{"id":230,"date":"2009-05-27T12:37:16","date_gmt":"2009-05-27T10:37:16","guid":{"rendered":"http:\/\/occamstypewriter.org\/boboh\/2009\/05\/27\/help_how_do_i_deal_with_microarrays\/"},"modified":"2009-05-27T12:37:16","modified_gmt":"2009-05-27T10:37:16","slug":"help_how_do_i_deal_with_microarrays","status":"publish","type":"post","link":"https:\/\/occamstypewriter.org\/boboh\/2009\/05\/27\/help_how_do_i_deal_with_microarrays\/","title":{"rendered":"Help! How Do I Deal With Microarrays?"},"content":{"rendered":"

In the past I have ranted about the evils of p-values<\/a> and also how we’re not collecting the right sort of data<\/a>. Both of these have just collided in my work, and I’m not sure what to do.<\/p>\n


\nThe problem (simplified, and with details removed to protect the guilty) is this. We have a large microarray study. The data are expression levels of thousands of genes in some treatments, with a few random effects thrown in as well. What we want to do it to pick out the interesting genes, i.e. those which show a difference between treatments, and those which have a big random effect. And, of course, those with both. Once we have a list of these, we can ask whether particular types of gene are behaving in interesting ways, or whether it seems random.
\n\"\"<\/a>
\nA randomly selected image of a lot of spots<\/em>
\nNow, the traditional way of dealing with this is to calculate p-values, and declare the genes with p<0.05 (possibly after a correction for multiple tests) interesting. For reason why that's a bad idea go here<\/a>, and don’t come back until you’ve fully digested the lesson, and have taken to heart that the author is the greatest thinker since the inventor of the number 54<\/a>. What makes this worse is the random effect: the test would be of whether the variance was greater than zero. But in reality the variance is always >0, so the test is really really silly.
\nInstead we could simply set a threshold, say a value of 2, and say any gene with a treatment effect larger than this (or smaller than -2) is “significant”. But if we do that, we will tend to pick genes with less reliable estimates (because they are more likely by chance to get beyond the threshold).
\nSo, having eliminated the two obvious approaches, what to do? At the moment I don’t know, which is why I’m blogging this: I’m hoping for some suggestions, or at least hints. I’m particularly vague on what will be done with the genes afterwards. It seems that people produce summaries like pie charts, and say things like “this group of genes is over-represented”. What is not clear to me is what else is done: what questions are being asked?
\nIf the questions are clear and precise, then I think the statistics can take over: for example we can weight the importance of genes by the reliability of the estimates (e.g. through their standard errors). It might even be unnecessary to pick out important genes: we can use all of them, or be liberal in picking out genes.
\nSo, I’m interested to hear any thoughts on this. In particular, if we have a treatment, and some genes that it (might) affect, what sort of questions are being asked about those genes? How do we go from this list of genes to something that’s useful? Or, better, how do we want<\/em> go from this list of genes to something that’s useful? If we can refine the biological questions, we can wheel out the statistical machinery more effectively.
\nAs you can see, this is a research problem, so any useful ideas might turn into a paper. Contributions will be fully acknowledged, of course.<\/p>\n","protected":false},"excerpt":{"rendered":"

In the past I have ranted about the evils of p-values and also how we’re not collecting the right sort of data. Both of these have just collided in my work, and I’m not sure what to do.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-230","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/occamstypewriter.org\/boboh\/wp-json\/wp\/v2\/posts\/230","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/occamstypewriter.org\/boboh\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/occamstypewriter.org\/boboh\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/occamstypewriter.org\/boboh\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/occamstypewriter.org\/boboh\/wp-json\/wp\/v2\/comments?post=230"}],"version-history":[{"count":0,"href":"https:\/\/occamstypewriter.org\/boboh\/wp-json\/wp\/v2\/posts\/230\/revisions"}],"wp:attachment":[{"href":"https:\/\/occamstypewriter.org\/boboh\/wp-json\/wp\/v2\/media?parent=230"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/occamstypewriter.org\/boboh\/wp-json\/wp\/v2\/categories?post=230"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/occamstypewriter.org\/boboh\/wp-json\/wp\/v2\/tags?post=230"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}