StoreyLab/superSeq

Stars
13
Rank 1,484,197 (Top 30 %)
Language
R
License
MIT License
Created about 5 years ago
Updated about 5 years ago

StoreyLab/superSeq

StoreyLab

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Assessing the increase in power from increasing read depth in a given RNA-Seq study

qvalue

R package to estimate q-values and false discovery rate quantities.

biobroom

Tidy up computational biology objects

reading

A collection of papers and books that Storey Lab members should read and others may find useful

terastructure

TeraStructure is a new algorithm to fit Bayesian models of genetic variation in human populations on tera-sample-sized data sets (10^12 observed genotypes, i.e., 1M individuals at 1M SNPs). This package provides a scalable, multi-threaded C++ implementation that can be run on a single computer.

edge

R package for identifying differentially expressed genes from genome-wide gene expression profiling studies.

subSeq

Subsampling of high-throughput sequencing count data

popkin

R package to estimate kinship and FST from SNP data

lfa

logistic factor analysis

bnpsd

R package to model and simulate admixed populations

alstructure

An R package that implements the ALStructure algorithm for estimating the admixture model of genetic population structure

gcatest

genotype conditional association test

fFDR

Functional FDR package

gcat

This package has been renamed gcatest: https://github.com/StoreyLab/gcatest

sparta

Dividing RNA-Seq reads based on their ancestral genotype

human-differentiation-manuscript

Details on the data analysis for "New kinship and F_ST estimates reveal higher levels of differentiation in the global human population" by Ochoa and Storey

superSeq-manuscript

ALStructure-manuscript

Data and code utilized in "A likelihood-free estimator of population structure bridging admixture models and principal components analysis", by Cabreros and Storey

factorial-MA-RS

Supplementary Materials for the manuscript "A nested parallel experiment demonstrates differences in intensity-dependence between RNA-seq and microarrays" by Robinson, Wang, and Storey