Ghent University - Center for Statistics (@CenterForStatistics-UGent)
Guthub

CenterForStatistics-UGent

Twitter logo Share LinkedIn logo Share Facebook logo Share
  • Stars
    star
    63
  • Global Org. Rank 71,171 (Top 23 %)
  • Registered about 7 years ago
  • Most used languages
    R
         93.8 %
    HTML
         6.3 %
  • Location 🇧🇪 Belgium
  • Country Total Rank 1,364
  • Country Ranking
    R
         18
    HTML
         1,233

Top repositories

1

RCM

A model-based visualization method for microbiome data
R
16
star
2

SPsimSeq

Semi-parametric simulation of bulk and single cell RNA-seq data
R
10
star
3

xnet

xnet: a package for supervised network prediction
R
10
star
4

pim

R package for probabilistic index models
R
9
star
5

digipcr

digital PCR processing tools in R
R
2
star
6

unifiedWMWqPCR

Bioconductor package of unified Wilcoxon-Mann-Whitney test for qPCR
R
2
star
7

reconsi

Resample collapsed null distributions for simultaneous inference under dependence
R
2
star
8

Additional-File-6

Additional File 6
2
star
9

PIMseq

repository for the package PIMseq
R
2
star
10

NTCPmodels

Package implementing NTCP models
R
1
star
11

dPowerCalcR

Power calculations for digital PCR
R
1
star
12

smooth2

Additional Material for the book Smooth Tests of Goodness of Fit Using R
HTML
1
star
13

PIMseq-paper

This repository contains codes and materials used in the PIMseq paper.
R
1
star
14

combi

Explorative integration of genomics data through multiplots
R
1
star
15

UCNR

Simulation code, case studies and tutorials for the Unified Censored Normal Regression model for qPCR analysis.
R
1
star
16

EBayesH

The R package EBayesH
R
1
star
17

mountainr

Bringing R and alpine to Docker
1
star
18

AppDGE

Shiny application to evaluate the performance of several differential gene expression tools for RNA-seq data.
R
1
star
19

Additional-File-2

This github repository includes R software codes used for a study on the evaluation of 14 differential gene expression methods for RNA-sequencing data (particularly for mRNA and lncRNA). The study has three main modules: (1) comparing selected normalization methods, (2) concordance analysis of 14 DGE analysis tools using 6 publicly accessible real RNA-seq data, and (3) non-parametric simulation study to evaluate tools with respect to false discovery rate and sensitivity.
1
star