Disponeblaj kursoj

Session in French – Confidence intervals and Hypothesis testing: a little bit of theory and practice with R

6/11/2023 – Full day

8/11/2023 – Afternoon

9/11/2023 – Afternoon


The basics of linear models with examples in R

An introduction to multivariate statistical methods with examples in R

Session in French – Confidence intervals and Hypothesis testing: a little bit of theory and practice with R

6/11/2023 – Full day

8/11/2023 – Afternoon

9/11/2023 – Afternoon


The basics of linear models with examples in R

An introduction to multivariate statistical methods with examples in R

Objectives: knowing how to

  • Navigate the filesystem, identify files by their path, create, move, rename, delete files and directories

  • Extract information from text files

Objectives:

  • Understand biological information available online

  • Understand sequence comparisons using local alignment

  • Find information about unknown sequences, using online tools

This course is intended to provide the students with the prerequisites needed to be able to follow the courses of the Bioinformatics track dedicated to the analysis of NGS data (B4, B5, B6, B7, B8, B9, B10, B11).


The course has three main parts:
1 - Main UNIX commands
2 - Main R commands / getting acquainted with R scripts and Rstudio
3 - Main Galaxy commands

Objectives:

  • Understand the key concepts underlying the quantification and comparison of OMIC datasets 

  • Perform the initial steps of most HTS data analysis

Objectives:

  • Design a successful transcriptomics experiment

  • How to get differential expressed genes from raw data

Objectives:

  • Learn the key steps to obtain genetic reliable variants from raw sequencing reads

  • First applications : use filtered files of variants to perform basic analyses

Objectives:

  • Getting exposed to important applications in the analysis of genetic data, genomewide

  • Analysing genomic data with R and other popular software

Objective:

Be able to analyze ChIP-seq data from sequencing reads to functional interpretation

Objectives:

  • Get acquainted with the key concepts of scRNAseq raw data analysis, quantification, functional characterization and visualization.

Objectives

  • Understand the key concepts of functional analysis

  • Perform functional analysis on RNA-Seq data on a simple design using R tools

Objectives:

  • understand more complex but useful options and commands

  • learn regular expressions and few commands using them,

  • everything needed to create your firsts own scripts.

Date: Tuesday, January the 8th, 14:00am to 17:30pm.

Where: room 5, building 6, under the canteen.

Teacher: Stéphane Rigaud

Assistant teacher: Marie Anselmet and Gaëlle Letort

This course provides a comprehensive introduction to QuPath, an open-source software platform designed for bioimage analysis of large 2D images, from digital-pathology to large slide scan. Participants will learn the basic of the software, how to navigate and uses QuPath for analyzing images, object annotations, and segmentation. 

The course covers essential topics such as project creation, annotation, tissue and nuclei segmentation, and quantification, enabling users to perform quantitative analysis of tissue samples. Using both QuPath integrated tools and State of the Art Deep-Learning extensions.

Course materials:

  • A laptop along with a mouse and a power connector
  • Download and install QuPath: https://qupath.github.io/
  • Download the following datasets:
    1. QuPath Aperio CMU-1.svs
    2. QuPath Hamamatsu OS-2.ndpi
    3. Thierry Pecot dataset

Additional material: QuPath Documentation

This course is an introductory course on utilizing Python for the analysis of biological images. While Fiji is great for quick and user-friendly image processing workflows, Python offers unparalleled flexibility and access to advanced tools like deep learning-based segmentation, batch processing, and custom analysis pipelines tailored to your research needs. The course is meant for students who have no or little experience with Python and basic knowledge in bio-image analysis (for example from following IA1).

Using TrackMate for analysis of time-lapse microscopy movies.

This course is aimed at beginners in bioimage analysis, that wants to learn how to analyse time-lapse movies. Such movies can follow the movement of cells, in 2D or 3D over time, or the motility of organelles and large objects. They offer unique insight into the dynamics of biology objects, on the evolution of their morphology and of molecular processes, imaged via transmission light or fluorescence microscopy. 

This half a day course includes a brief theoretical introduction about tracking algorithms, and is followed by a hands-on tutorial. For the tutorial we will use TrackMate (https://imagej.net/plugins/trackmate/), which is a somewhat popular Fiji plugin for tracking, developed in the Image Analysis Hub.

What do you need to attend:

For more information contact Jean-Yves.

Tutorial on how to use QuPath for large fixed images analysis and in particular histopathological images.

Cours d'Introduction à la programmation en R

Cours d'Introduction à la programmation en R

Formation nationale centre antirabique