Data Analysis, Bioinformatics

Perform a functional enrichment analysis on a set of differentially expressed S. cerevisiae genes, between two conditions or between two different strains. To do that you will need to identify a suitable dataset consisting of libraries of paired-end RNA-seq reads (fastq files), one for each condition/strain. How will you find a dataset? You will either 1) start with a literature search, find a relevant paper and then download the paper's data, or 2) start with a search in EBI-ENA or NCBI-SRA or GEO, find a suitable dataset and then track down the study from which it came. In both cases, you should know what the study is, what its goal and motivation was and what conditions/strains are being compared and why. Once you've found your data, in the beginning, you should have two pairs of fastq files: [login to view URL], [login to view URL], [login to view URL], [login to view URL] (R1 and R2 are usually used in the file names to denote the two read pairs) You will upload these to Galaxy in order to perform your analysis. Make sure to specify the genome assembly as sacCer3 . You will also need the Saccharomyces cerevisiae gene annotation file (gtf/gff3 format) that we have already used. If you don't already have it, you should download it and "adapt" its name again. We've already discussed this in class. The main steps of your analysis should be : Quality control of the read libraries. If needed, preprocessing the reads to improve their overall quality. Mapping of the reads onto the S. cerevisiae genome. Quantification of gene expression in both conditions Producing a table that you can use with a tool to do the differential gene expression analysis, e.g. DESeq2 Performing the analysis and visualizing the results, preferably as a volcano plot. If available, a quick comparison of your results to the paper's results. For example, did you find the same number of differentially expressed genes? Out of the top 10 most differentially expressed, do you find the same ones as the paper? Gene Ontology (GO) term functional enrichment using the list of differentially expressed genes. You can do this in Galaxy or in another website such as [login to view URL] . If possible, visualize the results. You can read about GO terms here for example [login to view URL] . Write an explanatory very simple paper on (bullet points) all the steps followed, the tools used, how, for what for, and why they were used. Include the name of the study and the fastq files. Also, answer to the questions above.