I got a list of few hundred genes after runnis standard Deseq2 analysis. I am wondering how to list a few genes to focus on based pathway enrichment and other analysis. I am also looking for suitable tools for that.
It depends on what your study's aims and hypotheses are.
If you are attempting to define a molecular predictor of a certain condition, then throw the DEGs into a linear or logistic regression model and perform stepwise regression in order to pick the best predictors (followed by suitable cross validation on the final model). As your list seems reasonably large, you can also try lasso penalized regression in order to pick best predictors. When you get the best predictors, perform ROC analysis and come up with an AUC. You can also derive sensitivity/specificity and precision/accuracy.
I would not form my conclusions based solely on gene enrichment or pathway analysis. They would just form part of it and give me an idea of what the data may be telling me.
You can use Enrichr on up and down regulated genes separately to find enriched GO terms or pathways and many more gene sets.
To visualise, to make it simple, I would just plot a heat map of differential genes and highlight important gene names, enriched in GO or pathway analysis. You can also highlight gene names in volcano plot.
TBH, I am happy to help the OP but the OP should also search for similar queries in biostars and google as it will bring up multiple hits in SEO and not make a redundant question. I am pretty sure this question has been asked plenty of times and there are amazing tutorials online as well that gives a functional flavor of what to do post DE analysis. A little search will help better.
You can do pathway enrichment using GSEA http://software.broadinstitute.org/gsea/doc/GSEAUserGuideFrame.html
GSEA pre-ranked requires complete list of genes with fold changes. you can chose signatures of interest and see if they are enriched.
Have a look at Protovis to get some ideas on how to display data.
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You have to read some papers to understand what you have do as q functional analysis post DEGs finding. There are a lot of things you can do depending upon the questions you want to address. Read some functional papers you will get the flavor of also how to represent. For pathway you can look at Enrichr , Reactome and IPA ingenuity. However image representation entirely depends upon you if you want to use the tools visualization or create your own. Then look for them in functional papers and search for the respective packages in R or MATLAB.
One of my favourite tools for downstram enrichment analyses is GeneCodis. Quite user-friendly and comprehensive.
I would not encourage to use GeneCodis as I see it was last updated in 2011, 6 years in this field totally takes off a tool from the research market. For any Pathway and GO enrichment, updated tools that resource the latest or an update was done in 2016 as of now should be used.