The person behind this is really Björn Grüning at the University of Freiburg. I am immensely thankful for the work he has put into this. Our intention to make sure that both the Galaxy version and the bioconda version are maintained in parallel to the one on this website, and continuously up to date!
Yes, Saturdays are somewhat weird days for software updates, but if you’re doing weekend work anyway, why wait to push bug fixes to the community? A very minor bug-fix update to Metaxa2 was released today, bringing the software to version 2.2.3.
Two things have changed in this version, both related to the genome mode. 1) We fixed a file reading bug in the ‘genome’ mode of the software. This bug caused the last sequence in an input FASTA file not to be read unless there was a newline after it. Since the ‘genome’ mode is rarely used by most users, we suspect not a lot of users have been affected by this bug.
2) While we were at it, we changed the behavior of the ‘genome’ mode to mirror that of the ‘auto’ mode, as the strict genome mode dropped sequences shorter than 2500 bp. We considered this behavior counter-intuitive to what most users would want, and has now changed the ‘genome’ mode to behave the same as the ‘auto’ mode and not drop short sequences.
No other changes have been made in this version. The update can be found at the Metaxa2 software page.
A new version of ITSx is released today. This minor update contains two minor bug fixes and two small new features.
The first bug was that ITSx returned empty sequences in the FASTA file for no detections for large input files. This has now been fixed.
The second bug fix is a bit more fuzzy and involved some fine-tuning of how large input files are handled in ITSx to stabilise E-value and score cut-offs.
The two new features are:
- The possbility to put the temporary directory in a custom location using the
- ITSx now warns when the input file contains sequences with identical identifiers, which usually leads to sequences being dropped from the input file.
The new update brings ITSx to version 1.1.3. Thanks for the users who have spotted bugs and suggested new features! Happy barcoding everyone!
We start the new year with a bang, or at least a new paper published. Bioinformatics put our paper (1) describing the software package CAFE online today (although it was accepted late last year). The CAFE package is a combination of Perl and R tools that can analyze data from paired transposon mutant sequencing experiments (2-4), generate fitness coefficients for each gene and condition, and perform appropriate statistical testing on these fitness coefficients. The paper is short, but shows that CAFE performs as good as the best competing tools (5-7) while being superior at controlling for false positives (you’ll have to dig into the supplement to find the data for that though).
Importantly, this is a collaborative effort by basically the entire research group from last spring: me, Haveela, Emil, Anna and our visiting student Adriana. A big thanks to all of you for working on this short but important paper! You can read the full paper here.
- Abramova A, Osińska A, Kunche H, Burman E, Bengtsson-Palme J (2021) CAFE: A software suite for analysis of paired-sample transposon insertion sequencing data. Bioinformatics, advance article doi: 10.1093/bioinformatics/btaa1086
- Chao,M.C. et al. (2016) The design and analysis of transposon insertion sequencing experiments. Nature reviews Microbiology, 14, 119–128.
- van Opijnen,T. and Camilli,A. (2013) Transposon insertion sequencing: a new tool for systems-level analysis of microorganisms. Nature reviews Microbiology, 11, 435–442.
- Goodman,A.L. et al. (2011) Identifying microbial fitness determinants by insertion sequencing using genome-wide transposon mutant libraries. Nature Protocols, 6, 1969–1980.
- McCoy,K.M. et al. (2017) MAGenTA: a Galaxy implemented tool for complete Tn- Seq analysis and data visualization. Bioinformatics, 33, 2781– 2783.
- Zhao,L. et al. (2017) TnseqDiff: identification of conditionally essential genes in transposon sequencing studies. BMC Bioinformatics, 18.
- Zomer,A. et al. (2012) ESSENTIALS: Software for Rapid Analysis of High Throughput Transposon Insertion Sequencing Data. PLoS ONE, 7, e43012.
Today, we released a minor update to Metaxa2, bringing it to version 2.2.2. The new version includes some bug fixes related to the Metaxa2 Database Repository, as well as a new “–temp” option allowing the user to specify the location for the temporary files. No other changes have been made in this version.
The update can be found at the Metaxa2 software page.
Exactly two years after we released the Metaxa2 database builder, here’s the first update to the software. Unfortunately, it is just a boring bug fix, but the good part is that brings back compatibility with the new version of HMMER (3.3) released in November 2019 (as noted here). It seems like it is mainly the Database builder which has been impacted with by this incompatibility, but we recommend everyone to update.
We have tried to bug check this version as good as we can to make sure we did not break any features while introducing this new compatibility. We think that this version is bug free, but as we wanted to push this out quickly, please be more observant than usual to odd behaviour, and make sure to report any bugs!
The update can be downloaded here: https://microbiology.se/sw/Metaxa2_2.2.1.tar.gz
Update: There is now an updated version of Metaxa2 that addresses this problem. Find it here.
We have recently discovered that the new version of HMMER (3.3) released in November 2019 have introduced new restrictions that make it partially incompatible with Metaxa2. The most apparent problem is in the Database Builder software, which will not build profiles properly in most cases. Instead, HMMER will return an error and only some profiles will be created.
