Showing 5 of total 5 results (show query)
bioc
MAST:Model-based Analysis of Single Cell Transcriptomics
Methods and models for handling zero-inflated single cell assay data.
Maintained by Andrew McDavid. Last updated 5 months ago.
geneexpressiondifferentialexpressiongenesetenrichmentrnaseqtranscriptomicssinglecell
232 stars 11.28 score 1.8k scripts 5 dependents
american-institutes-for-research
EdSurvey:Analysis of NCES Education Survey and Assessment Data
Read in and analyze functions for education survey and assessment data from the National Center for Education Statistics (NCES) <https://nces.ed.gov/>, including National Assessment of Educational Progress (NAEP) data <https://nces.ed.gov/nationsreportcard/> and data from the International Assessment Database: Organisation for Economic Co-operation and Development (OECD) <https://www.oecd.org/en/about/directorates/directorate-for-education-and-skills.html>, including Programme for International Student Assessment (PISA), Teaching and Learning International Survey (TALIS), Programme for the International Assessment of Adult Competencies (PIAAC), and International Association for the Evaluation of Educational Achievement (IEA) <https://www.iea.nl/>, including Trends in International Mathematics and Science Study (TIMSS), TIMSS Advanced, Progress in International Reading Literacy Study (PIRLS), International Civic and Citizenship Study (ICCS), International Computer and Information Literacy Study (ICILS), and Civic Education Study (CivEd).
Maintained by Paul Bailey. Last updated 1 months ago.
10 stars 7.86 score 139 scripts 1 dependentsbioc
DSS:Dispersion shrinkage for sequencing data
DSS is an R library performing differntial analysis for count-based sequencing data. It detectes differentially expressed genes (DEGs) from RNA-seq, and differentially methylated loci or regions (DML/DMRs) from bisulfite sequencing (BS-seq). The core of DSS is a new dispersion shrinkage method for estimating the dispersion parameter from Gamma-Poisson or Beta-Binomial distributions.
Maintained by Hao Wu. Last updated 5 months ago.
sequencingrnaseqdnamethylationgeneexpressiondifferentialexpressiondifferentialmethylation
7.02 score 248 scripts 5 dependentsamerican-institutes-for-research
WeMix:Weighted Mixed-Effects Models Using Multilevel Pseudo Maximum Likelihood Estimation
Run mixed-effects models that include weights at every level. The WeMix package fits a weighted mixed model, also known as a multilevel, mixed, or hierarchical linear model (HLM). The weights could be inverse selection probabilities, such as those developed for an education survey where schools are sampled probabilistically, and then students inside of those schools are sampled probabilistically. Although mixed-effects models are already available in R, WeMix is unique in implementing methods for mixed models using weights at multiple levels. Both linear and logit models are supported. Models may have up to three levels. Random effects are estimated using the PIRLS algorithm from 'lme4pureR' (Walker and Bates (2013) <https://github.com/lme4/lme4pureR>).
Maintained by Paul Bailey. Last updated 5 months ago.
10 stars 6.30 score 33 scripts 2 dependents
