Is there any way to check that i have obtained the correct set of differently expressed genes?can i come to know about differently expressed genes by just looking at normalized data? i apologize if some one find my question naive.
The short answer is no. The reason we are doing DE in the first place is to find those genes :-)
That said:
If you are using a well establised, well tested (benchmarked) tool - and your p-value distribution looks good (for more information on this take a look at this blog) there is a good chance you have a good set.
Please note that with datasets like TCGA breast cancer (or single cell data) you have so many samples that you have the power to detect very small changes. Therefore I would recomend to also use a cutoff on effect size (in this case the absolute log2FC). This can even be done in the statistical test (testing abs(log2FC) > x instead of the default abs(log2FC) > 0) in a number of tools.
Lastly you can as Grant suggest do validations - this can both be experimental such as qPCR or by analysing other similar datasets.
It is unclear what you have done, which data you have and what you are looking for. Please elaborate.
i have htseq-count TCGA breast cancer data and i have done TMM normalization. basically i want to use machine learning algorithms for my analysis
You can check by qPCR.