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regenie

regenie is a C++ program for whole genome regression modelling of large genome-wide association studies.

regexcite

PACKAGE EXISTS FOR DEMONSTRATION PURPOSES ONLY! Make Regular Expressions More Exciting

regressions

A Python package that implements various regression algorithms, including Partial Least Squares and Principal Components Regression

riskscore

Scoring risk prediction markers and risk prediction models

rlang

Low-level API for programming with R

rna-seq

rnaseq

GLBio RNASeq workshop

rss

Regression with Summary Statistics.

rvtests

Rare variant test software for next generation sequencing data

s-ldxr

Stratified squared trans-ethnic genetic correlation

saige

sarek

Detect germline or somatic variants from normal or tumour/normal whole-genome sequencing data

scanpy

Single-Cell Analysis in Python. Scales to >1M cells.

scientific-python-lectures

Lectures on scientific computing with python, as IPython notebooks.

scipy

Scipy library main repository

scrna.seq.course

Analysis of single cell RNA-seq data course

sed_awk

sed_awk

sequencingpipeline

Analytical framework of whole genome sequencing for genetic studies of human diseases

seurat

R toolkit for single cell genomics

seurat-object

shiny-examples

shinygpas

ShinyGPAS

signac

R toolkit for the analysis of single-cell chromatin data

simplestatistics

:game_die: Simple statistical functions implemented in readable Python.

simulation-for-data-science-with-r

Simulation for Data Science with R by Packt Publishing

sincera

An R implementation of the SINCERA pipeline for single cell RNA-seq profiling analysis

singlecellexperiment

Clone of the Bioconductor repository for the SingleCellExperiment package, see https://bioconductor.org/packages/devel/bioc/html/SingleCellExperiment.html for the official development version.

skimr

A frictionless, pipeable approach to dealing with summary statistics

slideseq-tools

Tools for analyzing Slide-seq data

smtpred

SMTpred is a program which combines SNP effects or individual scores from multiple traits according to their sample size, SNP-heritability (h2) and genetic correlation (rG), in order to create more accurate polygenic risk scores.