# HG changeset patch
# User greg
# Date 1609690889 0
# Node ID abfb861df87971564729180ca6b0ecbf312a37e1
# Parent  85384a9bfba2ea68f329ae15958cdbd750bb03b9
Uploaded

diff -r 85384a9bfba2 -r abfb861df879 macros.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/macros.xml	Sun Jan 03 16:21:29 2021 +0000
@@ -0,0 +1,24 @@
+<?xml version='1.0' encoding='UTF-8'?>
+<macros>
+    <token name="@WRAPPER_VERSION@">1.0</token>
+    <token name="@PROFILE@">19.09</token>
+    <xml name="param_reference_source">
+        <param name="reference_source" type="select" label="Choose the source for the reference genome">
+            <option value="cached" selected="true">locally cached</option>
+            <option value="history">from history</option>
+        </param>
+    </xml>
+    <xml name="citations">
+        <citations>
+            <citation type="bibtex">
+                @misc{None,
+                journal = {None},
+                author = {1. Stuber T},
+                title = {Manuscript in preparation},
+                year = {None},
+                url = {https://github.com/USDA-VS/vSNP},}
+            </citation>
+        </citations>
+    </xml>
+</macros>
+
diff -r 85384a9bfba2 -r abfb861df879 tool_data_table_conf.xml.test
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/tool_data_table_conf.xml.test	Sun Jan 03 16:21:29 2021 +0000
@@ -0,0 +1,7 @@
+<tables>
+    <!-- Location of genbank files for vsnp_build_tables tool -->
+    <table name="vsnp_genbank" comment_char="#">
+        <columns>value, name, path, description</columns>
+        <file path="${__HERE__}/test-data/vsnp_genbank.loc" />
+    </table>
+</tables>
diff -r 85384a9bfba2 -r abfb861df879 vsnp_build_tables.py
--- a/vsnp_build_tables.py	Thu Apr 30 15:55:22 2020 -0400
+++ b/vsnp_build_tables.py	Sun Jan 03 16:21:29 2021 +0000
@@ -1,17 +1,13 @@
 #!/usr/bin/env python
 
 import argparse
-import multiprocessing
 import os
+import re
+
 import pandas
-import queue
 import pandas.io.formats.excel
-import re
 from Bio import SeqIO
 
-INPUT_JSON_AVG_MQ_DIR = 'input_json_avg_mq_dir'
-INPUT_JSON_DIR = 'input_json_dir'
-INPUT_NEWICK_DIR = 'input_newick_dir'
 # Maximum columns allowed in a LibreOffice
 # spreadsheet is 1024.  Excel allows for
 # 16,384 columns, but we'll set the lower
@@ -32,7 +28,7 @@
         # Create an annotation file.
         annotation_file = "%s_annotations.csv" % group
         with open(annotation_file, "a") as fh:
-            for index, row in positions.iterrows():
+            for _, row in positions.iterrows():
                 pos = row.position
                 try:
                     aaa = pro.iloc[pro.index.get_loc(int(pos))][['chrom', 'locus', 'product', 'gene']]
@@ -144,18 +140,12 @@
     return annotation_dict
 
 
-def get_base_file_name(file_path):
+def get_sample_name(file_path):
     base_file_name = os.path.basename(file_path)
     if base_file_name.find(".") > 0:
         # Eliminate the extension.
         return os.path.splitext(base_file_name)[0]
-    elif base_file_name.find("_") > 0:
-        # The dot extension was likely changed to
-        # the " character.
-        items = base_file_name.split("_")
-        return "_".join(items[0:-1])
-    else:
-        return base_file_name
+    return base_file_name
 
