Popgen: Difference between revisions
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Created page with "CoGe can generate basic summary statistics given a GVCF input file and an annotation genome. == Summary Statistics == Summary statistics computed per feature overall (gene, C..." |
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== Steps == | == Steps == | ||
1. Load a GVCF file | ===1. Load a GVCF file=== | ||
2. In the resulting experiment's menu select "Analyze Diversity". | See the [[LoadExperiment]] tool to load a GCVF file against an existing genome in CoGe. | ||
3. Open the finished result in the PopGen tool to see results in tabular and graphical form. | |||
===2. Analyze Diversity=== | |||
In the resulting experiment's menu select "Analyze Diversity". | |||
===3. Open the finished result=== | |||
Open the result in the PopGen tool to see results in tabular and graphical form. | |||
Revision as of 17:59, 9 February 2016
CoGe can generate basic summary statistics given a GVCF input file and an annotation genome.
Summary Statistics
Summary statistics computed per feature overall (gene, CDS, etc) and by 0/4-fold degeneracy (for CDS only):
- Nucleotide diversity (pi) - average number of pairwise differences between variant sequences
- Watterson's theta
- Tajima's D
Steps
1. Load a GVCF file
See the LoadExperiment tool to load a GCVF file against an existing genome in CoGe.
2. Analyze Diversity
In the resulting experiment's menu select "Analyze Diversity".
3. Open the finished result
Open the result in the PopGen tool to see results in tabular and graphical form.