Wednesday, May 18, 2016

Comparing sets of identifiers: the Bioclipse implementation

Source: Wikipedia
The problem
That sounds easy: take two collection of identifiers, put them in sets, determine the intersection, done. Sadly, each collection uses identifiers from different databases. Worse, within one set identifiers from multiple databases. Mind you, I'm not going full monty, though some chemistry will be involved at some point. Instead, this post is really based on identifiers.

The example
Data set 1:

Data set 2: all metabolites from WikiPathways. This set has many different data sources, and seven provide more than 100 unique identifiers. The full list of metabolite identifiers is here.

The goal
Determine the interaction of two collections of identifiers from arbitrary databases, ultimately using scientific lenses. I will develop at least two solutions: one based on Bioclipse (this post) and one based on R (later).

First of all, we need something that links IDs in the first place. Not surprisingly, I will be using BridgeDb (doi:10.1186/1471-2105-11-5) for that, but for small molecules alternatives exist, like the Open PHACTS IMS based on BridgeDb, the Chemical Translation Service (doi:10.1093/bioinformatics/btq476) or UniChem (doi:10.1186/s13321-014-0043-5, doi:10.1186/1758-2946-5-3).

The Bioclipse implementation
The first thing we need to do is read the files. I have them saved as CSV even though it is a tab-separated file. Bioclipse will now open it in it's matrix editor (yes, I think .tsv needs to be linked to that editor, which does not seem to be the case yet). Reading the human metabolites from WikiPathways is done with this code (using Groovy as scripting language):

file1 = new File(
    "/Compare Identifiers/human_metabolite_identifiers.csv"
set1 = new java.util.HashSet();
file1.eachLine { line ->
  fields = line.split(/\t/)
  def syscode;
  def id;
  if (fields.size() >= 2) {
    (syscode, id) = line.split(/\t/)
  if (syscode != "syscode") { // ok, not the first line
    set1.add(bridgedb.xref(id, syscode))

You can see that I am using the BridgeDb functionality already, to create Xref objects. The code skips the first line (or any line with "column headers"). The BridgeDb Xref object's equals() method ensures I only have unique cross references in the resulting set.

Reading the other identifier set is a bit trickier. First, I manually changed the second column, to use the BridgeDb system codes. The list is short, and saves me from making mappings in the source code. One thing I decide to do in the source code is normalize the ChEBI identifiers (something that many of you will recognize):

file2 = new File(
  bioclipse.fullPath("/Compare Identifiers/set.csv")
set2 = new java.util.HashSet();
file2.eachLine { line ->
  fields = line.split(/\t/)
  def name;
  def syscode;
  def id;
  if (fields.size() >= 3) {
    (name, syscode, id) = line.split(/\t/)
  if (syscode != "syscode") { // ok, not the first line
    if (syscode == "Ce") {
      if (!id.startsWith("CHEBI:")) {
        id = "CHEBI:" + id
    set2.add(bridgedb.xref(id, syscode))

Then, the naive approach that does not take into account identifier equivalence makes it easy to list the number of identifiers in both sets:

intersection = new java.util.HashSet();

println "set1: " + set1.size()
println "set2: " + set2.size()
println "intersection: " + intersection.size()

This reports:

set1: 2584
set2: 6
intersection: 3

With the following identifiers in common:

[Ce:CHEBI:30089, Ce:CHEBI:15904, Ca:25513-46-6]

Of course, we want to use the identifier mapping itself. So, we first compare identifiers directly, and if not matching, use BridgeDb and an metabolite identifier mapping database (get one here):

mbMapper = bridgedb.loadRelationalDatabase(

intersection = new java.util.HashSet();
for (id2 in set2) {
  if (set1.contains(id2)) {
    // OK, direct match
  } else {
    mappings =, id2)
    for (mapped in mappings) {
      if (set1.contains(mapped)) {
        // OK, direct match

This gives five matches:

[Ch:HMDB00042, Cs:5775, Ce:CHEBI:15904, Ca:25513-46-6, Ce:CHEBI:30089]

The only metabolite it did not find in any pathway is the KEGG identified metabolite, homocystine. I just added this compound to Wikidata. That means that in the next metabolite mapping database, it will recognize this compound too.

The R and JavaScript implementations
I will soon write up the R version in a follow up post (but got to finish grading student reports first).