 
 def output_cascade_table(cascade_order, mqdf, group, annotation_dict):
@@ -168,17 +158,20 @@
     # is used by the excel_formatter.
     if count is None:
         if group is None:
-            json_file_name = "%s_order_mq.json" % type_str
+            json_file_name = os.path.join(OUTPUT_EXCEL_DIR, "%s_order_mq.json" % type_str)
             excel_file_name = os.path.join(OUTPUT_EXCEL_DIR, "%s_table.xlsx" % type_str)
         else:
-            json_file_name = "%s_%s_order_mq.json" % (group, type_str)
+            json_file_name = os.path.join(OUTPUT_EXCEL_DIR, "%s_%s_order_mq.json" % (group, type_str))
             excel_file_name = os.path.join(OUTPUT_EXCEL_DIR, "%s_%s_table.xlsx" % (group, type_str))
     else:
+        # The table has more columns than is allowed by the
+        # MAXCOLS setting, so multiple files will be produced
+        # as an output collection.
         if group is None:
-            json_file_name = "%s_order_mq_%d.json" % (type_str, count)
+            json_file_name = os.path.join(OUTPUT_EXCEL_DIR, "%s_order_mq_%d.json" % (type_str, count))
             excel_file_name = os.path.join(OUTPUT_EXCEL_DIR, "%s_table_%d.xlsx" % (type_str, count))
         else:
-            json_file_name = "%s_%s_order_mq_%d.json" % (group, type_str, count)
+            json_file_name = os.path.join(OUTPUT_EXCEL_DIR, "%s_%s_order_mq_%d.json" % (group, type_str, count))
             excel_file_name = os.path.join(OUTPUT_EXCEL_DIR, "%s_%s_table_%d.xlsx" % (group, type_str, count))
     df.to_json(json_file_name, orient='split')
     # Output the Excel file.
@@ -228,94 +221,74 @@
         output_excel(df, type_str, group_str, annotation_dict)
 
