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qiita_pet/support_files/doc/source/faq.rst

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the "Upload instructions"
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`here <https://www.google.com/url?q=https%3A%2F%2Fvamps.mbl.edu%2Fmobe_workshop%2Fwiki%2Findex.php%2FMain_Page&sa=D&sntz=1&usg=AFQjCNE4PTOKIvFNlWtHmJyLLy11mfzF8A>`__.
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.. _example_study_processing_workflow:
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Example study processing workflow
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---------------------------------
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qiita_pet/support_files/doc/source/index.rst

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dev/index.rst
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faq.rst
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resources.rst
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processing-recommendations.rst
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Processing recommendations
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==========================
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Currently, Qiita supports the processing :sup:`(*)` of raw data from:
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#. Target gene barcoded sequencing
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#. Shotgun sequencing
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Note that the selected processing are mainly guided so we can perform meta-analyses, this is combine different studies, even from different wet lab techniques or
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sequencing technologies. Remember to check the :ref:`example_study_processing_workflow` before continuing.
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For more information about meta-analysis, examples and things to consider:
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- `"Tiny microbes, enormous impacts: what matters in gut microbiome studies?" <https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1086-x>`_
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- `"Meta-analyses of studies of the human microbiota" <http://genome.cshlp.org/content/23/10/1704.short>`_.
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- `"A Guide to Enterotypes across the Human Body: Meta-Analysis of Microbial Community Structures in Human Microbiome Datasets" <http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1002863>`_.
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- `"Dynamic changes in short- and long-term bacterial composition following fecal microbiota transplantation for recurrent Clostridium difficile infection" <http://microbiomejournal.biomedcentral.com/articles/10.1186/s40168-015-0070-0>`_.
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:sup:`(*)` Remember that you can also upload BIOM tables for plotting but not covered here because this is only for raw data.
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Target gene barcoded sequencing
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-------------------------------
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For this you can start with raw, not demultiplexed data or per_sample_FASTQ, see :ref:`example_study_processing_workflow`. Either way, you will need to
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"Split libraries and QC", which uses the default in QIIME 1.9.1. Once your demultiplexed and QCed artifact is created you need to select which processing to perform.
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There are two main ideologies/methodologies to process target gene data: sequence clustering and sequence cleanup.
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Sequencing cleanup (preferred)
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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For this we use `deblur <https://github.com/biocore/deblur>`_. Here 2 BIOM tables are generated by default: fina.biom and final.only-16s.biom. The former is the full biom table, which can be used with any target gene and wetlab work;
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the latter is the trimmed version to those sequences that match Greengenes at 80% similarity, a really basic and naive filtering. Each of those BIOM tables, is accompanied by a FASTA that contains
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the representative sequences. The OTU IDs are given by the unique sequence.
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Note that deblur needs all sequences to be trimmed at the same length, thus the recommended pipeline is to trim everything at 150bp and the deblur.
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Sequencing clustering
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^^^^^^^^^^^^^^^^^^^^^
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Here we use close reference picking, for an explanation of the different picking methods see
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`"Subsampled open-reference clustering creates consistent, comprehensive OTU definitions and scales to billions of sequences" <https://peerj.com/articles/545/>`_.
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Here we generate a single BIOM table with the OTUs/per-sample. The OTU IDs are given based on the reference database selected.
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Currently, we have the reference databases: Greengenes version 3_8-97, Silva 119 and Unite 7. Depending on your selection is if the reference has a phylogenetic tree.
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Shotgun sequencing
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------------------
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Here you need to start with per_sample_FASTQ, we recommend to only upload already QC-ed and adaptor and human sequences removed FASTQ files. However, we have a step for
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this preprocessing available in Qiita via `KneadData <https://bitbucket.org/biobakery/kneaddata/wiki/Home>`_.
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The recommended processing steps are:
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#. Remove adapters and human sequences from your files using KneadData. We currently have TruSeq3-PE-2 and NexteraPE-PE adaptor removal.
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#. Use `HUMAnN2 <https://bitbucket.org/biobakery/humann2/wiki/Home>`_ to generate BIOM tables.
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For more information visit the `Shotgun Qiita Plugin GitHub page<https://github.com/qiita-spots/qp-shotgun>`.

qiita_pet/templates/study_ajax/prep_summary.html

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"<div class='col-md-12'>" +
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"<h4><a class='btn btn-info' id='show-hide-btn' onclick='toggle_graphs();'>-</a><i> Files network</i></h4>" +
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"<b>(Click nodes for more information, blue are jobs)</b>" +
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"<br/>Check our data <a target='_blank' href='{% raw qiita_config.portal_dir %}/static/doc/html/processing-recommendations.html' onclick='return !window.open(this.href, \"Qiita processing recommendations\", \"width=800,height=500\")'>processing recommendations</a>." +
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"</div>" +
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"</div>" +
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"<div class='row'><div class='col-md-12 graph' style='width:90%' id='graph-network-div'>" +

qiita_pet/templates/study_ajax/processing_artifact.html

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<div class="row">
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<div class="col-md-12">
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<h4><i> Processing workflow</i> <button class="btn btn-primary btn-sm" onclick="run_workflow();" id='run-btn' disabled><span class="glyphicon glyphicon-play"></span> Run</button></h4>
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<h4>
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<i>Processing workflow</i>
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<button class="btn btn-primary btn-sm" onclick="run_workflow();" id='run-btn' disabled><span class="glyphicon glyphicon-play"></span> Run</button>
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</h4>
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<h5>
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Wondering what to select? Check our data <a target='_blank' onclick="return !window.open(this.href, 'Qiita processing recommendations', 'width=800,height=500')" href='{% raw qiita_config.portal_dir %}/static/doc/html/processing-recommendations.html'>processing recommendations</a>.
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</h5>
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