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Data Analysis

The Single Nucleotide Polymorphism (SNP) data generated from the two SNP genotyping platforms in GSL contains the actual nucleotide calls for each marker locus. A SNP map containing the physical position of the SNP markers are sent to clients along with the SNP data.

SNP markers used in the BeadXpress and Fluidigm system are bi-allelic, which means there are only two possible alleles that can be detected in each marker locus. In case of a third allele (which is very rare), it will just be represented as a missing data or (.) in the SNP data matrix. For a homozygous call, it could represented by the four nucleotides such as A, T, C or G.  While for a heterozygous call, it is represented by a slash (/) such as A/T, C/G…etc.

For downstream data analysis, the SNP data results should be formatted according to the required format of the software of interest. You can format your data results and data analysis using the IRRI GSL-Galaxy.

There are also several genotype analysis software that can be downloaded for free.

Flapjack. A graphical tool used to facilitate analysis of large data generated from high-throughput SNP platforms and genotyping technologies by allowing visualization of markers, lines and their corresponding SNP calls per chromosome. 

GGT 2.0. Stands for Graphical GenoTypes. A software used to generate a graphical representation of molecular marker data in a chromosome.

Powermarker. Free graphical interface which consists of statistical methods for population that allows user to perform different marker data analysis and manipulate and view all data objects.

Structure 2.2. A software package used for investigating population structure.




  • Milne I, Flapjack-graphical genotype visualization. Bioinformatics. 2010;24: 3133-3134.
  • van Berloo R. GGT 2.0: versatile Software for visualization and analysis of genetic data. J. Hered. 2008;99:232-236.
  • Liu K,  Muse SV . POWERMARKER: an integrated analysis environment for genetic marker analysis. Bioinformatics.2005;21:2128-2129.
  • Simon P. Q-Gene: processing quantitative real-time RT-PCR data.Bioinformatics. 2003;19:1439–1440.
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