 
-def preprocess_tables(task_queue, annotation_dict, timeout):
-    while True:
-        try:
-            tup = task_queue.get(block=True, timeout=timeout)
-        except queue.Empty:
-            break
-        newick_file, json_file, json_avg_mq_file = tup
-        avg_mq_series = pandas.read_json(json_avg_mq_file, typ='series', orient='split')
-        # Map quality to dataframe.
-        mqdf = avg_mq_series.to_frame(name='MQ')
-        mqdf = mqdf.T
-        # Get the group.
-        group = get_base_file_name(newick_file)
-        snps_df = pandas.read_json(json_file, orient='split')
-        with open(newick_file, 'r') as fh:
-            for line in fh:
-                line = re.sub('[:,]', '\n', line)
-                line = re.sub('[)(]', '', line)
-                line = re.sub(r'[0-9].*\.[0-9].*\n', '', line)
-                line = re.sub('root\n', '', line)
-        sample_order = line.split('\n')
-        sample_order = list([_f for _f in sample_order if _f])
-        sample_order.insert(0, 'root')
-        tree_order = snps_df.loc[sample_order]
-        # Count number of SNPs in each column.
-        snp_per_column = []
-        for column_header in tree_order:
-            count = 0
-            column = tree_order[column_header]
-            for element in column:
-                if element != column[0]:
-                    count = count + 1
-            snp_per_column.append(count)
-        row1 = pandas.Series(snp_per_column, tree_order.columns, name="snp_per_column")
-        # Count number of SNPS from the
-        # top of each column in the table.
-        snp_from_top = []
-        for column_header in tree_order:
-            count = 0
-            column = tree_order[column_header]
-            # for each element in the column
-            # skip the first element
-            for element in column[1:]:
-                if element == column[0]:
-                    count = count + 1
-                else:
-                    break
-            snp_from_top.append(count)
-        row2 = pandas.Series(snp_from_top, tree_order.columns, name="snp_from_top")
-        tree_order = tree_order.append([row1])
-        tree_order = tree_order.append([row2])
-        # In pandas=0.18.1 even this does not work:
-        # abc = row1.to_frame()
-        # abc = abc.T --> tree_order.shape (5, 18), abc.shape (1, 18)
-        # tree_order.append(abc)
-        # Continue to get error: "*** ValueError: all the input arrays must have same number of dimensions"
-        tree_order = tree_order.T
-        tree_order = tree_order.sort_values(['snp_from_top', 'snp_per_column'], ascending=[True, False])
-        tree_order = tree_order.T
-        # Remove snp_per_column and snp_from_top rows.
-        cascade_order = tree_order[:-2]
-        # Output the cascade table.
-        output_cascade_table(cascade_order, mqdf, group, annotation_dict)
-        # Output the sorted table.
-        output_sort_table(cascade_order, mqdf, group, annotation_dict)
-        task_queue.task_done()
-
-
-def set_num_cpus(num_files, processes):
-    num_cpus = int(multiprocessing.cpu_count())
-    if num_files < num_cpus and num_files < processes:
-        return num_files
-    if num_cpus < processes:
-        half_cpus = int(num_cpus / 2)
-        if num_files < half_cpus:
-            return num_files
-        return half_cpus
-    return processes
+def preprocess_tables(newick_file, json_file, json_avg_mq_file, annotation_dict):
+    avg_mq_series = pandas.read_json(json_avg_mq_file, typ='series', orient='split')
+    # Map quality to dataframe.
+    mqdf = avg_mq_series.to_frame(name='MQ')
+    mqdf = mqdf.T
+    # Get the group.
+    group = get_sample_name(newick_file)
+    snps_df = pandas.read_json(json_file, orient='split')
+    with open(newick_file, 'r') as fh:
+        for line in fh:
+            line = re.sub('[:,]', '\n', line)
+            line = re.sub('[)(]', '', line)
+            line = re.sub(r'[0-9].*\.[0-9].*\n', '', line)
+            line = re.sub('root\n', '', line)
+    sample_order = line.split('\n')
+    sample_order = list([_f for _f in sample_order if _f])
+    sample_order.insert(0, 'root')
+    tree_order = snps_df.loc[sample_order]
+    # Count number of SNPs in each column.
+    snp_per_column = []
+    for column_header in tree_order:
+        count = 0
+        column = tree_order[column_header]
+        for element in column:
+            if element != column[0]:
+                count = count + 1
+        snp_per_column.append(count)
+    row1 = pandas.Series(snp_per_column, tree_order.columns, name="snp_per_column")
+    # Count number of SNPS from the
+    # top of each column in the table.
+    snp_from_top = []
+    for column_header in tree_order:
+        count = 0
+        column = tree_order[column_header]
+        # for each element in the column
+        # skip the first element
+        for element in column[1:]:
+            if element == column[0]:
+                count = count + 1
+            else:
+                break
+        snp_from_top.append(count)
+    row2 = pandas.Series(snp_from_top, tree_order.columns, name="snp_from_top")
+    tree_order = tree_order.append([row1])
+    tree_order = tree_order.append([row2])
+    # In pandas=0.18.1 even this does not work:
+    # abc = row1.to_frame()
+    # abc = abc.T --> tree_order.shape (5, 18), abc.shape (1, 18)
+    # tree_order.append(abc)
+    # Continue to get error: "*** ValueError: all the input arrays must have same number of dimensions"
+    tree_order = tree_order.T
+    tree_order = tree_order.sort_values(['snp_from_top', 'snp_per_column'], ascending=[True, False])
+    tree_order = tree_order.T
+    # Remove snp_per_column and snp_from_top rows.
+    cascade_order = tree_order[:-2]
+    # Output the cascade table.
+    output_cascade_table(cascade_order, mqdf, group, annotation_dict)
+    # Output the sorted table.
+    output_sort_table(cascade_order, mqdf, group, annotation_dict)
 
 
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
 
-    parser.add_argument('--input_avg_mq_json', action='store', dest='input_avg_mq_json', required=False, default=None, help='Average MQ json file')
-    parser.add_argument('--input_newick', action='store', dest='input_newick', required=False, default=None, help='Newick file')
-    parser.add_argument('--input_snps_json', action='store', dest='input_snps_json', required=False, default=None, help='SNPs json file')
     parser.add_argument('--gbk_file', action='store', dest='gbk_file', required=False, default=None, help='Optional gbk file'),
-    parser.add_argument('--processes', action='store', dest='processes', type=int, help='User-selected number of processes to use for job splitting')
+    parser.add_argument('--input_avg_mq_json', action='store', dest='input_avg_mq_json', help='Average MQ json file')
+    parser.add_argument('--input_newick', action='store', dest='input_newick', help='Newick file')
+    parser.add_argument('--input_snps_json', action='store', dest='input_snps_json', help='SNPs json file')
 
     args = parser.parse_args()
 
