Witold Wolski's repositories
MLwithCaret_AS3
Predicting wine quality with ML
demo-crosstalk
A short lesson on using crosstalk for adding interactivity to an R Markdown document
GettingStartedWithJulialang
Getting started with Julialang
GradedProjectMas6003MixedModels
Graded Project Mas6003 MixedModels 2017
grpc-go-course
Companion Repository for my gRPC Golang course
LFQb
Benchmarking label-free quantification (LFQ) in bottom-up proteomics by DIA-LC-MS and DIA-NN
MAS6006Proj1
Sheffield university MAS6006 Project1 shiny app
MAS6006Proj2
Building emulators using Gaussian processes
MSstatsPTM_simulations
Repository containing the simulation data and analysis used to evaluate MSstatsPTM
sigora
Pathway Analysis is statistically linking observations on the molecular level to biological processes or pathways on the systems(i.e., organism, organ, tissue, cell) level. Traditionally, pathway analysis methods regard pathways as collections of single genes and treat all genes in a pathway as equally informative. However, this can lead to identifying spurious pathways as statistically significant since components are often shared amongst pathways. SIGORA seeks to avoid this pitfall by focusing on genes or gene pairs that are (as a combination) specific to a single pathway. In relying on such pathway gene-pair signatures (Pathway-GPS), SIGORA inherently uses the status of other genes in the experimental context to identify the most relevant pathways. The current version allows for pathway analysis of human and mouse datasets. In addition, it contains pre-computed Pathway-GPS data for pathways in the KEGG and Reactome pathway repositories and mechanisms for extracting GPS for user-supplied repositories.
Statistical_Rethinking_with_brms_ggplot2_and_the_tidyverse
The bookdown version lives here: https://bookdown.org/connect/#/apps/1850/access
wolski.github.io
my user page