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indrajeetpatil
statsExpressions:Tidy Dataframes and Expressions with Statistical Details
Utilities for producing dataframes with rich details for the most common types of statistical approaches and tests: parametric, nonparametric, robust, and Bayesian t-test, one-way ANOVA, correlation analyses, contingency table analyses, and meta-analyses. The functions are pipe-friendly and provide a consistent syntax to work with tidy data. These dataframes additionally contain expressions with statistical details, and can be used in graphing packages. This package also forms the statistical processing backend for 'ggstatsplot'. References: Patil (2021) <doi:10.21105/joss.03236>.
Maintained by Indrajeet Patil. Last updated 1 months ago.
bayesian-inferencebayesian-statisticscontingency-tablecorrelationeffectsizemeta-analysisparametricrobustrobust-statisticsstatistical-detailsstatistical-teststidy
312 stars 10.92 score 146 scripts 2 dependents
bioc
dreamlet:Scalable differential expression analysis of single cell transcriptomics datasets with complex study designs
Recent advances in single cell/nucleus transcriptomic technology has enabled collection of cohort-scale datasets to study cell type specific gene expression differences associated disease state, stimulus, and genetic regulation. The scale of these data, complex study designs, and low read count per cell mean that characterizing cell type specific molecular mechanisms requires a user-frieldly, purpose-build analytical framework. We have developed the dreamlet package that applies a pseudobulk approach and fits a regression model for each gene and cell cluster to test differential expression across individuals associated with a trait of interest. Use of precision-weighted linear mixed models enables accounting for repeated measures study designs, high dimensional batch effects, and varying sequencing depth or observed cells per biosample.
Maintained by Gabriel Hoffman. Last updated 7 days ago.
rnaseqgeneexpressiondifferentialexpressionbatcheffectqualitycontrolregressiongenesetenrichmentgeneregulationepigeneticsfunctionalgenomicstranscriptomicsnormalizationsinglecellpreprocessingsequencingimmunooncologysoftwarecpp
12 stars 8.14 score 128 scripts
mrcieu
gwasglue2:GWAS summary data sources connected to analytical tools
Description: Many tools exist that use GWAS summary data for colocalisation, fine mapping, Mendelian randomization, visualisation, etc. This package is a conduit that connects R packages that can retrieve GWAS summary data to various tools for analysing those data.
Maintained by Rita Rasteiro. Last updated 1 years ago.
21 stars 5.69 score 11 scripts 2 dependents