@@ -326,56 +299,4 @@
     else:
         annotation_dict = None
 
-    # The assumption here is that the list of files
-    # in both INPUT_NEWICK_DIR and INPUT_JSON_DIR are
-    # named such that they are properly matched if
-    # the directories contain more than 1 file (i.e.,
-    # hopefully the newick file names and json file names
-    # will be something like Mbovis-01D6_* so they can be
-    # sorted and properly associated with each other).
-    if args.input_newick is not None:
-        newick_files = [args.input_newick]
-    else:
-        newick_files = []
-        for file_name in sorted(os.listdir(INPUT_NEWICK_DIR)):
-            file_path = os.path.abspath(os.path.join(INPUT_NEWICK_DIR, file_name))
-            newick_files.append(file_path)
-    if args.input_snps_json is not None:
-        json_files = [args.input_snps_json]
-    else:
-        json_files = []
-        for file_name in sorted(os.listdir(INPUT_JSON_DIR)):
-            file_path = os.path.abspath(os.path.join(INPUT_JSON_DIR, file_name))
-            json_files.append(file_path)
-    if args.input_avg_mq_json is not None:
-        json_avg_mq_files = [args.input_avg_mq_json]
-    else:
-        json_avg_mq_files = []
-        for file_name in sorted(os.listdir(INPUT_JSON_AVG_MQ_DIR)):
-            file_path = os.path.abspath(os.path.join(INPUT_JSON_AVG_MQ_DIR, file_name))
-            json_avg_mq_files.append(file_path)
-
-    multiprocessing.set_start_method('spawn')
-    queue1 = multiprocessing.JoinableQueue()
-    queue2 = multiprocessing.JoinableQueue()
-    num_files = len(newick_files)
-    cpus = set_num_cpus(num_files, args.processes)
-    # Set a timeout for get()s in the queue.
-    timeout = 0.05
-
-    for i, newick_file in enumerate(newick_files):
-        json_file = json_files[i]
-        json_avg_mq_file = json_avg_mq_files[i]
-        queue1.put((newick_file, json_file, json_avg_mq_file))
-
-    # Complete the preprocess_tables task.
-    processes = [multiprocessing.Process(target=preprocess_tables, args=(queue1, annotation_dict, timeout, )) for _ in range(cpus)]
-    for p in processes:
-        p.start()
-    for p in processes:
-        p.join()
-    queue1.join()
-
-    if queue1.empty():
-        queue1.close()
-        queue1.join_thread()
+    preprocess_tables(args.input_newick, args.input_snps_json, args.input_avg_mq_json, annotation_dict)
diff -r 85384a9bfba2 -r abfb861df879 vsnp_build_tables.xml
--- a/vsnp_build_tables.xml	Thu Apr 30 15:55:22 2020 -0400
+++ b/vsnp_build_tables.xml	Sun Jan 03 16:21:29 2021 +0000
@@ -1,5 +1,8 @@
-<tool id="vsnp_build_tables" name="vSNP: build tables" version="1.0.0">
+<tool id="vsnp_build_tables" name="vSNP: build tables" version="@WRAPPER_VERSION@.2" profile="@PROFILE@">
     <description></description>
+    <macros>
+        <import>macros.xml</import>
+    </macros>
     <requirements>
         <requirement type="package" version="1.76">biopython</requirement>
         <requirement type="package" version="0.25.3">pandas</requirement>
@@ -7,78 +10,35 @@
     </requirements>
     <command detect_errors="exit_code"><![CDATA[
 #import re
-#set output_excel_dir = 'output_excel_dir'
-#set input_type = $input_type_cond.input_type
-mkdir $output_excel_dir &&
-#if $input_type == "collection":
-    #set input_newick_dir = 'input_newick_dir'
-    mkdir $input_newick_dir &&
-    #set input_json_avg_mq_dir = 'input_json_avg_mq_dir'
-    mkdir $input_json_avg_mq_dir &&
-    #set input_json_dir = 'input_json_dir'
-    mkdir $input_json_dir &&
-    #for $i in $input_type_cond.input_avg_mq_json_collection:
-        #set file_name = $i.file_name
-        #set identifier = re.sub('[^\s\w\-]', '_', str($i.element_identifier))
-        ln -s '$file_name' '$input_json_avg_mq_dir/$identifier' &&
-    #end for
-    #for $i in $input_type_cond.input_snps_json_collection:
-        #set file_name = $i.file_name
-        #set identifier = re.sub('[^\s\w\-]', '_', str($i.element_identifier))
