Grad school help: Transcriptomics and Pathways Analysis

Question

[tugar360]

I have a GEO accession number from a longitudinal study following severe malaria patient who then became mild case. I want to compare their transcription by comparing the mild vs the severe condition, get the differentially expressed genes and perform a pathway analysis then write a journal-like paper from that. I wanted to use DAVID for that but I'm still struggling to get a hang of the analysis. I wouldn't mind using R but I'd wish to get an idea of how and where to start. Analysing the retrieved data from NCBI GEO and doing the pathway analysis. Anyone with an idea how they'd go about this? Thank you.

Answer 1

[curious]

You might be able to so some stuff with GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/) depending on the dataset. if its microarray data, you could just download the data and go though the analysis from scratch. A lot of it will be R based (if not all of it), there are tons of tutorials out there. If it is RNA-seq, the learning curve is going to be a lot steeper and you will probably need to string together multiple open source tools. I can give you some good links if its RNA-seq.

[WouterDeCoster]

If it is RNA-seq, the learning curve is going to be a lot steeper

I'm not sure if I agree with that part of your answer. I don't think it's more difficult, and also for RNA-seq there are excellent workflows such as this one from bioconductor.

[lshepard]

I agree with you. I would consider bulk RNA-seq probably the best NGS application to start with as the resources are most abundant and matured (compared to epigenomics for example). Now if it is scRNA-seq, then it gets trickier based on the single-cell method, but still "doable" :)