ANGSD: Analysis of next generation Sequencing Data
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PCA: Difference between revisions
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Matteo | |||
= Genotype likelihood approach = | |||
Matteo Fumagallis methods for doing PCA/Covariance based on ANGSD output files: | |||
Fumagalli, M, Vieira, FG, Korneliussen, TS, Linderoth, T, Huerta-Sánchez, E, Albrechtsen, A, Nielsen, R (2013). Quantifying population genetic differentiation from next-generation sequencing data. Genetics, 195, 3:979-92. | |||
This works without the need to call SNPs or genotypes based on genotype likelihoods | |||
The main documentation for this is found here: | The main documentation for this is found here: | ||
https://github.com/mfumagalli/ngsTools and here https://github.com/mfumagalli/ngsTools#ngscovar | https://github.com/mfumagalli/ngsTools and here https://github.com/mfumagalli/ngsTools#ngscovar | ||
= single read sampling = | |||
Both PCA and MDS can be performed based on sampling of a single read at each site. This can work even with very low depth data e.g. <1X. This method can be [[PCA_MDS found here]]. However, it requires low error rate and polymorphic sites need to be inferred (or provided by user) |
Revision as of 11:22, 27 April 2016
Genotype likelihood approach
Matteo Fumagallis methods for doing PCA/Covariance based on ANGSD output files:
Fumagalli, M, Vieira, FG, Korneliussen, TS, Linderoth, T, Huerta-Sánchez, E, Albrechtsen, A, Nielsen, R (2013). Quantifying population genetic differentiation from next-generation sequencing data. Genetics, 195, 3:979-92.
This works without the need to call SNPs or genotypes based on genotype likelihoods
The main documentation for this is found here: https://github.com/mfumagalli/ngsTools and here https://github.com/mfumagalli/ngsTools#ngscovar
single read sampling
Both PCA and MDS can be performed based on sampling of a single read at each site. This can work even with very low depth data e.g. <1X. This method can be PCA_MDS found here. However, it requires low error rate and polymorphic sites need to be inferred (or provided by user)