cmpe492-Transcriptomics_Analysis

This is my Bachelor Degree Senior Project.

I applied Data Quantification, Differential Expression and Functional analysis to analyze transcriptomics data of mus musculus over a diet data.

Please look into the project poster for more information.

By FarukOzderim

Data:

https://www.ebi.ac.uk/ena/data/view/PRJNA292382

This data has 3 diets + 1 control diet over musmusculus.

It is a study with name "Omega-3 fatty acids partially revert the metabolic gene expression profile induced by long-term calorie restriction".

Dataset contains single raw RNA-sequences from liver and muscle.

Run

You can run download dataset and data quantification steps with

bash scriptForAll.sh

be careful that this will download 40gb of data and run ~8 hours after download on a standard pc.

After this step for differential expression and functional analysis You can move kallisto outputs into a data directory, and use metadataLike.txt and differentiate liver and muscle data like in

-results/deseq2 results/muscle/data

-results/deseq2 results/liver/data

-results/deseq2 results/muscle/metadata.txt

-results/deseq2 results/liver/metadata.txt

and run script1,2,3,4.r one by one with R in that directory. This will apply deseq2 and functional analysis.

Results

You can find my kallisto, differential expression, functional analysis results are under results segment.

Reference:

I used this workshop as a reference for my work:

https://github.com/sysmedicine/phd2020