Tools.The Open Specifications documentation does not require the use of Microsoftprogramming tools or programming environments in order for you to develop animplementation. If you have access to Microsoft programming tools andenvironments, you are free to take advantage of them. Certain OpenSpecifications documents are intended for use in conjunction with publiclyavailable standards specifications and network programming art and, as such,assume that the reader either is familiar with the aforementioned material orhas immediate access to it.
Here we have answered some of the most common questions that arise at the point of submitting an article in LaTeX. If your question relates specifically to the Springer Nature LaTeX authoring template, please consult the User Manual provided in the .zip package.
CS Sp-Hox V1 .zip Tool
MultiQC is a reporting tool that parses summary statistics from results and log filesgenerated by other bioinformatics tools. MultiQC doesn't run other tools for you -it's designed to be placed at the end of analysis pipelines or to be run manuallywhen you've finished running your tools.
We recommend using virtual environments to manage your Python installation.Our favourite is conda, a cross-platform tool to manage Python environments.You can installation instructions for Minicondahere.
To generate PDFs, MultiQC uses the simple template. This uses flat plots,has no navigation or toolbar and strips out all JavaScript. The resultingHTML report is pretty basic, but this simplicity is helpful when generatingPDFs.
Once the report is generated MultiQC attempts to call Pandoc,a command line tool able to convert documents between different file formats.You must have Pandoc already installed for this to work. If you don't havePandoc installed, you will get an error message that looks like this:
Please note that Pandoc is a complex tool and has a number of its own dependenciesfor PDF generation. Notably, it uses LaTeX / XeLaTeX which you must also have installed.Please make sure that you have the latest version of Pandoc andthat it can successfully convert basic HTML files to PDF before reportingand errors.
This opens the MultiQC Toolbox Export Plots panel with the current plotselected. You have a range of export options here. When deciding on outputformat bear in mind that SVG is a vector format, so can be edited in toolssuch as Adobe Illustratoror the free tool Inkscape. This makes it idealfor use in publications and manual customisation / annotation. ThePlot scaling option changes how large the labels are relative to the plot.
To help with this, you can use the Highlight Samples tool to colour datasetsof interest. Simply enter some text which will match the samples you want tohighlight and press enter (or click the add button). If you like, you can alsocustomise the highlight colour.
To make it easier to match groups of samples, you can use a regular expressionsby turning on 'Regex mode'. You can test regexes using a nice tool atregex101.com. See a nice introduction to regexeshere. Note that patterndelimiters are not needed (use pattern, not /pattern/).
To avoid having to re-enter the same toolbox setup repeatedly, you cansave your settings using the 'Save Settings' panel. Just pick a nameand click save. To load, choose your set of settings and press load(or delete). Loaded settings are applied on top of current settings.All configs are saved in browser local storage - they do not travelwith the report and may not work in older browsers.
This works well most of the time, until someone has an automated processingpipeline that renames things. For this reason, as of version v0.3.2 of MultiQC,the file search patterns are loaded as part of the main config. This means thatthey can be overwritten in /multiqc_config.yaml or/.multiqc_config.yaml. So if you always rename your _fastqc.zip files to_qccheck.zip, MultiQC can still work.
A substantial number of MultiQC modules take the sample name identifiers that yousee in the report from the file contents - typically the filename of the input file.This is because log files can often be called things like mytool.log or even concatenated.Using the input filename used by the tool is typically safer and more consistent across modules.
As of MultiQC version 1.8, log output is coloured using the coloredlogsPython package. The code attempts to detect if the logs on the terminal are being redirected to a fileor piped to another tool and will disable colours if so. If the colours annoy you or you're endingup with weird characters in your MultiQC output, you can disable this feature with the command lineflag --no-ansi. Sadly it's not possible to set this in a config file, as the logger is initilisedbefore configs are loaded.
Probably the easiest way to speed up MultiQC is to only use the modules that youknow you have files for. MultiQC supports a lot of different tools and searchesfor matching files for all of them every time you run it.