-        ln -s '$file_name' '$input_json_dir/$identifier' &&
-    #end for
-    #for $i in $input_type_cond.input_newick_collection:
-        #set file_name = $i.file_name
-        #set identifier = re.sub('[^\s\w\-]', '_', str($i.element_identifier))
-        ln -s '$file_name' '$input_newick_dir/$identifier' &&
-    #end for
-#end if
+
+mkdir 'output_excel_dir' &&
+
+## The input_snps_json and input_avg_mq_json identifiers
+## are typically the same string, so we append a uniquq
+## extension to enable the links.
+#set input_snps_json_identifier = re.sub('[^\s\w\-]', '_', str($input_snps_json.element_identifier)) + '.snps'
+ln -s '${input_snps_json}' '${input_snps_json_identifier}' &&
+#set input_avg_mq_json_identifier = re.sub('[^\s\w\-]', '_', str($input_avg_mq_json.element_identifier)) + '.avg_mq'
+ln -s '${input_avg_mq_json}' '${input_avg_mq_json_identifier}' &&
+#set input_newick_identifier = re.sub('[^\s\w\-]', '_', str($input_newick.element_identifier))
+ln -s '${input_newick}' '${input_newick_identifier}' &&
+
 python '$__tool_directory__/vsnp_build_tables.py'
---processes \${GALAXY_SLOTS:-4}
-#if $input_type == "single":
-    --input_avg_mq_json '$input_avg_mq_json'
-    --input_snps_json '$input_snps_json'
-    --input_newick '$input_newick'
-#end if:
-#if str($gbk_cond.gbk_param) == "yes":
-    #set gbk_source_cond = $gbk_cond.gbk_source_cond
-    #set gbk_source = $gbk_source_cond.gbk_source
-    #if str($gbk_source) == "cached":
-        --gbk_file '$gbk_source_cond.gbk_file.fields.path'
+--input_snps_json '${input_snps_json_identifier}'
+--input_avg_mq_json '${input_avg_mq_json_identifier}'
+--input_newick '${input_newick_identifier}'
+#if str($gbk_cond.gbk_param) == 'yes':
+    #if str($gbk_cond.gbk_source_cond.gbk_source) == 'cached':
+        --gbk_file '$gbk_cond.gbk_source_cond.gbk_file.fields.path'
     #else:
-        --gbk_file '$gbk_source_cond.gbk_file'
+        --gbk_file '$gbk_cond.gbk_source_cond.gbk_file'
     #end if
 #end if
 ]]></command>
     <inputs>
-        <conditional name="input_type_cond">
-            <param name="input_type" type="select" label="Choose the category for the files to be analyzed">
-                <option value="single" selected="true">Single files</option>
-                <option value="collection">Collection of files</option>
-            </param>
-            <when value="single">
-                <param name="input_snps_json" type="data" format="json" label="SNPs json file">
-                    <validator type="unspecified_build"/>
-                </param>
-                <param name="input_avg_mq_json" type="data" format="json" label="Average MQ json file">
-                    <validator type="unspecified_build"/>
-                </param>
-                <param name="input_newick" type="data" format="newick" label="Best-scoring ML tree file">
-                    <validator type="unspecified_build"/>
-                </param>
-            </when>
-            <when value="collection">
-                <param name="input_snps_json_collection" format="json" type="data_collection" collection_type="list" label="Collection of SNPs json files">
-                    <validator type="unspecified_build"/>
-                </param>
-                <param name="input_avg_mq_json_collection" format="json" type="data_collection" collection_type="list" label="Collection of average MQ json files">
-                    <validator type="unspecified_build"/>
-                </param>
-                <param name="input_newick_collection" format="newick" type="data_collection" collection_type="list" label="Collection of best-scoring ML tree files">
-                    <validator type="unspecified_build"/>
-                </param>
-            </when>
-        </conditional>
+        <param name="input_snps_json" type="data" format="json" label="SNPs json file"/>
+        <param name="input_avg_mq_json" type="data" format="json" label="Average MQ json file"/>
