EIGENSOFT specifications


Unique identifier OMICS_07868
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Version 6.0.1
Stability Stable
Maintained Yes



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  • person_outline Samuela Pollack <>

EIGENSOFT articles

EIGENSOFT citations

PMCID: 5312535

[…] (rad and wgs) with a snp array dataset [20], and then performed principle component analysis (pca) and population structure analysis over the combined datasets. pca was carried out using smartpca in eigensoft (version 4.2) [26]. population structure analysis was carried out using admixture (version 1.23) [27] and the results of the population structure analysis were plotted using clumpak […]

PMCID: 4578943

[…] populations the samples were derived from and how best to assign individual genotypes from these populations, we implemented a principal component analysis (pca) using the software smartpca [39] in eigensoft v4.2. pca was performed with default setting for both focal species groups. because missing data can bias inference of population structure if the missing data are structured [39] we used […]

PMCID: 4519554

[…] well-established procedures did not provide any positive results. although a high number of different explorative runs with different parameters were performed, tests based either on eigenstrat | eigensoft, plink, geneland, or spagedi did not provide any indication of a potential geographic variation of genetic heterogeneity in the study area. a brief summary of a representative extract […]

PMCID: 4519554

[…] would stand out over a much more admixed group, as it is expected for the native german population., our additional analysis with vastly cited multivariate methods, geneland, eigenstrat | eigensoft, plink, and spagedi, did not also submit indication of population stratification in the study area. this outcome is consistent with our expectations. these tools proved to be successful […]

PMCID: 4666579

[…] degree of genetic relatedness (estimated kinship coefficient >0.2) or with a discordant sex were removed. population outliers were identified by principal component analysis (pca) implemented in eigensoft, 16 we excluded markers with a call rate <99% or with significant deviation from hardy–weinberg equilibrium (p>1 × 10−3) and were left with 176 799 variants. a large number […]

EIGENSOFT institution(s)
Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA, USA


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