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I'm using several datasets that are encoded using either Entrez or Ensembl IDs to specify genes, and need to decide on which to standardise on.

Are there any major reasons to use one over the other?

Which tools and conversion tables are best to use for this?

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    $\begingroup$ It may be useful to specify some more about your particular use case. I don't have an answer to your question, but it's feasible that the pros and cons of the two databases differ depending on what you're trying to do. $\endgroup$
    – roblanf
    Jun 7, 2017 at 6:11
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    $\begingroup$ There is a discussion on Biostar in the same topic. biostars.org/p/16505 $\endgroup$
    – arup
    Jun 7, 2017 at 7:17
  • $\begingroup$ Hi einonm, thanks for your question, and welcome to Bioinformatics Stack Exchange. Bioinformatics is a big subject area with a vast array of tools and databases, many which have almost the same purpose but are designed to attack a particular problem. As @roblanf has pointed out, it would be helpful if you could add a bit more story / context to your question so that the community can better understand the problem. A more specific question means the chance of a good, relevant answer is increased. $\endgroup$
    – gringer ♦
    Jun 7, 2017 at 9:40
  • $\begingroup$ It's not just a matter of what IDs to use, but of what gene models to use. Even if an Ensembl gene has a cross reference to an Entrez gene, that's only because the Ensembl xref pipeline has decided that they are similar enough. $\endgroup$
    – Kusalananda
    Jun 7, 2017 at 9:51

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I think there is no general answer to your question.

Which type of ID you will use depends on how practical it will be for your downstream processing. This depends on what other source of information you have, how much conversion work you will need to do in order to match your data to these information if you use one or the other.

I think the choice may emerge by trial and error, as you realize that a given choice is actually not convenient in your particular use case. Try to set up easy to use conversion procedures that you can easily insert in some steps of your workflow, so that you can easily switch from one choice to the other.

Concerning the tools to do the conversion, see the following question and its answers: Converting gene names from one public database format to another

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