Transcriptomics Data Analysis for Group Project
Content
Transcriptomics 1: 👋 Hello data!
This week you will meet your data. There are four datasets, one for each project in this strand. The independent study will concisely cover how each of these four data sets were generated and how they have been processed before being given to you. It will also give an overview of the analysis we will carry out over three workshops. In the workshop, you will learn what steps to take to get a good understanding of transciptomics data before you consider any statistical analysis. This is an often overlooked, but very valuable and informative, part of any data pipeline. It will give you the understanding of the data and R data structures that you will need to code and trouble-shoot code. It will also allow you to spot failed or problematic samples and will inform your decisions on quality control. At the end of this workshop and the following independent study you will have performed quality control by filtering out uninformative genes and samples, and saved this filtered data for use in the next workshop. You will also have a script that you can use to repeat this process on other datasets.
Transcriptomics 2: Statistical Analysis
This week we cover differential expression analysis on your quality controlled data. The independent study will allow you to check you have what you should have following the Transcriptomics 1: Hello Data workshop and Consolidation study. It then summarises the concepts and methods used to carry out differential expression analysis in workshop. In the workshop, you will perform the differential expression and learn how to compuationally annotate your genes with more information from the databases. This will include the Gene Ontology (GO) terms that describe the biological processes, molecular functions and cellular components that the gene is involved in. At the end of this workshop and the following independent study you will have files containing the genes which are differentially expressed, along with the statistical information, summary information and annotation. You will be able to consider which genes you want to investigates with your Project director and have what you need for the next workshop. You will also have a script that you can use to repeat this process on other datasets.
Transcriptomics 3: Visualising and Interpreting
This week you will learn some how to do some common data visualisations for transcriptomic data. You will conduct and present a Principal Component Analysis (PCA) and a Volcano plot. We will also conduct a GO enrichment analysis. The independent study will allow you to check you have what you should have following the Transcriptomics 2: Statistical Analysis workshop and Consolidation study. At the end of this workshop and the following independent study you will at least two figures suitable for including in your report, along with an understanding of the results you can report on. You will also have a script that you can use to repeat this process on other datasets.
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