doc changes - 072020 (#3021)

Author: antgonza

CHANGELOG.md

@@ -17,6 +17,7 @@ Version 072020
 * Removed legacy future dependencies from Python2.7
 * Users can see the available system plugins, their commands and resource allocations: https://qiita.ucsd.edu/software/
 * Added qiime2.2020.06 to the system; which updated these plugins: qp-qiime2, qtp-biom, qtp-diversity, qtp-visualization
+* Shogun v1.0.8 for Metagenomic and Metatrascriptomics processing; this new version includes bowtie2 v2.4.1 as aligner and [Web of Life](https://biocore.github.io/wol/) and [rep200](ftp://ftp.ncbi.nlm.nih.gov/refseq/release/).
 
 Version 052020
 --------------

qiita_db/sql_connection.py

@@ -203,7 +203,7 @@ def _raise_execution_error(self, sql, sql_args, error):
 
     @_checker
     def add(self, sql, sql_args=None, many=False):
-        """Add an sql query to the transaction
+        """Add a sql query to the transaction
 
         Parameters
         ----------

qiita_pet/support_files/doc/source/dev/resource_allocation.rst

@@ -19,7 +19,7 @@ separate possible name conflicts while at the same time keeping this separation
 simple.
 
 #. RESOURCE_PARAMS_COMMAND: This is the most common entry as it defines the allocation
-   for an specific command name, like "Shogun v1.0.7" or "Beta diversity (phylogenetic)",
+   for a specific command name, like "Shogun v1.0.7" or "Beta diversity (phylogenetic)",
    for the complete list of commands visit: `Qiita Software <https://qiita.ucsd.edu/software/>`__
 #. COMPLETE_JOBS_RESOURCE_PARAM: When a RESOURCE_PARAMS_COMMAND completes, it will define if the job
    finished successfully and a set of artifact(s) that need to be validated and then added to Qiita -

qiita_pet/support_files/doc/source/faq.rst

@@ -210,6 +210,18 @@ To correct this issue, simply add a column to your preparation information file
 names listed in the sample_name column in your preparation information file.
 
 
+What's a Qiita Artifact?
+------------------------
+
+A Qiita artifact is a collection of files and their summaries that represent the output
+or input of a processing or analytical command.
+
+For example a per_sample_FASTQ artifact will contain the per sample FASTQ files and their
+summary (if a user generated); while a BIOM artifact has the feature table as a biom file, a
+QIIME2 QZA, any other supporting files (like a phylogenetic tree for deblur or sortmerna_picked_otus.tgz
+for close reference picking), and summaries.
+
+
 How to convert Qiita files to QIIME2 artifacts?
 -----------------------------------------------
 
@@ -235,7 +247,7 @@ etc; for more information check
 How to cite Qiita?
 ------------------
 
-If you use Qiita for processing, submition to EBI-ENA and/or its data for any published research, please include the following citation:
+If you use Qiita for processing, submission to EBI-ENA and/or its data for any published research, please include the following citation:
 
 **Qiita: rapid, web-enabled microbiome meta-analysis.**
 Antonio Gonzalez, Jose A. Navas-Molina, Tomasz Kosciolek, Daniel McDonald, Yoshiki Vázquez-Baeza, Gail Ackermann, Jeff DeReus, Stefan Janssen, Austin D. Swafford, Stephanie B. Orchanian, Jon G. Sanders, Joshua Shorenstein, Hannes Holste, Semar Petrus, Adam Robbins-Pianka, Colin J. Brislawn, Mingxun Wang, Jai Ram Rideout, Evan Bolyen, Matthew Dillon, J. Gregory Caporaso, Pieter C. Dorrestein & Rob Knight. Nature Methods, volume 15, pages 796–798 (2018);

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

@@ -88,7 +88,7 @@ Shogun aligners
    - Version: 0.99.8
    - Alignment file format: b6o (BLAST tabular output, i.e., `-outfmt 6`)
    - Website: https://github.com/knights-lab/BURST
-   - Citation: Al-Ghalith, Gabriel and Dan Knights. BURST enables optimal exhaustive DNA alignment for big data. DOI 2017:doi.org/10.5281/zenodo.806850
+   - Citation: Gabriel Al-Ghalith and Dan Knights. BURST enables optimal exhaustive DNA alignment for big data. DOI 2017:doi.org/10.5281/zenodo.806850
    - Note: Manuscript under review.
 
