PCA - Revision history

Albrecht: /* single read sampling */

2018-02-07T14:56:42Z

single read sampling

← Older revision		Revision as of 16:56, 7 February 2018
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	= single read sampling =		= 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 found here:[[PCA_MDS]]. However, it requires low error rate and polymorphic sites need to be inferred (or provided by user)		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 found here:[[PCA_MDS]]. However, it requires low error rate and polymorphic sites need to be inferred (or provided by user based on for example reference data such as the 1000G for humans)

Albrecht: /* NGS tools */

2018-02-07T14:55:46Z

NGS tools

← Older revision		Revision as of 16:55, 7 February 2018
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	This works without the need to call SNPs or genotypes based on genotype likelihoods.		This works even without the need to call SNPs or genotypes based on genotype likelihoods.

	NB! If you have very different depths for the different samples, e.i. some very low and others medium and high, then you might want to use the single base sampling approach [[PCA_MDS]]		NB! If you have very different depths for the different samples, e.i. some very low and others medium and high, then you might want to use the PCAngsd or use single base sampling approach [[PCA_MDS]]

	The main documentation for this is found here:		The main documentation for this is found here:

Albrecht at 14:54, 7 February 2018

2018-02-07T14:54:45Z

@@ Line 1: / Line 1: @@
 = 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.

Albrecht at 11:36, 13 May 2016

2016-05-13T11:36:34Z

← Older revision		Revision as of 13:36, 13 May 2016
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	This works without the need to call SNPs or genotypes based on genotype likelihoods		This works without the need to call SNPs or genotypes based on genotype likelihoods.

			NB! If you have very different depths for the different samples, e.i. some very low and others medium and high, then you might want to use the single base sampling approach [[PCA_MDS]]

	The main documentation for this is found here:		The main documentation for this is found here:

Albrecht at 10:23, 27 April 2016

2016-04-27T10:23:08Z

← Older revision		Revision as of 12:23, 27 April 2016
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	= single read sampling =		= 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)		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 found here:[[PCA_MDS]]. However, it requires low error rate and polymorphic sites need to be inferred (or provided by user)

Albrecht at 10:22, 27 April 2016

2016-04-27T10:22:17Z

@@ Line 1: / Line 1: @@
-Matteo Fumagalli has been working on methods for doing PCA/Covariance based on ANGSD output files.
 The main documentation for this is found here:
 https://github.com/mfumagalli/ngsTools and here https://github.com/mfumagalli/ngsTools#ngscovar

Thorfinn: Created page with "Matteo Fumagalli has been working on methods for doing PCA/Covariance based on ANGSD output files. The main documentation for this is found here: https://github.com/mfumagall..."

2015-07-30T14:22:48Z

Created page with "Matteo Fumagalli has been working on methods for doing PCA/Covariance based on ANGSD output files. The main documentation for this is found here: https://github.com/mfumagall..."

New page

Matteo Fumagalli has been working on methods for doing PCA/Covariance based on ANGSD output files.

The main documentation for this is found here:
https://github.com/mfumagalli/ngsTools and here https://github.com/mfumagalli/ngsTools#ngscovar