup, A. Geneland: A program for landscape genetics. Molecular Ecology Notes, 5, 712-715, 2005. 
  * G. Guillot, Estoup, A., Mortier, F. Cosson, J.F. A spatial statistical model for landscape genetics. Genetics, 170, 1261-1280, 2005.