adding bucket table import from GNPS

README.md

@@ -70,6 +70,13 @@ This function will take as input an existing GNPS Molecular Networking task and
 qiime metabolomics import-gnpsnetworkingclusteringtask
 ```
 
+#### MS2 GNPS Clustering Bucket Table Import Command
+This function will take as input an existing Bucket Table from GNPS Molecular Networking Clustering to produce a biom qza file.
+
+```
+qiime metabolomics import-gnpsnetworkingclusteringbuckettable
+```
+
 #### MZmine2 Feature Import Command
 This function will take as input a feature quantification file from MZmine2 and a manifest file and produce a biom qza file.
 
@@ -159,11 +166,11 @@ Select Export->CSV File
 
 ### Manifest File Format
 
-The manifest file specifies the location of the files that will be processed by the metabolomics plugin. It is a .CSV (comma separated value) formatted table that contains two columns. The first column indicates the ‘sample-sample’ for each file, while the second column indicates its corresponding relative file path (relative to where qiime commands are called). The gnps-clustering and the mzmine2-clustering tools are using both the same manifest file.
+The manifest file specifies the location of the files that will be processed by the metabolomics plugin. It is a .CSV (comma separated value) formatted table that contains two columns. The first column indicates the ‘sample_name’ for each file, while the second column indicates its corresponding relative file path (relative to where qiime commands are called). The gnps-clustering and the mzmine2-clustering tools are using both the same manifest file.
 
-View of the manifest file (.CSV format). The first column indicates the ‘sample-same for each file, while the second column indicates its corresponding relative file path. The example file can be [downloaded here](https://github.com/mwang87/q2_metabolomics/raw/master/q2_metabolomics/tests/data/manifest.tsv).
+View of the manifest file (.CSV format). The first column indicates the sample_name for each file, while the second column indicates its corresponding relative file path. The example file can be [downloaded here](https://github.com/mwang87/q2_metabolomics/raw/master/q2_metabolomics/tests/data/manifest.tsv).
 
-| sample-name        | filepaths           |
+| sample_name        | filepaths           |
 | ------------- |:-------------:|
 | sample1      | data/121114_nanoDESI_polar_ISP2_control_DD_MS2.mzXML |
 | sample2      | data/121119_VM37_FT-IT.mzXML |
@@ -267,7 +274,7 @@ qiime diversity pcoa \
  --output-dir pcoa_canberra_qiime2
 ```
 
-To create an interactive ordination plot of the above created PCoA with integrated sample metadata use the qiime emperor plot function. Make sure that the ‘sample-id’s provided in the metadata file correspond to the sample-ids in the canberra distance_matrix.qza file:
+To create an interactive ordination plot of the above created PCoA with integrated sample metadata use the qiime emperor plot function. Make sure that the ‘sample_name’s provided in the metadata file correspond to the sample_name in the canberra distance_matrix.qza file:
 
 ```
 qiime emperor plot \
@@ -372,7 +379,7 @@ qiime diversity pcoa \
   --output-dir pcoa_canberra_qiime2
 ```
 
-To create an interactive ordination plot of the above created PCoA with integrated sample metadata use the qiime emperor plot function. Make sure that the ‘sample-id’s provided in the metadata file correspond to the sample-ids in the canberra distance_matrix.qza file:
+To create an interactive ordination plot of the above created PCoA with integrated sample metadata use the qiime emperor plot function. Make sure that the ‘sample_name’s provided in the metadata file correspond to the sample_name in the canberra distance_matrix.qza file:
 
 ```
 qiime emperor plot \
@@ -541,7 +548,7 @@ qiime diversity pcoa \
   --output-dir pcoa_canberra_qiime2
 ```
 
-To create an interactive ordination plot of the above created PCoA with integrated sample metadata use the qiime emperor plot function. Make sure that the ‘sample-id’s provided in the metadata file correspond to the sample-ids in the canberra distance_matrix.qza file:
+To create an interactive ordination plot of the above created PCoA with integrated sample metadata use the qiime emperor plot function. Make sure that the ‘sample_name’s provided in the metadata file correspond to the sample_name in the canberra distance_matrix.qza file:
 
 ```
 qiime emperor plot \
@@ -642,7 +649,7 @@ qiime diversity pcoa \
 --output-dir pcoa_canberra_qiime2
 ```
 
