lfa - Logistic Factor Analysis for Categorical Data
Logistic Factor Analysis is a method for a PCA analogue on Binomial data via estimation of latent structure in the natural parameter. The main method estimates genetic population structure from genotype data. There are also methods for estimating individual-specific allele frequencies using the population structure. Lastly, a structured Hardy-Weinberg equilibrium (HWE) test is developed, which quantifies the goodness of fit of the genotype data to the estimated population structure, via the estimated individual-specific allele frequencies (all of which generalizes traditional HWE tests).
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snpdimensionreductionprincipalcomponentregressionopenblas
7.23 score 16 stars 1 dependents 59 scripts 697 downloads
popkin - Estimate Kinship and FST under Arbitrary Population Structure
Provides functions to estimate the kinship matrix of individuals from a large set of biallelic SNPs, and extract inbreeding coefficients and the generalized FST (Wright's fixation index). Method described in Ochoa and Storey (2021) <doi:10.1371/journal.pgen.1009241>.
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6.64 score 21 stars 104 scripts 258 downloadssubSeq - Subsampling of high-throughput sequencing count data
Subsampling of high throughput sequencing count data for use in experiment design and analysis.
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immunooncologysequencingtranscriptionrnaseqgeneexpressiondifferentialexpression
6.56 score 20 stars 30 scripts 406 downloadsgcatest - Genotype Conditional Association TEST
GCAT is an association test for genome wide association studies that controls for population structure under a general class of trait models. This test conditions on the trait, which makes it immune to confounding by unmodeled environmental factors. Population structure is modeled via logistic factors, which are estimated using the `lfa` package.
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snpdimensionreductionprincipalcomponentgenomewideassociation
5.43 score 6 stars 5 scripts 345 downloads
