GENE ONTOLOGY using TOPPGENE - Free tutorial

This tutorial takes you through the use of ToppGene Suite for gene ontology analysis. This a one-stop web portal for gene list enrichment analysis and candidate gene prioritisation. Hints and tips on interpreting the output of gene ontology analysis are also given.
Toppgene can be found at toppgene.cchmc.org/
This tutorial is brought to you by Dr Katherine West in the College of Medical Veterinary and Life Sciences at the University of Glasgow, Scotland. This is part of series of tutorials on gene expression analysis.
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[@vigorianat]

Thank you so much for your tutorials. This one and the DAVID have been very useful

[@GenomicsGurus]

Glad you found them useful!

[@swongel]

Thank you so much for this instructive video.

[@GenomicsGurus]

You're very welcome!

[@johnnyflash2564]

Thanks for the tutorial, this helped me a lot!

[@GenomicsGurus]

Glad you found it useful :)

[@m.aissah8723]

Thank you for the tutorial. Please I am really interested in how to draw the bar charts to show the BP, CC and MF enrichments as well as the dot graph/chart to show the KEGG pathway as shown in published papers. Do you have an idea how to achieve that after obtaining those values, thank you.

[@hussainshaik4363]

Differentially expressed genes from one of the cluster in scRNA seq data can be used here?for enrichment analysis? please tell

[@Gabiibonfa]

Thanks for the video. Is it possible to use toppgene for genes differentially expressed in cattle? or just for humans?

[@GenomicsGurus]

If you convert your gene IDs to gene symbols, these are the same across mammalian species.

[@kouapatrick3838]

Hi, it cannot recognize the genes from wheat plant for eg. TraesCS3A02G320500, Do you have any tipps

[@GenomicsGurus]

I see you have resolved this problem now. Thanks.

[@abdou-samadkone6397]

Hello and thank you for the tutorial. However I have some difficulties to calculate the Fold2change and to adjust p-value. Can you give me a way to do this calculation? thanks

[@GenomicsGurus]

It depends what your starting data is. Normally you have a control and an experimental, with replicates. If it is fastq files of RNAseq data, then you will need to align the data to a genome (eg with Hisat2), generate transcripts (eg stringtie) and the calculate the log2fc and adjp using Deseq2. The publically available usegalaxy servers will let you do that for free. You shouldn't just calculate log2fc from FPKM values as the datasets need to be normalised - DEseq2 does that for you.

[@abdou-samadkone6397]

@@GenomicsGurus Thank you. I am actually using RNAseq data from TCGA. So I already have the gene names and the patient ID with their respective expression values. Can I have your email address if possible? I would really like to have some recommendations. I have been trying to figure out this analysis for a while. I am new to biostatistics.

[@GenomicsGurus]

[e-mail]

[@sadia2280-o4u]

i want to add top 25 gene ontology data in my thesis, how I can shorten the obtained results for graphical point of view? any help will be appreciated

[@GenomicsGurus]

You need to filter the gene sets. I often use p < 0.05 and FDR < 0.25, but it depends how many you want to work with. A useful way to plot them is to make a horizontal bar chart, one bar for each gene set, the x axis is NES, log10p or log10FDR, y axis cross at zero, and you make the value negative for genesets that are downregulated and positive for those that are upregulated.