News: Course in Berlin- Genomics with R and Bioconductor - September 16-20
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11 days ago by
info0
info0 wrote:

Dear all,

we still have a few places on our course " Genomics with R and Bioconductor"


Where: Free University (FU) Berlin (Germany)


When: 16-20 September 2019


Instructor: Dr. Ludwig Geistlinger - CUNY Graduate School of Public Health and Health Policy, New York (USA)


Registration Deadline: 20th August 2019


Course:

This course will provide biologists and bioinformaticians with practical statistical analysis skills to perform rigorous analysis of high-throughput genomic data. The course assumes basic familiarity with genomics and with R programming, but does not assume prior statistical training. It covers the statistical concepts necessary to design experiments and analyze high-throughput data generated by next-generation sequencing, including: exploratory data analysis, principal components analysis, clustering, differential expression, and gene set analysis.


Programme:

Session 1 – Introduction

Monday - 09:30 to 17:30

Lecture 1: Data distributions

random variables distributions population and samples

Hands-On 1: Introduction to R

Lecture 2: Creating high-quality graphics in R

Visualizing data in 1D, 2D & more than two dimensions Heatmaps Data transformations

Hands-On 2: Graphics with base R and ggplot2

Session 2 – Hypothesis testing


Tuesday - 09:30 to 17:30

Lecture 1: Hypothesis testing theory

type I and II error and power multiple hypothesis testing: false discovery rate, familywise error rate exploratory data analysis (EDA)

Hands-On 1: Standard tests & EDA

Lecture 2: Hypothesis testing in practice

hypothesis tests for categorical variables (chi-square, Fisher's exact) Monte Carlo simulation Permutation tests

Hands-On 2: Permutation tests

Session 3 - Bioconductor


Wednesday – Classes from 09:30 to 17:30

Lecture 1: Introduction to Bioconductor

Incorporating Bioconductor in your data analysis ExpressionSet / SummarizedExperiment Annotation resources

Hands-On 1: Leveraging Bioconductor annotation resources

Lecture 2: Genomic intervals

Introduction to genomic region algebra Basic operations: construction, intra- and inter-region operations Finding overlaps

Hands-On 2: Solving common bioinformatic challenges with GenomicRanges

Session 4 - Next-generation sequencing data


Thursday - 09:30 to 17:30

Lecture 1: High-throughput count data

Characteristics of count data Exploring count data Modeling count data

Hands-On 1: Analyzing next-generation sequencing data

Lecture 2: Clustering and Principal Components Analysis

Measures of similarity Hierarchical clustering Dimension reduction Principal components analysis (PCA)

Hands-On 2: Clustering & PCA

Session 5 - Differential expression and gene set analysis


Friday - 09:30 to 17:30

Lecture 1 - Differential expression analysis

Normalization Experimental designs Generalized linear models

Lab 1: Performing differential expression analysis with DESeq2

Lecture 2 - Gene set analysis

A primer on terminology, existing methods & statistical theory GO/KEGG overrepresentation analysis Functional class scoring & permutation testing Network-based enrichment analysis

Lab 2: Performing gene set enrichment analysis with the EnrichmentBrowser


For the full list of our courses and Workshops, please see: https://www.physalia-courses.org/courses-workshops


Should you have any questions, please feel free to contact us


Thanks and best regards,

Carlo Pecoraro, Ph.D

Physalia-courses DIRECTOR

info@physalia-courses.org

http://www.physalia-courses.org/

Twitter: @physacourses

mobile: +49 17645230846

https://groups.google.com/forum/#!forum/physalia-courses

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