Microbiology, Metagenomics and Bioinformatics

For a couple of years, I have been working with microbial ecology and diversity, and how such features can be assessed using molecular barcodes, such as the SSU (16S/18S) rRNA sequence (the Metaxa and Megraft packages). However, I have also been aiming at the ITS region, and how that can be used in barcoding (see e.g. the guidelines we published last year). It is therefore a great pleasure to introduce my next gem for community analysis; a software tool for detection and extraction of the ITS1 and ITS2 regions of ITS sequences from environmental communities. The tool is dubbed ITSx, and supersedes the more specific fungal ITS extractor written by Henrik Nilsson and colleagues. Henrik is once more the mastermind behind this completely rewritten version, in which I have done the lion’s share of the programming. Among the new features in ITSx are:

• Robust support for the Cantharellus, Craterellus, and Tulasnella genera of fungi
• Support for nineteen additional eukaryotic groups on top of the already present support for fungi (specifically these groups: Tracheophyta (vascular plants), Bryophyta (bryophytes), Marchantiophyta (liverworts), Chlorophyta (green algae), Rhodophyta (red algae), Phaeophyceae (brown algae), Metazoa (metazoans), Oomycota (oomycetes), Alveolata (alveolates), Amoebozoa (amoebozoans), Euglenozoa, Rhizaria, Bacillariophyta (diatoms), Eustigmatophyceae (eustigmatophytes), Raphidophyceae (raphidophytes), Synurophyceae (synurids), Haptophyceae (haptophytes) , Apusozoa, and Parabasalia (parabasalids))
• Multi-processor support
• Extensive output options
• Virtually zero false-positive extractions

ITSx is today moved from a private pre-release state to a public beta state. No code changes has been made since February, indicative of that the last pre-release candidate is now ready to fly on its own. As far as our testing has revealed, this version seems to be bug free. In reality though, researchers tend to find the most unexpected usage scenarios. So please, if you find any unexpected behavior in this version of ITSx, send me an e-mail and make us aware of the potential shortcomings of our software.

We expect this open-source software to boost research in microbial ecology based on barcoding of the ITS region, and hope that the research community will evaluate its performance also among the eukaryote groups that we have less experience with.

A long time ago, we (Martin Eriksson, Martin Hartmann, Henrik Nilsson and me) were invited to write an overview on Metaxa for the Encyclopedia of Metagenomics. I guess the workload for pulling such a project off is huge, so there’s no surprise that it has taken a while for it to be accepted, but now it is available for consumption.

Meanwhile, Metaxa have been getting regular updates, and I hope to soon be able to show you a new major update to the software, bringing it up to the next generation of metagenomics. More on that soon.

• Bengtsson-Palme J, Hartmann M, Eriksson KM, Nilsson RH: Metaxa, overview. In:Nelson K. (Ed.) Encyclopedia of Metagenomics: SpringerReference (www.springerreference.com). Springer-Verlag Berlin Heidelberg (2013). [Link]

Those attending the Metagenomics lab (part of the basic NGS course for PhD students given at GU this week), can find the material for the lab on this page:
http://microbiology.se/ngs-metagenomics-lab/
Of course, the page is open for anyone else as well, although you won’t get the support that the GU students are given.

You might remember that I a long time ago promised a minor update to Megraft. I then forgot about actually posting the update. So it’s very much about time, the updated 1.0.2 version of Megraft. The new thing in this version is improved handling of sequences with N’s (unknown bases) in them, and improved handling of sequences with strange sequence IDs (which sometimes have confused Megraft 1.0.1). The update can be downloaded here.

Some good and some bad news regarding the PETKit. Good news first; I have written a fourth tool for the PETKit, which is included in the latest release (version 1.0.2b, download here). The new tool is called Pesort, and sorts input read pairs (or single reads) so that the read pairs occur in the same order. It also sorts out which reads that don’t have a pair and outputs them to a separate file. All this is useful if you for some reason have ended up with a scrambled read file (pair). This can e.g. happen if you want to further process the reads after running Khmer or investigate the reads remaining after mapping to a genome.

Then the bad news. There’s a critical bug in PETKit version 1.0.1b. This bug manifest itself when using custom offsets for quality scores (using the –offset option), and makes the Pearf and Pepp tools too strict – leading to that they discard reads that actually are of good quality. This does not affect the Pefcon program. If you use the PETKit for read filtering or ORF prediction, and have used custom offset values, I recommend that you re-run your data with the newly released PETKit version (1.0.2b), in which this bug has been fixed. If you have only used the default offset setting, your safe. I sincerely apologize for any inconveniences that this might have caused.