Friday, April 29, 2016

Sci-Hub succeeds where publishers fail (open and closed)

Sci-Hub use in The Netherlands is not limited to
the academic research cities. Harlingen is a small
harbor town where at best a doctor lives and
one or two students who visit parents in the
weekend. The nature of the top downloaded
paper suggests it is not a doctor :)
Data from Bohannon and Elbakyan.
Knowledge dissemination is a thing. It's not easy. In fact, it's a major challenge. Traditional routes are not efficient anymore, where they were 200 years ago. The world has moved on; the publishing industry has not. I have written plenty in this blog about how the publishers could catch up, and while this is happening, progress is (too) slow.

The changes are not only technical, but also social. Several publishers still believe we live in a industrial area, where the world has moved on into a knowledge era. More people are mining and servicing data than there are making physical things (think about that!). Access to knowledge matters, and dealing with data and knowledge stopped being something specific for academic and other research institutes many, many years ago. Arguments that knowledge is only for the highly educated is simply contradicting and bluntly ignore our modern civilization.

This makes access to knowledge a mix of technological and social evolution, and on both end many publishers fail, fail hard, fail repeatedly. I would even argue that all the new publishers are improving things, but are failing to really innovate in knowledge dissemination. And not just the publishing industry, also many scientists. Preprint servers are helpful, but this is really not the end goal. If you really care about speeding up knowledge dissemination, stop worrying about things like text mining, preprints, but you have to start making knowledge machine readable (sorry, scientist) and release that along or before your article. Yes, that is harder, but just realize you are getting well-paid for doing your job.

So, by no means the success of Sci-Hub is unexpected. It is not really the end goal I have in mind, and in many ways contradicting what I want. But the research community thinks differently, clearly. Oh wait, not just the research community, but the current civilization. The results of the Bohannon analysis of the Sci-Hub access logs I just linked to clearly shows this. There are so many aspects, and so many interpretations and remaining questions. The article rightfully asks, is it need or convenience. I argued recently the latter is likely an important reason at western universities, and that it is nothing new.

This article is a must read if you care about the future of civilization. Bonus points for a citable data set!

Bohannon, J. Who's downloading pirated papers? everyone. Science 352, 508-512 (2016). URL
Elbakyan, A. & Bohannon, J. Data from: Who's downloading pirated papers? everyone. (2016). URL

Sunday, April 24, 2016

Programming in the Life Sciences #22: jsFiddle

My son pointed me to jsFiddle which allows you to edit JavaScript snippets and run them. I have heard of them before, but never really got time for it. But I'm genuinely impressed with the stuff he is doing, and finally wanted to try sharing JavaScript snippets online, particularly, because I had to update the course description of Programming in the Life Sciences. In this course the students work with JavaScript and there are a number of example, but that has a lot of HTML boiler plate code.

So, here's the first of those examples, but then stripped from most of the things you don't need, and with some extra documentation as comments:

Saturday, April 23, 2016

Splitting up Bioclipse Groovy scripts

Source: Wikipedia, CC-BY-SA 3.0
... without writing additional script managers (see doi:10.1186/1471-2105-10-397). That was what I was after. I found that by using evaluate() you could load additional code. Only requirements, you wrap stuff in a class, and the filename need to match the class name. So, you put stuff in a class SomeName and safe that in a Bioclipse project (e.g. SomeProject/) with the name SomeName.groovy.

That is, I have this set up:


Then, in this aScript.groovy you can include the following code to load that class and make use of the content:

  someClass = evaluate(
    new File(

Maybe there are even better ways, but this works for me. I tried the regular Groovy way of instantiating a class defined like this, but because the Bioclipse Groovy environment does not have a working directory, I could not get that to work.

Tuesday, April 05, 2016

Still a draft: The Amsterdam Call for Action on Open Science

It was on the agenda: "Presenting the Amsterdam Call for Action". However, a day of hard work by some 300 participants of the Dutch Presidency's meeting on Open Science did not allow for the draft to be finalized today. Instead, the editors will work the next 24h (a bit less by now) on a new draft that will be send around to the participants which will then have about a week to send in further comments.

There was enough feedback given on the draft indeed, and followers of my blog and twitter account know how much they already got from just me. It will be a busy 24 hours for the editors. I am really looking forward with the next draft they come up with. BTW, it is not clear yet if I will be able to share the draft that I get tomorrow. We'll see. At least I will tweet about whether or not my main points got addressed.

Meanwhile, the Dutch VSNU sent out a press release that "[they are] pleased with European action plan Open Science". Given that it was in fact not released yet, suggests a few things:

  1. they anticipated the draft was a done deal (which aligns with the lack of openness around the draft);
  2. automated sending out of press releases is a bad idea.