Have a look at https://www.youtube.com/watch?v=JQ24T9fpXvg and https://www.youtube.com/watch?v=YUxVv6pkxD4
Dear Sx Wang
I'm not sure what you want exactly. Are you after differential gene expression? In the case of GEO, you can simply use GEO2R to identify DEGs in most datasets. Let me know if you need anything else. Thanks
Dear Sx Wang
These articles might be useful, have a look:
1. https://www.frontiersin.org/articles/10.3389/fonc.2020.573295/full
2. https://www.bioconductor.org/packages/devel/bioc/vignettes/TCGAbiolinks/inst/doc/analysis.html
3. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6345189/
4. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7027371/
5. https://www.por-journal.com/articles/10.3389/pore.2021.1609868/full
6. https://www.mdpi.com/2075-4418/10/2/66/htm
7. Article Identification of four genes and biological characteristics ...
Kind Regards
Qamar Ul Islam
Dear Sx Wang
Even though I am not sure if I understand what you mean, here is my answer. As I understand it, you have a gene of interest and its expression in breast cancer samples and normal tissue samples. A fold change can be calculated by dividing the expressions, so the gene expression difference could be found that way. In this case, it represents breast cancer expression divided by normal tissue expression. You can then use log to obtain fold change as well. So that's how differential expression is calculated. Does that answer your question?
Sx Wang In that case, may I suggest for TCGA, use this webtool GEPIA 2.0, wherein you can compare the expression of gene(s) of interest between Tumor and Normal, and across different Tumor stages. (http://gepia2.cancer-pku.cn/#index ) However, if you're up to the task, I'm sure datasets in GEO have this function called GEO2R, wherein they give you basic code to load the dataset, extract gene expression data, and run DGE analysis. If you have a sample dataset, I can guide you further.
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