Some users have asked me to fix a table output bug in Metaxa, and I have finally got around to do so. The fix is released today in the 1.1.2 Metaxa package (download here). This version also brings an updated manual (finally), as the User’s Guide has lagged behind since version 1.0. Please continue to report bugs to metaxa [at sign] microbiology [dot] se

Download the Metaxa package

Read the manual

Good news for everyone using my bloutminer script; it has received an update making it even more useful! Basically, I have added a function to extract the top N matches to each query (using the -n option), and I have also added the ability to output a filtered set of sequences in the same tabulated BLAST-format as the input came in. Thereby, bloutminer can now be used in more settings to easily filter out a subset in a large BLAST report (in tabular format, generated using the blastall -m 8 option). The script can be downloaded here: http://microbiology.se/software/

You know the feeling when your assembler supports paired-end sequences, but your FASTQ quality filterer doesn’t care about what pairs that belong together? Meaning that you end up with a mess of sequences that you have to script together in some way. Gosh, that feeling is way too common. It is for situations like that I have put together the Paired-End ToolKit (PETKit), a collection of FASTQ/FASTA sequence handling programs written in Perl. Currently the toolkit contains three command-line tools that does sequence conversion, quality filtering, and ORF prediction, all adapted for paired-end sequences specifically. You can read more about the programs, which are released as open source software, on the PETKit page. At the moment they lack proper documentation, but running the software with the “–help” option should bring up a useful set of options for each tool. This is still considered beta-software, so any bug reports, and especially suggestions, are welcome.

Also, if you have an idea of another problem that is unsolved or badly executed for paired-end sequences, let me know, and I will see if I can implement it in PETKit.

The Core Facilites at Sahlgrenska are looking for a skilled bioinformatician that can support research projects employing the Core Facilites’ services. The employee will e.g. deal with setting up analysis pipelines for next generation sequencing data. They (of course) want an experienced bioinformatician, who also knows programming (Java, C and/or C++, and scripting languages such as Perl or Python). It is also preferable if the applicant knows how to set up secure systems and manage work with the Unix/Linux terminal. More on the position can be found at GU’s web site. The application time closes on the 17th of September.

I have co-authored a paper together with, among others, Henrik Nilsson that was published today in MycoKeys. The paper deals with checking quality of DNA sequences prior to using them for research purposes. In our opinion, a lot of the software available for sequence quality management is rather complex and resource intensive. Not everyone have the skills to master such software, and in addition computational resources might also be scarce. Luckily, there’s a lot that can be done in quality control of DNA sequences just using manual means and a web browser. This paper puts these means together into one comprehensible and easy-to-digest document. Our targeted audience is primaily biologists who do not have a strong background in computer science, and still have a dataset requiring DNA sequence quality control.

We have chosen to focus on the fungal ITS barcoding region, but the guidelines should be pretty general and applicable to most groups of organisms. In very short our five guidelines spells:

1. Establish that the sequences come from the intended gene or marker
   Can be done using a multiple alignment of the sequences and verifying that they all feature some suitable, conserved sub-region (the 5.8S gene in the ITS case)
2. Establish that all sequences are given in the correct (5’ to 3’) orientation
   Examine the alignment for any sequences that do not align at all to the others; re-orient these; re-run the alignment step; and examine them again
3. Establish that there are no (at least bad cases of) chimeras in the dataset
   Run the sequences through BLAST in one of the large sequence databases, e.g. at NCBI (or in the ITS case, use the UNITE database), to verify that the best match comprises more or less the full length of the query sequences
4. Establish that there are no other major technical errors in the sequences
   Examine the BLAST results carefully, particularly the graphical overview and the pairwise alignment, for anomalies (there are some nice figures in the paper on how it should and should not look like)
5. Establish that any taxonomic annotations given to the sequences make sense
   Examine the BLAST hit list to see that the species names produced make sense

A much more thorough description of these guidelines can be found in the paper itself, which is available under open access from MycoKeys. There’s simply no reason not to go there and at least take a look at it. Happy quality control!

Reference
Nilsson RH, Tedersoo L, Abarenkov K, Ryberg M, Kristiansson E, Hartmann M, Schoch CL, Nylander JAA, Bergsten J, Porter TM, Jumpponen A, Vaishampayan P, Ovaskainen O, Hallenberg N, Bengtsson-Palme J, Eriksson KM, Larsson K-H, Larsson E, Kõljalg U: Five simple guidelines for establishing basic authenticity and reliability of newly generated fungal ITS sequences. MycoKeys. Issue 4 (2012), 37–63. doi: 10.3897/mycokeys.4.3606 [Paper link]