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Proteomics data analysis with QFeatures: Lesson dessign

This page documents the design process and motivation of this lesson material.

Lesson Title: An Introduction to Proteomics data analysis with QFeatures

Target audience

The main audience of this carpentry lesson is researches that are familiar with proteomics data analysis but have little to no experience with QFeatures, a Bioconductore package for analysing quantitative features for mass spectrometry data. In addition, we expect them to be familiar with R. We do not expect them to be familiar with SummarizedExperiment objects, and aim that the learners will learn about them in this tutorial.

Learner Profiles

Chloe from proteomics facility

Notes

They may not see why they could benefict from using these structures.
Probably they are intimidated to use Bioconductor objects.
They have no idea how step the learning curve will be.
Want to learn using a real life example.

Required Pre-Knowledge

R – Previous programming experience in R is required
Basic Proteomics data analysis is required –

Learning objectives

Overview

After following this lesson, learners will be able to:

Build QFeatures data structure

Extract components of a QFeatures data structure

Use functions supported by QFeatures package to process quantitative proteomics data

The following offers more details to each learning objective based on Bloom’s Taxonomy. For hints on how to use this approach, see lesson 15 of the instructor training

Identify the anatomy of proteomics data

This includes knowledge of the dataset we will use in this lesson

After this module, learners can …

Inspect the anatomy of peptide.txt file use in this lesson
Select the quantitative information and the metadata information used in this proteomics data analysis

Identify the anatomy of SummarizedExperiment and QFeatures objects

This includes knowledge of these types of objects

After this module, learners can …

Recognize the anatomy of SummarizedExperiment and QFeatures objects
Execute common operations on SummarizedExperiment and QFeatures objects

Read Maxquant output as QFeatures object

This includes knowledge of functions used to import txt file into QFeatures objects

After this module, learners can …

Import txt files into QFeatures S4 objects

Manipulate QFeatures object

This includes

After this module, learners can …

Perform downstream proteomics data analysis with Qfeatures

This includes

After this module, learners can …

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