+        <param name="input_newick" type="data" format="newick" label="Best-scoring ML tree file"/>
         <conditional name="gbk_cond">
             <param name="gbk_param" type="select" label="Use Genbank file?">
                 <option value="yes" selected="true">yes</option>
@@ -93,9 +53,9 @@
                     <when value="cached">
                         <param name="gbk_file" type="select" label="Genbank file">
                             <options from_data_table="vsnp_genbank">
-                                <!-- No filter here! -->
+                                <filter type="data_meta" column="0" key="dbkey" ref="input_avg_mq_json"/>
+                                <validator type="no_options" message="A cached Genbank file is not available for the build associated with the selected average MQ json file"/>
                             </options>
-                            <validator type="no_options" message="A cached Genbank file is not available for the build associated with the selected average MQ json file"/>
                         </param>
                     </when>
                     <when value="history">
@@ -109,8 +69,8 @@
         </conditional>
     </inputs>
     <outputs>
-        <collection name="excel" type="list">
-            <discover_datasets pattern="__name__" directory="output_excel_dir" format="xlsx" />
+        <collection name="excel" type="list" label="${tool.name} on ${on_string}">
+            <discover_datasets pattern="(?P&lt;designation&gt;.+)\.(?P&lt;ext&gt;xlsx)" directory="output_excel_dir"/>
         </collection>
     </outputs>
     <tests>
@@ -119,42 +79,39 @@
             <param name="input_newick" value="input_newick.newick" ftype="newick" dbkey="89"/>
             <param name="input_avg_mq_json" value="input_avg_mq_json.json" ftype="json" dbkey="89"/>
             <param name="gbk_param" value="no"/>
-            <output_collection name="excel" type="list">
-                <element name="cascade_table.xlsx" file="cascade_table.xlsx" ftype="xlsx" compare="sim_size"/>
-                <element name="sort_table.xlsx" file="sort_table.xlsx" ftype="xlsx" compare="sim_size"/>
+            <output_collection name="excel" type="list" count="2">
+                <element name="input_newick_newick_cascade_table" file="cascade_table.xlsx" ftype="xlsx" compare="sim_size"/>
+                <element name="input_newick_newick_sort_table" file="sort_table.xlsx" ftype="xlsx" compare="sim_size"/>
+            </output_collection>
+        </test>
+        <test>
+            <param name="input_snps_json" value="Mbovis-01_snps.json" ftype="json" dbkey="89"/>
+            <param name="input_newick" value="Mbovis-01_snps.newick" ftype="newick" dbkey="89"/>
+            <param name="input_avg_mq_json" value="Mbovis-01_avg_mq.json" ftype="json" dbkey="89"/>
+            <param name="gbk_param" value="no"/>
+            <output_collection name="excel" type="list" count="2">
+                <element name="Mbovis-01_snps_cascade_table" file="Mbovis-01_cascade_table.xlsx" ftype="xlsx" compare="sim_size"/>
+                <element name="Mbovis-01_snps_sort_table" file="Mbovis-01_sort_table.xlsx" ftype="xlsx" compare="sim_size"/>
             </output_collection>
         </test>
         <test>
-            <param name="input_type" value="collection"/>
-            <param name="input_snps_json_collection">
-                <collection type="list">
-                    <element name="Mbovis-01_snps.json" value="Mbovis-01_snps.json" dbkey="89"/>
-                    <element name="Mbovis-01D_snps.json" value="Mbovis-01D_snps.json" dbkey="89"/>
-                    <element name="Mbovis-01D6_snps.json" value="Mbovis-01D6_snps.json" dbkey="89"/>
-                </collection>
-            </param>
-            <param name="input_newick_collection">
-                <collection type="list">
-                    <element name="Mbovis-01_snps.newick" value="Mbovis-01_snps.newick" dbkey="89"/>
