Tag: Software updates

Metaxa and HMMER 3.1b

As you might be aware, a new version of HMMER is out since late May. You might wonder how Metaxa (relying on HMMER3) will work if you update to the new version of HMMER, and I have finally got around to test it! The answer, according to my somewhat limited testing, is that Metaxa 1.1.2 seems to be working fine with HMMER 3.1.

You might need to go into the database directory (“metaxa_db”; should be located in the same directory as the Metaxa binaries), and remove all the files ending with suffixes .h3f .h3i .h3m and .h3p inside the “HMMs” directory. On most installation, this should not be necessary. Myself, I just plugged HMMER 3.1 in and started Metaxa, but if you get error messages complaining that “Error: bad format, binary auxfiles, .hmm:
binary auxfiles are in an outdated HMMER format (3/b); please hmmpress your HMM file again”, then you should try removing the files and re-running Metaxa. This might especially be a problem on older Metaxa versions. [Update: Note that this fix will likely not work with ITSx!]

Bear in mind that I have not run thorough testing on Metaxa and HMMER 3.1, and probably won’t for the 1.1.2 version, since there’s a 2.0 version waiting just around the corner…

Additionally, if you experience problems with Megraft, you should try the same fix as for Metaxa, but with the Megraft database directory instead. Regarding ITSx, a minor update will be released very soon, which also will address HMMER 3.1b compatibility. [Update: See this post for how to work around HMMER 3.1 problems with ITSx.]

Happy barcoding everyone!

ITSx – a software tool for detection and extraction of ITS1 and ITS2 sequences

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.

An update to Megraft

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.

PETKit updated – Critical bug fix

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.

Metaxa updated to version 1.1.2

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

Bloutminer updated

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: https://microbiology.se/software/

Introducing the PETKit

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.

One more thing…

I realized that I have been using a newer version of Metaxa than most of you for the last couple of months. This bug fix was written sometime in February or March, and we have kept it internal to make sure it works as it should. Then other things came across and we never got around to actually release it. But with testing passed and upcoming versions of Metaxa in the pipeline, I think it is about time that everyone gets their hands on the latest Metaxa version.

It’s only two small things this time:

  • Slight tweaks to the new HMM scoring system, making Metaxa just a little bit faster
  • Fixed a rarely occurring bug causing the –heuristics options to be ignored in certain circumstances

Download the Metaxa 1.1.1 package here

Metaxa and Illumina data

For the last months I have been (part time) struggling with getting Metaxa to eat Illumina paired-end data. This is a pretty tricky task, mainly due to the fact that Illumina reads are so much shorter than those obtained by Sanger and 454 sequencing. Therefore, I am more than happy to inform the community that today (the day before I go on vacation) I have a working prototype up and running. In fact, calling it a prototype is unfair, it is a quite far gone piece of software by now. Currently, I am running it on test data sets, and I will try to keep it running over the next couple of weeks. Thereafter, I hope to be able to release it sometime this autumn (but don’t expect a September release!), harnessing the power of Illumina sequencing for SSU identification. Stayed tuned, and have a great summer!

Finally – Metaxa 1.1

I am extremely happy to announce that Metaxa 1.1 (first announced back in July) has finally left the beta stage, and is now designated as a feature complete 1.1 update. We consider this update stable for production use. The 1.1 update utilize hmmsearch instead of hmmscan for higher extraction speeds and better accuracy. This clever trick was inspired by a blog post by HMMER’s creator Sean Eddy on hmmscan vs hmmsearch (http://selab.janelia.org/people/eddys/blog/?p=424). As the speedup comes from the extraction step, the speed increase will be largest for huge data sets with only a small proportion of actual SSU sequences (typically large 454 metagenomes).

What took so long, you might ask, as I promised an imminent release already in August. Well, during testing a difference in scoring was discovered. This difference did not have any implications for long sequences (> ~350 bp), but caused Metaxa to have problems on short reads (most evident on ~150 bp and shorter). Therefore, the scoring system had to be redesigned, which in turn required more extensive testing. Now, however, Metaxa 1.1 has a fine-tuned scoring system, which by default is based on scores instead of E-values, and in some instances have even better detection accuracy than the old Metaxa version. We encourage everyone to try out this new version of Metaxa (although the 1.0.2 version will remain available for download). It should be bug free, but we cannot ensure 100% compatibility in all usage scenarios. Therefore, we are happy if you report any bugs or inconsistencies to the e-mail address: metaxa (at] microbiology [dot) se.

The new version of Metaxa can be downloaded here: https://microbiology.se/software/metaxa/ Please note that the manual has not yet been updated yet, so use the help feature for the up-to-date options. Happy SSU detecting!