Training – Introduction to data analysis

Course description :
This five weeks graduate level course will give participants basic skills and hands-on training in biostatistics. It will cover all the steps of an analysis workflow : design, collection, curation, hypothesis testing and data mining. The course can be divided into four different topics whose practice is mandatory for those seeking to implement a relevant analysis workflow. Thus, it will cover basics and practice in unix, text file management, R and biostatistics. We will focus on the topics useful for scientists working in a wet lab: experimental design, hypothesis testing, production of good scientific plots.



Course schedule :
The course will take place from January 16th to February 17th 2017, with two-hour lectures every day.
Two sessions are provided:

• session 1 from 9 AM to 11 AM
• session 2 from 11 AM to 1 PM.

Course location :
Lectures will take place in Amphi Jacques Monod. Please note On Fridays, lectures will take place in the Bâtiment François Jacob, room 28-01-01A. On February 10th and 17th they will take place in the afternoon, from 1:30 to 3:30 for session 1 and from 3:30 to 5:30 for session 2.

In order to follow the course all students need to bring their own laptop. Please check that your computer meets the minimum requirements listed below. PC – Windows Based : Intel i3 / Windows 7/ 4Go RAM / 256 Go HD, Apple Macintosh : mid-2010 mac book /OSX 10.10/ 4Go RAM/ 256 Go HD Teachers will be available on Thursday January 12th from 9 to 12 in the Hub meeting room (26-06-06 A) to help you if you have doubts about the configuration of your machine or if you need help to install the necessary software.

• On PC – windows based you will need to install putty: http://www.putty.org/
• You all need to install R version 3.3.2 : https://cran.univ-paris1.fr/ and RStudio : https://www.rstudio.com/products/rstudio/ (RStudio desktop, free version)

-> Programme -> Course documents

• Session 1 – Unix (Week 1)
• Session 2 – Unix2 (Week 2)
• Session 3 – R
• Session 4 – Statistics
• Session 5 – Experimental Design
• Session 6 – Estimation & Tests
• Session 7 – Regression Lineaire
• Session 8 – PCA
• Session 9 – Clustering
• Session 10 – Final Project

-> Evaluation

Programme

Introduction

Session 1: Unix

Session 2: Unix2

Day 1


Day 2


Day 3


Day 4


Day 5


Day 5 – end

Session 3 : R

Session 4 : Statistics

Session 5 : Experimental Design

Files: BransfordJohnsonExperiment_solution.pdf

Session 6 : Estimation & Tests

Files: Examples.R Internal.R lungA.csv Exercices.R

Session 7 : Regression Lineaire

Files: TP lungA.csv lungB.csv lungC.csv

Session 8 : PCA

Files: dat_pca_clus_counts.rda MultivariateAnalysis.Rmd

Session 9 : Clustering

Session 10 : Final Project

Files: IntroRmarkdown.pdf toStart.Rmd project.Rmd famuss.bib