-                    <element name="Mbovis-01D_snps.newick" value="Mbovis-01D_snps.newick" dbkey="89"/>
-                    <element name="Mbovis-01D6_snps.newick" value="Mbovis-01D6_snps.newick" dbkey="89"/>
-                </collection>
-            </param>
-            <param name="input_avg_mq_json_collection">
-                <collection type="list">
-                    <element name="Mbovis-01_snps.json" value="Mbovis-01_avg_mq.json" dbkey="89"/>
-                    <element name="Mbovis-01D_snps.json" value="Mbovis-01D_avg_mq.json" dbkey="89"/>
-                    <element name="Mbovis-01D6_snps.json" value="Mbovis-01D6_avg_mq.json" dbkey="89"/>
-                </collection>
-            </param>
+            <param name="input_snps_json" value="Mbovis-01D_snps.json" ftype="json" dbkey="89"/>
+            <param name="input_newick" value="Mbovis-01D_snps.newick" ftype="newick" dbkey="89"/>
+            <param name="input_avg_mq_json" value="Mbovis-01D_avg_mq.json" ftype="json" dbkey="89"/>
             <param name="gbk_param" value="no"/>
-            <output_collection name="excel" type="list">
-                <element name="Mbovis-01D6_snps_cascade_table.xlsx" file="Mbovis-01D6_cascade_table.xlsx" ftype="xlsx" compare="sim_size"/>
-                <element name="Mbovis-01D6_snps_sort_table.xlsx" file="Mbovis-01D6_sort_table.xlsx" ftype="xlsx" compare="sim_size"/>
-                <element name="Mbovis-01D_snps_cascade_table.xlsx" file="Mbovis-01D_cascade_table.xlsx" ftype="xlsx" compare="sim_size"/>
-                <element name="Mbovis-01D_snps_sort_table.xlsx" file="Mbovis-01D_sort_table.xlsx" ftype="xlsx" compare="sim_size"/>
-                <element name="Mbovis-01_snps_cascade_table.xlsx" file="Mbovis-01_cascade_table.xlsx" ftype="xlsx" compare="sim_size"/>
-                <element name="Mbovis-01_snps_sort_table.xlsx" file="Mbovis-01_sort_table.xlsx" ftype="xlsx" compare="sim_size"/>
+            <output_collection name="excel" type="list" count="2">
+                <element name="Mbovis-01D_snps_cascade_table" file="Mbovis-01D_cascade_table.xlsx" ftype="xlsx" compare="sim_size"/>
+                <element name="Mbovis-01D_sort_table" file="Mbovis-01D_sort_table.xlsx" ftype="xlsx" compare="sim_size"/>
+            </output_collection>
+        </test>
+        <test>
+            <param name="input_snps_json" value="Mbovis-01D6_snps.json" ftype="json" dbkey="89"/>
+            <param name="input_newick" value="Mbovis-01D6_snps.newick" ftype="newick" dbkey="89"/>
+            <param name="input_avg_mq_json" value="Mbovis-01D6_avg_mq.json" ftype="json" dbkey="89"/>
+            <param name="gbk_param" value="no"/>
+            <output_collection name="excel" type="list" count="2">
+                <element name="Mbovis-01D6_cascade_table" file="Mbovis-01D6_cascade_table.xlsx" ftype="xlsx" compare="sim_size"/>
+                <element name="Mbovis-01D6_sort_table" file="Mbovis-01D6_sort_table.xlsx" ftype="xlsx" compare="sim_size"/>
             </output_collection>
         </test>
     </tests>
@@ -189,18 +146,8 @@
 
 **Required Options**
 
- * **Choose the category for the files to be analyzed** -  select "Single files" or "Collections of files", then select the appropriate history items (single SNPs json, average MQ json and newick files, or collections of each) based on the selected option.
  * **Use Genbank file** - Select "yes" to annotate the tables using the information in the Genbank file.  Locally cached files, if available, provide the most widely used annotations, but more custom Genbank files can be chosen from the current history.
     </help>
-    <citations>
-        <citation type="bibtex">
-            @misc{None,
-            journal = {None},
-            author = {1. Stuber T},
-            title = {Manuscript in preparation},
-            year = {None},
-            url = {https://github.com/USDA-VS/vSNP},}
-        </citation>
-    </citations>
+    <expand macro="citations"/>
 </tool>