We do currently not know if this also affects the functionality of Metaxa2 itself. We are currently investigating this.
For now, the solution to this problem is to use the previous version of HMMER (version 3.2.1) while we investigate further. That version can be downloaded here: http://hmmer.org/download.html
I am sorry about not discovering this earlier, this only came to our attention this week!
ITSx has been updated with some minor bug fixes (solving bugs that caused big problems for a small subset of users).
The first bug was that the no detections file generated in a previous file was not removed before it was written to (if it happened to have the same name in a subsequent run). This could cause weird errors where sequences which were not part of the input file were reported as not detected, and subsequently inconsistent counts for the number of missing sequences. This bug should now be fixed (although I have to admit that it is hard to test for this error in all possible scenarios).
The second bug was very serious for anyone who worked with ITS sequences from Chlorophyta. The ‘-t’ option did not accept ‘G’ (the code for Chlorophyta) as an option, while it did accept ‘green algae’ or ‘chlorophyta’. The Chlorophyta profiles were also included in the default ‘all’ profiles mode, and thus this error did not manifest itself for the vast majority of users. I am sorry for the mess this must have caused for the Chlorophyta researchers using ITSx and thank the users of the software for pointing this error out.
Sorry for these bug fixes taking so long! It has been a very unusual and stressful spring and summer, and I hope to be able to be more responsive in the future. The new update brings ITSx to version 1.1.2. No other changes except the two bug fixes have been made in this version.
I am happy to share the news that the paper describing out software tool Mumame is now out in its final form! (1) The paper got published today in the journal Metabarcoding and Metagenomics after being available as a preprint (2) since last autumn. This version has not changed a whole lot since the preprint, but it is more polished and better argued (thanks to a great review process). The software is virtually the same, but is not also available via Conda.
In the paper, we describe the Mumame software, which can be used to distinguish between wildtype and mutated sequences in shotgun metagenomic sequencing data and quantify their relative abundances. We further demonstrate the utility of the tool by quantifying antibiotic resistance mutations in several publicly available metagenomic data sets (3-6), and find that the tool is useful but that sequencing depth is a key factor to detect rare mutations. Therefore, much larger numbers of sequences may be required for reliable detection of mutations than is needed for most other applications of shotgun metagenomics. Since the preprint was published, Mumame has also found use in our recently published paper on selection for antibiotic resistance in a Croatian macrolide production wastewater treatment plant, unfortunately with inconclusive results (7). Mumame is freely available here.
I again want to stress the fantastic work that Shruthi Magesh did last year as a summer student at WID in the evaluation of this tool. As I have pointed out earlier, I did write the code for the software (with a lot of input from Viktor Jonsson), but Shruthi did the software testing and evaluations. Thanks and congratulations Shruthi, and good luck in pursuing your PhD program!
- Magesh S, Jonsson V, Bengtsson-Palme J: Mumame: A software tool for quantifying gene-specific point-mutations in shotgun metagenomic data. Metabarcoding and Metagenomics, 3: 59–67 (2019). doi: 10.3897/mbmg.3.36236
- Magesh S, Jonsson V, Bengtsson-Palme J: Quantifying point-mutations in metagenomic data. bioRxiv, 438572 (2018). doi: 10.1101/438572
- Bengtsson-Palme J, Boulund F, Fick J, Kristiansson E, Larsson DGJ: Shotgun metagenomics reveals a wide array of antibiotic resistance genes and mobile elements in a polluted lake in India. Frontiers in Microbiology, 5, 648 (2014). doi: 10.3389/fmicb.2014.00648
- Lundström S, Östman M, Bengtsson-Palme J, Rutgersson C, Thoudal M, Sircar T, Blanck H, Eriksson KM, Tysklind M, Flach C-F, Larsson DGJ: Minimal selective concentrations of tetracycline in complex aquatic bacterial biofilms. Science of the Total Environment, 553, 587–595 (2016). doi: 10.1016/j.scitotenv.2016.02.103
- Pal C, Bengtsson-Palme J, Kristiansson E, Larsson DGJ: The structure and diversity of human, animal and environmental resistomes. Microbiome, 4, 54 (2016). doi: 10.1186/s40168-016-0199-5
- Kraupner N, Ebmeyer S, Bengtsson-Palme J, Fick J, Kristiansson E, Flach C-F, Larsson DGJ: Selective concentration for ciprofloxacin in Escherichia coli grown in complex aquatic bacterial biofilms. Environment International, 116, 255–268 (2018). doi: 10.1016/j.envint.2018.04.029
- Bengtsson-Palme J, Milakovic M, Švecová H, Ganjto M, Jonsson V, Grabic R, Udiković Kolić N: Pharmaceutical wastewater treatment plant enriches resistance genes and alter the structure of microbial communities. Water Research, 162, 437-445 (2019). doi: 10.1016/j.watres.2019.06.073