 #. UTree
@@ -97,7 +97,7 @@ Shogun aligners
    - Version: 2.0 RF
    - Alignment file format: custom mapping file
    - Website: https://github.com/knights-lab/UTree
-   - Citation: Al-Ghalith, Gabriel and Dan Knights. Faster and lower-memory metagenomic profiling with UTree. DOI: 10.5281/zenodo.998252
+   - Citation: Gabriel Al-Ghalith and Dan Knights. Faster and lower-memory metagenomic profiling with UTree. DOI: 10.5281/zenodo.998252
 
 Shogun reference databases
 ^^^^^^^^^^^^^^^^^^^^^^^^^^
@@ -126,6 +126,19 @@ Shogun reference databases
      - Strains: 89
      - Note: Nucleotide sequences per genome were concatenated with a linker of 20 "N"s.
 
+#. Rep200: NCBI representative and reference microbial genomes, corresponding to RefSeq release 200 (2020-05-14)
+
+   - Genomes:             11,955
+   - Nucleotides:        926,894
+   - Basepairs:   62,823,581,921 (excluding gaps)
+   - Numbers of taxonomic units:
+
+     - Archaea:  419
+     - Bacteria: 11080
+     - Fungi:    320
+     - Protozoa: 88
+     - Viral:    48
+
 #. Rep94: NCBI representative and reference microbial genomes, corresponding to RefSeq release 94.
 
    - Domains: Bacteria, Archaea
@@ -166,7 +179,10 @@ Metatranscriptome processing
 
 Sample processing guidelines for metatranscriptomic data
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-Total community RNA extracted from samples contain both coding and non-coding RNA. Typically, ribosomal RNA make up >90% of the library if not depleted prior to library construction. Ribosomal depletion allows for mRNA enrichment. Even if you are dealing with ribosomal RNA subtracted cDNA libraries, there will be some
+
+Total community RNA extracted from samples contain both coding and non-coding RNA. Typically, ribosomal RNA make up
+>90% of the library if not depleted prior to library construction. Ribosomal depletion allows for mRNA enrichment. Even if
+you are dealing with ribosomal RNA subtracted cDNA libraries, there will be some
 residual ribosomal RNA in the libraries that you want to remove/separate from the non ribosomal RNA sequences.
 
 Ribosomal read filtering
@@ -178,7 +194,8 @@ is used for removal of ribosomal reads from quality filtered Metatranscriptome d
 Latest SortMeRNA version: v2.1
 
 Input: Quality filtered Metatranscriptome reads (FASTA/FASTQ)
-Ribosomal reads are identified by searching against pre-curated rRNA databases. Currently, rRNA databases covering bacteria, archaea and eukarya were downloaded and indexed from `SILVA <https://www.arb-silva.de>`_ and `Rfam <https://rfam.xfam.org>`_.
+Ribosomal reads are identified by searching against pre-curated rRNA databases. Currently, rRNA databases covering bacteria, archaea and eukarya
+were downloaded and indexed from `SILVA <https://www.arb-silva.de>`_ and `Rfam <https://rfam.xfam.org>`_.
 Currently indexed databases and their clustering ids:
 
 - silva-bacterial-16s-id 90%
@@ -206,7 +223,8 @@ Reference database(s) and their corresponding indexes separated by "," and multi
 
 SortMeRNA Usage
 ^^^^^^^^^^^^^^^
-SortMeRNA filters the ribosomal from the non-ribosomal reads from the input sample dataset (via BLAST search)and outputs two fasta/q files containing the ribosomal and non-ribosomal reads respectively.
+SortMeRNA filters the ribosomal from the non-ribosomal reads from the input sample dataset (via BLAST search)and outputs two fasta/q files containing the
+ribosomal and non-ribosomal reads respectively.
 Additionally, a summary file showing the proportion of reads matching to each of the screened ribosomal databases can also be made available.
 Default options have been set to report only the best alignment per read reaching E-value.
 For non ribo-depleted samples (i.e. total RNA), the ribosomal reads obtained from SortMeRNA can be further used in taxonomic/compositional analysis.

qiita_ware/test/test_private_plugin.py

@@ -371,7 +371,7 @@ def test_build_analysis_files(self):
             'analysis': 3, 'merge_dup_sample_ids': True})
 
         # testing shape and get_resource_allocation_info as
-        # build_analysis_files is an special case
+        # build_analysis_files is a special case
         def _set_allocation(memory):
             with TRN:
                 sql = """UPDATE qiita.processing_job_resource_allocation