Statistics and RNA-Seq

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Statistics and RNA-Seq

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Statistics and RNA-Seq

Keywords

FASTQ, Alignment, BAM, Differential-expression, Statistical-model, Exploratory-analysis

Authors

Benilton Carvalho @benilton

Description

This lecture and optional practical introduce the relevant statistical concepts along with its computational counterparts used on a common RNA-Seq data analysis workflow.

Aims

Make the participants aware of steps involved in the analysis of RNA-Seq data and comfortable with the statistical concepts used during such analyses, in a way that the attendees are able to critically question results and understand the rationale of statistical procedures used in high-throughput data analyses.

Prerequisites

None

Target audience

beginner, biologists, statisticians, mathematicians, computer scientists

Learning objectives

Make the attendee comfortable with the statistical nomenclature used in RNA-Seq data analysis;
Clarify misconceptions in the use of statistical models;
Elaborate the interpretation of parameters in statistical models;
Stimulate critical thinking and interpretation of high-throughput data modelling;
Conduct basic analysis of RNA-Seq data.

Materials

Slides in PPTX
Slides in PDF

Data

### Description
Count table for pilot study on rats comparing pilocarpine-induced animals to controls. The objective is to identify a list of genes that are candidates for differential expression when comparing the treated group to the controls.