-To create an interactive ordination plot of the above created PCoA with integrated sample metadata use the qiime emperor plot function. Make sure that the ‘sample-id’s provided in the metadata file correspond to the sample-ids in the canberra distance_matrix.qza file:
+To create an interactive ordination plot of the above created PCoA with integrated sample metadata use the qiime emperor plot function. Make sure that the ‘sample_name’s provided in the metadata file correspond to the sample_name in the canberra distance_matrix.qza file:
 
 ```
 qiime emperor plot \

examplefiles/metadata_long.txt

@@ -1,4 +1,4 @@
-sample-id	filepath	description	age	age_units	sample_set	fermented	empo_1	empo_2	empo_3
+sample_name	filepath	description	age	age_units	sample_set	fermented	empo_1	empo_2	empo_3
 G95952	G95952_BA6_01_31659.mzXML	milk with yogurt culture	0	hrs	A	yes	host associated	animal	animal secretion
 G95982	G95982_repeat_RB8_01_31543.mzXML	milk with yogurt culture	11	hrs	A	yes	host associated	animal	animal secretion
 G96107	G96107_repeat_RD4_01_31616.mzXML	milk with yogurt culture	24	hrs	A	yes	host associated	animal	animal secretion

meta.yaml

@@ -1,6 +1,6 @@
 package:
   name: q2-metabolomics
-  version: "0.0.3"
+  version: "0.0.5"
 
 source:
   path: .

q2_metabolomics/__init__.py

@@ -1,6 +1,7 @@
 
 from ._method import import_gnpsnetworkingclustering
 from ._method import import_gnpsnetworkingclusteringtask
+from ._method import import_gnpsnetworkingclusteringbuckettable
 from ._method import import_mzmine2
 
 __version__ = "0.0.1"

q2_metabolomics/_method.py

@@ -171,6 +171,19 @@ def import_gnpsnetworkingclusteringtask(manifest: str, taskid: str) -> biom.Tabl
     return _create_table_from_task(taskid, sid_map)
 
 
+def import_gnpsnetworkingclusteringbuckettable(manifest: str, buckettable: str) -> biom.Table:
+    sid_map = {}
+    with open(manifest) as csvfile:
+        reader = csv.DictReader(csvfile)
+        for row in reader:
+            sid = row["sample_name"]
+            filepath = row["filepath"]
+            fileidentifier = os.path.basename(os.path.splitext(filepath)[0])
+            sid_map[fileidentifier] = sid
+
+    return _create_table_from_buckettable(buckettable, sid_map)
+
+
 def _create_table_from_task(task_id, sid_map):
     """Pulling down BioM"""
     url_to_biom = "http://gnps.ucsd.edu/ProteoSAFe/DownloadResultFile?task=%s&block=main&file=cluster_buckets/" % (
@@ -181,16 +194,20 @@ def _create_table_from_task(task_id, sid_map):
     local_file.write(requests.get(url_to_biom).text)
     local_file.close()
 
-    with open(f.name) as fh:
-        table = biom.Table.from_tsv(fh, None, None, None)
-
-    table.update_ids(sid_map, axis='sample', inplace=True)
+    table = _create_table_from_buckettable(f.name, sid_map)
 
     # Cleanup Tempfile
     os.unlink(f.name)
 
     return table
 
+def _create_table_from_buckettable(buckettable_path, sid_map):
+    with open(buckettable_path) as fh:
+        table = biom.Table.from_tsv(fh, None, None, None)
+
+    table.update_ids(sid_map, axis='sample', inplace=True)
+
+    return table
 
 def import_mzmine2(manifest: str, quantificationtable: str) -> biom.Table:
     """Loading Manifest Mapping"""

q2_metabolomics/plugin_setup.py

@@ -20,7 +20,7 @@
     input_descriptions={},
     outputs=[('feature_table', FeatureTable[Frequency])],
     parameter_descriptions={
-        'manifest': 'Manifest file for describing information about each file. Headers of sample-id and filepath',
+        'manifest': 'Manifest file for describing information about each file. Headers of sample_name and filepath',
         'credentials': 'GNPS login credentials json'
     },
     output_descriptions={'feature_table': 'Resulting feature table'},
@@ -36,7 +36,7 @@
     input_descriptions={},
     outputs=[('feature_table', FeatureTable[Frequency])],
     parameter_descriptions={
-        'manifest': 'Manifest file for describing information about each file. Headers of sample-id and filepath',
+        'manifest': 'Manifest file for describing information about each file. Headers of sample_name and filepath',
         'taskid': 'GNPS Task ID'
     },
     output_descriptions={'feature_table': 'Resulting feature table'},
@@ -45,6 +45,22 @@
     citations=[]
 )
 
+plugin.methods.register_function(
+    function=q2_metabolomics.import_gnpsnetworkingclusteringbuckettable,
+    inputs={},
+    parameters={'manifest': qiime2.plugin.Str, 'buckettable': qiime2.plugin.Str},
+    input_descriptions={},
+    outputs=[('feature_table', FeatureTable[Frequency])],
+    parameter_descriptions={
+        'manifest': 'Manifest file for describing information about each file. Headers of sample_name and filepath',
+        'buckettable': 'Path to Bucket Table from GNPS Molecular Networking Clustering'
+    },
+    output_descriptions={'feature_table': 'Resulting feature table'},
+    name='GNPS Metabolomics MS/MS Spectral Counts - Import Existing GNPS Bucket Table',
+    description=("Computes feature BioM for metabolomics by importing GNPS Molecular Networking Bucket Table"),
+    citations=[]
+)
+
 
 plugin.methods.register_function(
     function=q2_metabolomics.import_mzmine2,
@@ -53,7 +69,7 @@
     input_descriptions={},
     outputs=[('feature_table', FeatureTable[Frequency])],
     parameter_descriptions={
-        'manifest': 'Manifest file for describing information about each file. Headers of sample-id and filepath',
+        'manifest': 'Manifest file for describing information about each file. Headers of sample_name and filepath',
         'quantificationtable': 'Quantification Table output from MZMine2'
     },
     output_descriptions={'feature_table': 'Resulting feature table'},