MiModD

List of public Galaxy servers with MiModD tools installed

D stands for Desktop ...

to emphasize the fact that, with MiModD, you do not have to upload gigabytes of sequencing data to the cloud just because the tool you want to analyze it with does not come with a decent installer.
Installation of MiModD for use from the command line is extremely simple and, with just a little bit more effort, you can run it from inside your own local instance of Galaxy, too.

It is true, however, that when you want to combine MiModD with other bioinformatics tools (to do things like quality control of sequenced reads, indel realignment, variant visualization, etc.), then equipping your system with all these additional tools may require quite a bit of effort, and having them available through a public Galaxy server together with MiModD would really feel much more convenient.
In addition, using MiModD on a public server is, admittedly, the best solution for Windows users who cannot, or do not want to, find a Linux or macOS system to run MiModD on.

So for all these reasons and because we kept getting user requests for it, here are lists of public Galaxy servers offering MiModD tools:

Servers offering the main MiModD tools

MiModD is available on all three major public Galaxy servers:

• https://usegalaxy.eu/ - The official European Galaxy instance
• https://usegalaxy.org - the U.S.-based Galaxy Main server
• https://usegalaxy.org.au - Galaxy Australia

On these servers, you can carry out complete MiModD-based mapping-by-sequencing analyses, but certain MiModD tools that are functionally redundant with other tools on the server are not available (see below on how to combine MiModD with other tools to obtain a fully functional analysis workflow on these servers).

Using MiModD on public Galaxy servers

Local installs of MiModD provide a standalone solution for complete mapping-by-sequencing analyses starting from sequenced reads and ending with a list of candidate mutations annotated with predicted effects on genes and transcript.
In the context of an established Galaxy server equipped with standard tools for NGS data analysis, however, some of the MiModD tools would be redundant with the existing tools on the server and are, therefor, not included. Typically, these are:

• the MiModD Read Alignment tool
  for aligning sequenced reads to the reference genome of your species of interest, and
• the MiModD Variant Annotation tool
  for annotating candidate variant lists with predicted genomic effects

Here is how you can replace these tools with other tools found on such servers ( for a complete picture of how to analyze your data with MiModD, you should work through our collection of tutorials ):

Using bowtie2 for the read alignment step

bowtie2 is our recommended alternative to the MiModD Read alignment tool.
For standard analyses you can accept almost all default settings configured for the tool, and just configure the following options:

• Set the "Is this single or paired library" parameter to the type of your sequenccing data. Then select your sequenced reads as the "FASTA/Q file"(s) to use.
  Note that of the different input formats supported by MiModD, bowtie2 only accepts fastq.
• Under "Will you select a reference genome from your history or use a built-in index?" select "Use a built-in genome index" if the server comes with an appropriate reference genome for your analysis preinstalled. If you have uploaded your own reference genome in fasta format, select "Use a genome from the history and build index".
• Select "Set read groups (SAM/BAM specification)" under "Set read groups information?" to specify, at least, a read group ID and a sample name. This corresponds to the SAM header information that you would pass to the MiModD Read Alignment tool.

You will have to run a separate job for every sample/read group in your analysis and will end up with a corresponding number of aligned reads datasets. This is fine because you can select all of them as "Aligned reads input dataset(s)" in a subsequent single run of the MiModD Variant Calling tool.

Using standard Galaxy SnpEff tools for variant annotation

The SnpEff Variant effect and annotation tool is a good replacement for the MiModD Variant Annotation tool. To use it though, you will first have to obtain a SnpEff genome database describing genomic features found on your reference genome, and this can be done with the SnpEff Download tool.

• Find out the versions of this tool offered by the server by clicking on the "Versions" button at the very top of the tool interface.
• Find out the name of a SnpEff genome database file corresponding to your reference genome that is compatible with any of the SnpEff versions found above.
  The databases available for any specific SnpEff version can be browsed by using the link provided under that version's "Select the genome version you want to download" text box.
• Select the tool version compatible with the database file you want to download, provide the name of that genome file under "Select the genome version you want to download" and execute the job.

This should add a new dataset of type snpeffdb to your history, which you can use as input to the SnpEff Variant effect and annotation tool:

• Make sure you are using the same version of the SnpEff tool as you downloaded the genome file for! Use the "Versions" button to change to the right version if required.
• Under "Sequence changes (SNPs, MNPs, InDels)" select your VCF dataset with the variants that you wish to annotate.
• Make sure "Input format" and "Output format" are set to "VCF".
• Select "Reference genome from your history" under "Genome source" and then the Snpeff genome database you obtained above as the "SnpEff Genome Data". Note: Only genome databases compatible with the tool version you have set above, will be selectable at this step. Change the tool version if necessary!
• Under "Annotation options" select the "Use 'EFF' field compatible with older versions (instead of 'ANN')" checkbox or the output of the tool will not be compatible with the MiModD Report Variants tool.
• Configure the remaining parameters as you like or go with the defaults.

The resulting new VCF dataset of annotated variants can be used as input to the MiModD Report Variants tool.