Icon of program: Partition

Partition for Windows

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Editors’ Review

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Partition is a model-based statistical package designed to identify population subdivisions and assign individuals to populations using genotype data from co-dominant marker loci.

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Partition 0/3

  • Pros

    • Identifies population sub-division and assigns individuals
    • Uses genotypes at co-dominant marker loci
    • Supports microsatellites and allozymes
    • Model is appropriate for out-crossing diploid organisms
    • Handles unknown population composition and number

  • Cons

    • Requires unlinked or loosely linked marker loci
    • Assumes linkage equilibrium
    • Assumes Hardy-Weinberg equilibrium for source populations
Icon of program: Partition

Partition for Windows

Download now

Used Partition for Windows?

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Full Specifications

GENERAL
Release
Latest update
Version
2.0
OPERATING SYSTEMS
Platform
Windows
Operating System
  • Windows 7
  • Windows ME
  • Windows 98
  • Windows XP
  • Windows 10
  • Windows 2000
  • Windows NT
  • Windows 2003
  • Windows Vista
Additional Requirements
None
POPULARITY
Total Downloads
484
Downloads Last Week
0
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Developer’s Description

By Khalid Belkhir and Kevin J Dawson
Identify population sub division and assign individuals to populations.
Partition is a model-based statistical software package for identifying population sub-division (barriers to gene flow) and assigning individuals to populations, on the basis of their genotypes at co-dominant marker loci. Suitable genetic markers include microsatellites and allozymes. Unlinked, or loosely linked, marker loci should be used, so that the assumption of linkage equilibrium is a reasonable one.

The underlying population genetic model is appropriate for out-crossing diploid organisms. It assumes that the individuals in the sample belong to a number of separate source populations. These source populations are assumed to be at Hardy-Weinberg and linkage equilibrium, but the allelic composition of these source populations, and even the number of source populations represented in the sample, are treated as parameters whose values are unknown.

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