Tools for Analyzing Factorial Experiments

The Entire Transcript from the Office in Tidy Format

Schloss Lab Tools for Reproducible Microbiome Research

Standardized Climate Indices Such as SPI, SRI or SPEI

Single-Cell Integrator and Batch Effect Remover

Colour Palettes Based on the Scientific Colour-Maps

Tools Developed by the NCEAS Scientific Computing Support Team

Data Sets from Design and Analysis of Experiments and
Observational Studies using R
R package scidesignR version 1.0.0

Highly Customizable 'rmarkdown' Theme for Scientific Reporting

Visualize 'Reproducibility' and 'Replicability' in a Comparison
of Scientific Studies
R package scifigure version 0.2

Extra Recipes Steps for Dealing with Omics Data

A Semi-Supervised Category Identification and Assignment Tool

Interpretation of Heterogeneous Single-Cell Gene Expression Data

Scientific Graphing Functions for Factorial Designs

Summarize Data for Scientific Publication

Upgraded 'Rmarkdown' Themes for Scientific Writing

Single-Cell Imputation using Subspace Regression

Maximum-Likelihood Perfect Phylogeny Inference at Scale

Provides Some Useful Functions for Making Statistical Tables

Inferring Functional Gene Co-Expression Networks from Single
Cell Data
R package scLink version 1.0.1

R Toolbox for Unsupervised Spectral Clustering

Fitting Discrete Distribution Models to Count Data

Aligning Ontology Annotation Across Single Cell Datasets with
'scOntoMatch'

Spectral Clustering-Based Method for Identifying B Cell Clones

Score Projection Between in 'Vivo' and in 'Vitro' Datasets

A Package to Score Behavioral Questionnaires

R package scorecardModelUtils version 0.0.1.0

Score Test Integrated with Empirical Bayes for Association Study

Peak Functions for Peak Detection in Univariate Time Series

Implementation of SCORE, SCORE+ and Mixed-SCORE

A Collection of Scoring Functions for Assessing Point Forecasts
R package scoringfunctions version 0.0.6

Scoring Rules for Parametric and Simulated Distribution
Forecasts

Utilities for Scoring and Assessing Predictions

Semi-Supervised Calibration of Risk with Noisy Event Times