As an example, logs from Picard are published to STDOUT and so can have any file name.Some people concatenate logs, so the contents can be anywhere in the file and the filesmust also be searched by subsequent tools in case they contain multiple outputs.If you know that all of your Picard MarkDuplicate log files have the filenamemysamplename_markduplicates.log then you can safely customise that search patternwith the following MultiQC config:
Note that by default, partial matches are replaced. So if a log file gives a samplename of IDX102934_mytool then the result will be Sample_1_mytool.There are two config options to fine-tune this behaviour:
Setting sample_names_replace_exact to True in a MultiQC config file will tellMultiQC to only change a sample name if the pattern fully matches the search string.In the above example, IDX102934_mytool would remain unchanged.
Setting sample_names_replace_complete to True, the replacement string will be usedas a complete replacement if the search pattern matches at all.In the above example, IDX102934_mytool would become Sample_1.
Although it is possible to rename samples manually and in bulk using thereport toolbox, it's often desirable to embed such renaming patternsinto the report so that they can be shared with others. For example, a typical case could befor a sequencing centre that has internal sample IDs and also user-supplied sample names.Or public sample identifiers such as SRA numbers as well as more meaningful names.
It is possible to filter which samples are visible through the report toolbox,but it can be desirable to embed such patterns into the report so that they can be sharedwith others. One example can be to add filters for batches, to easily scan if certainquality metrics overlap between these batches.
The columns are organised by either namespace or table ID, then column ID.In the above example, Samtools is the namespace in the General Statistics table -the text that is at the start of the tooltip. For custom tables, the ID may be easier to use.
MultiQC has been designed to be placed at the end of bioinformatics workflowsand works well when it's a final step in a pipeline. Here you can find a fewtips about integration with different workflow tools.
Snakemake wrappers not only deliver predefined and unit tested code for generating the requested output with the respective tool, but also define the required software stack in terms of conda packages.
This first installs all the required tools into isolated conda environments, and then executes all necessary steps to create the target that is given in the top rule. In other words, it will execute FastQC twice (creating fastqc/1.html and fastqc/2.html) and MultiQC once, creating multiqc_report.html.
These files can be useful as MultiQC essentially standardises the outputs from a lot of different tools.Typical usage of MultiQC outputs could be filtering of large datasets (eg. single-cell analysis) or trend-monitoring of repeated runs.
Anglerfish is a tool designed to de-multiplex Illumina libraries sequenced on Oxford Nanopore Technologies flowcells for the purpose of quality control. Assessment of pool balancing, contamination and insert sizes are currently supported.
BioBloom Tools (BBT) provides the meansto create filters for a given reference and then to categorize sequences.This methodology is faster than alignment but does not provide mapping locations.BBT was initially intended to be used for pre-processing and QC applicationslike contamination detection, but is flexible to accommodate other purposes.This tool is intended to be a pipeline component to replace costly alignment steps.
CCS takes multiple subreads of the same SMRTbell molecule and combines themusing a statistical model to produce one highly accurate consensus sequence,also called HiFi read, with base quality values. This tool powers the CircularConsensus Sequencing workflow in SMRT Link.
The Cutadapt module parses results generated byCutadapt,a tool to find and remove adapter sequences, primers, poly-Atails and other types of unwanted sequence from your high-throughputsequencing reads.
DRAGEN has a number of different pipelines and outputs, including base calling, DNA and RNA alignment, andmany others. Starting with the release of DRAGEN v3.6, it also supports primary analysis of sequencingdata, modelled after the QC metrics generated by the widely used FastQC tool.
This module parses the output from that hardware-accelerated QC tool, and uses it to generate similarplots to both FastQC and MultiQC's current FastQC module. These plots are presented in their ownsection and module, such that they can be run indepedently or in conjunction with other MultiQCDRAGEN modules as desired.
The FastQ Screen module parses results generated byFastQ Screen,a tool that allows you to screen a library of sequences in FastQ formatagainst a set of sequence databases so you can see if the composition ofthe library matches with what you expect.
Filtlong is a tool for filtering long reads by quality.It can take a set of long reads and produce a smaller, better subset. It uses both read length (longer is better) and read identity (higher is better) when choosing which reads pass the filter. 2ff7e9595c
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