Processing recommendations and pipelines

qiita_pet/support_files/doc/source/faq.rst

@@ -26,6 +26,8 @@ example go
 the "Upload instructions"
 `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>`__.
 
+.. _example_study_processing_workflow:
+
 Example study processing workflow
 ---------------------------------
 

qiita_pet/support_files/doc/source/index.rst

@@ -29,3 +29,4 @@ following documents:
    dev/index.rst
    faq.rst
    resources.rst
+   processing-recommendations.rst

qiita_pet/support_files/doc/source/processing-recommendations.rst

@@ -0,0 +1,65 @@
+Processing recommendations
+==========================
+
+Currently, Qiita supports the processing :sup:`(*)` of raw data from:
+
+#. Target gene barcoded sequencing
+#. Shotgun sequencing
+
+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
+sequencing technologies. Remember to check the :ref:`example_study_processing_workflow` before continuing.
+
+For more information about meta-analysis, examples and things to consider:
+
+- `"Tiny microbes, enormous impacts: what matters in gut microbiome studies?" <https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1086-x>`_
+- `"Meta-analyses of studies of the human microbiota" <http://genome.cshlp.org/content/23/10/1704.short>`_.
+- `"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>`_.
+- `"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>`_.
+
+:sup:`(*)` Remember that you can also upload BIOM tables for plotting but not covered here because this is only for raw data.
+
+Target gene barcoded sequencing
+-------------------------------
+
+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
+"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.
+There are two main ideologies/methodologies to process target gene data: sequence clustering and sequence cleanup.
+
+Sequencing cleanup (preferred)
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+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;
+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
+the representative sequences. The OTU IDs are given by the unique sequence.
+
+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.
+
+Sequencing clustering
+^^^^^^^^^^^^^^^^^^^^^
+
+Here we use close reference picking, for an explanation of the different picking methods see
+`"Subsampled open-reference clustering creates consistent, comprehensive OTU definitions and scales to billions of sequences" <https://peerj.com/articles/545/>`_.
+Here we generate a single BIOM table with the OTUs/per-sample. The OTU IDs are given based on the reference database selected.
+
+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.
+
+
+Shotgun sequencing
+------------------
+
+Qiita currently has one shotgun metagenomics data analysis pipeline. Note that this is the initial processing pipeline and we will be adding more soon.
+
+With that said, the current workflow is as follows:
+
+#. Removal of adapter sequence and host contamination using `KneadData <https://bitbucket.org/biobakery/kneaddata/wiki/Home>`_.
+#. Gene calling and pathway profiling using `HUMAnN2 <https://bitbucket.org/biobakery/humann2/wiki/Home>`_.
+
+This workflow starts with per_sample_FASTQ files. We recommend only uploading sequences that have already been through QC and host /
+human sequence removal. However, all sequence files currently are required to go through KneadData to ensure they are ready for
+subsequent analyses. Currently, the KneadData command removes adaptor sequences (choice of TruSeq3-PE-2 and NexteraPE-PE) and
+sequences mapping to the human genome (additional host genomes will become available soon).
+
+Next, the QC'd sequences will be compared against reference databases to determine the presence and abundance of protein-coding functional genes and
+pathways using HUMAnN2. These are then summarized as BIOM tables, which can be used in subsequent analysis and visualization.
+
+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

@@ -243,6 +243,7 @@
             "<div class='col-md-12'>" +
               "<h4><a class='btn btn-info' id='show-hide-btn' onclick='toggle_graphs();'>-</a><i> Files network</i></h4>" +
               "<b>(Click nodes for more information, blue are jobs)</b>" +
+              "<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>." +
             "</div>" +
           "</div>" +
           "<div class='row'><div class='col-md-12 graph' style='width:90%' id='graph-network-div'>" +

qiita_pet/templates/study_ajax/processing_artifact.html

@@ -401,7 +401,13 @@ <h4>Processing {{name}} (ID: {{artifact_id}})</h4>
 
 <div class="row">
   <div class="col-md-12">
-    <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>
+    <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>
+    <h5>
+      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>.
+    </h5>
   </div>
 </div>