AveDissR

AveDissR assesses genetic distinctness and redundancy in plant germplasm collections by computing average dissimilarity and integrating analysis of molecular variance (AMOVA) with principal coordinates analysis (PCoA).


Key Features:

  • Integrated analyses: Combines dissimilarity calculation, analysis of molecular variance (AMOVA), and principal coordinates analysis (PCoA) within a single workflow.
  • Average dissimilarity metric: Calculates the average dissimilarity of each accession relative to other accessions in the dataset.
  • Marker compatibility: Supports dominant markers such as amplified fragment length polymorphisms (AFLPs) and codominant markers including simple sequence repeats (SSRs) and single-nucleotide polymorphisms (SNPs) for large datasets.
  • Output generation: Produces comprehensive output files for downstream germplasm assessment and interpretation.

Scientific Applications:

  • Germplasm distinctness assessment: Identifies genetically distinct or redundant accessions within plant germplasm collections.
  • Unique resource identification: Detects unique genetic resources for conservation and utilization.
  • Breeding program support: Informs selection and optimization in breeding programs through characterization of genetic variation.
  • Biodiversity and crop improvement: Supports conservation strategies and crop improvement efforts by quantifying genetic relationships among accessions.

Methodology:

Calculates the average dissimilarity of each accession relative to others and integrates this metric with analysis of molecular variance (AMOVA) and principal coordinates analysis (PCoA).

Topics

Details

Tool Type:
library
Operating Systems:
Linux, Windows, Mac
Programming Languages:
R
Added:
8/6/2018
Last Updated:
12/10/2018

Operations

Publications

Yang M, Fu Y. AveDissR: An R function for assessing genetic distinctness and genetic redundancy. Applications in Plant Sciences. 2017;5(7). doi:10.3732/apps.1700018. PMID:28791204. PMCID:PMC5546164.

PMID: 28791204
PMCID: PMC5546164
Funding: - National Natural Science Foundation of China: 31670678

Documentation