A brief message for anyone who uses my PubMed retractions report. It’s no longer available at RPubs; instead, you will find it here at Github. Github pages hosting is great, once you figure out that docs/ corresponds to your web root :)
Now I really must update the code and try to make it more interesting than a bunch of bar charts.
A recent tweet:
PubMed articles containing “novel” in title or abstract 1845 – 2014
So here is the update, at Github and the report.
“Novel” findings, as judged by the usage of that word in titles and abstracts really have undergone a startling increase since about 1975. Indeed, almost 7.2% of findings were “novel” in 2014, compared with 3.2% for the period 1845 – 2014. That said, if we plot using a log scale as suggested by Tal on the original post, the rate of usage appears to be slowing down. See image, right (click for larger version).
As before, none of this is novel.
Just a quick update to the previous post. At the helpful suggestion of Steve Royle, I’ve added a new section to the report which attempts to normalise retractions by journal. So for example, J. Biol. Chem. has (as of now) 94 retracted articles and in total 170 842 publications indexed in PubMed. That becomes (100 000 / 170 842) * 94 = 55.022 retractions per 100 000 articles.
Top 20 journals, retracted articles per 100 000 publications
Back in 2010, I wrote a web application called PMRetract to monitor retraction notices in the PubMed database. It was written primarily as a way for me to explore some technologies: the Ruby web framework Sinatra, MongoDB (hosted at MongoHQ, now Compose) and Heroku, where the app was hosted.
I automated the update process using Rake and the whole thing ran pretty smoothly, in a “set and forget” kind of way for four years or so. However, the first era of PMRetract is over. Heroku have shut down git pushes to their “Bamboo Stack” – which runs applications using Ruby version 1.8.7 – and will shut down the stack on June 16 2015. Currently, I don’t have the time either to update my code for a newer Ruby version or to figure out the (frankly, near-unintelligible) instructions for migration to the newer Cedar stack.
So I figured now was a good time to learn some new skills, deal with a few issues and relaunch PMRetract as something easier to maintain and more portable. Here it is. As all the code is “out there” for viewing, I’ll just add few notes here regarding this latest incarnation.
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I am forever returning to PubMed data, downloaded as XML, trying to extract information from it and becoming deeply confused in the process.
Take the seemingly-simple question “how many retracted articles are there in PubMed?”
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Chris writes:
The blog post in question concerns conversion of PubMed PMIDs to BibTeX citations. However, a few things have changed since 2010.
Here’s what currently works.
| # pmid2bibtex.rb | |
| # convert a PubMed PMID to BibTeX citation format | |
| # updated version of http://chrisamiller.com/science/2010/12/13/using-bioruby-to-fetch-citations-from-pubmed/ | |
| # works as of 2015-03-18 | |
| require 'bio' | |
| Bio::NCBI.default_email = "me@me.com" # required for EUtils | |
| id = "18265351" | |
| pm = Bio::PubMed::efetch(id) # array of MEDLINE-formatted string | |
| med = Bio::MEDLINE.new(pm[0]) # MEDLINE object | |
| bib = med.reference.format("bibtex") # format is a method of Reference object | |
| # "@article{PMID:18265351,\n author = {Brown, T. and Mackey, K. and Du, T.},\n title = {Analysis of RNA by northern | |
| # and slot blot hybridization.},\n journal = {Curr Protoc Mol Biol},\n year = {2004},\n volume = {Chapter | |
| # 4},\n pages = {Unit 4.9},\n url = {http://www.ncbi.nlm.nih.gov/pubmed/18265351},\n}\n" |
Before we start: yes, we’ve been here before. There was the Biostars question “Calculating Time From Submission To Publication / Degree Of Burden In Submitting A Paper.” That gave rise to Pierre’s excellent blog post and code + data on Figshare.
So why are we here again? 1. It’s been a couple of years. 2. This is the R (+ Ruby) version. 3. It’s always worth highlighting how the poor state of publicly-available data prevents us from doing what we’d like to do. In this case the interesting question “which bioinformatics journal should I submit to for rapid publication?” becomes “here’s an incomplete analysis using questionable data regarding publication dates.”
Let’s get it out of the way then.
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File this one under “has troubled me (and others) for some years now, let’s try to resolve it.”
Let’s use the excellent R/rentrez package to search PubMed for articles that were retracted in 2013.
library(rentrez)
es <- entrez_search("pubmed", "\"Retracted Publication\"[PTYP] 2013[PDAT]", usehistory = "y")
es$count
# [1] 117
117 articles. Now let’s fetch the records in XML format.
xml <- entrez_fetch("pubmed", WebEnv = es$WebEnv, query_key = es$QueryKey,
rettype = "xml", retmax = es$count)
Next question: which XML element specifies the “Date of publication” (PDAT)?
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Just how many (bad) -omics are there anyway? Let’s find out.
Update: code and data now at Github
Read the rest…
PubMed cumulative retractions 1977-present
Several of these sources cite data from my humble web application, PMRetract. So now seems like a good time to mention that:
Now I just need to fix up my Git repositories. Currently there’s one which pushes to GitHub and a second, with a copy of the Sinatra code for pushing to Heroku, which isn’t too smart.
What You're Doing Is Rather Desperate 