QIIME plugin error from mmvec

Hello,

I’ve been trying to use the emperor plugin to create heatmaps from mmvec using the tutorial posted on github (https://github.com/biocore/mmvec). My code is:
$ qiime mmvec heatmap --i-ranks ranks.qza --m-microbe-metadata-file taxonomy_v2.tsv --m-microbe-metadata-column Taxonomy --m-metabolite-metadata-file metabolite-metadata-v2.txt --m-metabolite-metadata-column Compound_Source --p-level 5 --o-visualization ranks-heatmap.qzv

Plugin error from mmvec:

index 0 is out of bounds for axis 0 with size 0

I went to the Q-Tips meeting previously to help identify the problem and they found mismatched names between my taxonomy file and the ranks file. I’ve since fixed those names and everything should be correct, but I’m still getting the same error. From what I can tell, the same names are used for the feature tables and the metadata. Could someone help me figure out what’s causing these errors?

My QIIME info (installed via conda):
$ qiime info
System versions
Python version: 3.6.7
QIIME 2 release: 2019.10
QIIME 2 version: 2019.10.0
q2cli version: 2019.10.0

Installed plugins
alignment: 2019.10.0
composition: 2019.10.0
cutadapt: 2019.10.0
dada2: 2019.10.0
deblur: 2019.10.0
demux: 2019.10.0
diversity: 2019.10.0
emperor: 2019.10.0
feature-classifier: 2019.10.0
feature-table: 2019.10.0
fragment-insertion: 2019.10.0
gneiss: 2019.10.0
longitudinal: 2019.10.0
metabolomics: 0.0.1
metadata: 2019.10.0
mmvec: 1.0.5
phylogeny: 2019.10.0
quality-control: 2019.10.0
quality-filter: 2019.10.0
sample-classifier: 2019.10.0
taxa: 2019.10.0
types: 2019.10.0
vsearch: 2019.10.0

Thank you,
Jacob

Hi @jhaffner09, what does this command return if you run it with the --verbose flag?

qiime mmvec heatmap --i-ranks ranks.qza --m-microbe-metadata-file taxonomy_v2.tsv --m-microbe-metadata-column Taxonomy --m-metabolite-metadata-file metabolite-metadata-v2.txt --m-metabolite-metadata-column Compound_Source --p-level 5 --o-visualization ranks-heatmap.qzv --verbose

Just to confirm are your sample names between your two datasets matching?

There is also some filtering that is also done internally - samples / features that don’t pass a certain read depth filter criteria will get thrown out. So you may want to check the --min-feature-count and --min-sample-count options (see qiime mmvec paired-omics --help for more options).

Feel free to post your files, since that could help with debugging.

Hi @mortonjt, thank you for your response.
Here is what I got from running the --verbose flag:
$ qiime mmvec heatmap --i-ranks ranks.qza --m-microbe-metadata-file taxonomy_v2.tsv --m-microbe-metadata-column Taxonomy --m-metabolite-metadata-file metabolite-metadata-v2.txt --m-metabolite-metadata-column Compound_Source --p-level 5 --o-visualization ranks-heatmap.qzv --verbose

Traceback (most recent call last):
  File "/opt/anaconda3/envs/qiime2/lib/python3.6/site-packages/q2cli/click/type.py", line 163, in _convert_metadata
    artifact = qiime2.Artifact.load(fp)
  File "/opt/anaconda3/envs/qiime2/lib/python3.6/site-packages/qiime2/sdk/result.py", line 66, in load
    archiver = archive.Archiver.load(filepath)
  File "/opt/anaconda3/envs/qiime2/lib/python3.6/site-packages/qiime2/core/archive/archiver.py", line 299, in load
    archive = cls.get_archive(filepath)
  File "/opt/anaconda3/envs/qiime2/lib/python3.6/site-packages/qiime2/core/archive/archiver.py", line 259, in get_archive
    raise ValueError("%s does not exist." % filepath)
ValueError: taxonomy_v2.tsv does not exist.

During handling of the above exception, another exception occurred:
Traceback (most recent call last):
  File "/opt/anaconda3/envs/qiime2/lib/python3.6/site-packages/q2cli/click/type.py", line 166, in _convert_metadata
    metadata = qiime2.Metadata.load(fp)
  File "/opt/anaconda3/envs/qiime2/lib/python3.6/site-packages/qiime2/metadata/metadata.py", line 309, in load
    return MetadataReader(filepath).read(into=cls,
  File "/opt/anaconda3/envs/qiime2/lib/python3.6/site-packages/qiime2/metadata/io.py", line 47, in __init__
    "(not a directory): %s" % filepath)
qiime2.metadata.io.MetadataFileError: Metadata file path doesn't exist, or the path points to something other than a file. Please check that the path exists, has read permissions, and points to a regular file (not a directory): taxonomy_v2.tsv

There may be more errors present in the metadata file. To get a full report, sample/feature metadata files can be validated with Keemei: https://keemei.qiime2.org

Find details on QIIME 2 metadata requirements here: https://docs.qiime2.org/2019.10/tutorials/metadata/

There was an issue with loading the file taxonomy_v2.tsv as metadata:

  Metadata file path doesn't exist, or the path points to something other than a file. Please check that the path exists, has read permissions, and points to a regular file (not a directory): taxonomy_v2.tsv

  There may be more errors present in the metadata file.  

When I started preparing the files for mmvec, I matched the sample IDs between the 16S and metabolite data, so those should be correct. I’ve also confirmed the “taxonomy_v2.tsv” is in the correct directory with the other files. I had a previous error that was caused by mismatched names between the taxonomy file and the conditionals.tsv file, but since fixed that. I checked to make sure all the other names matched, but I might have missed something or formatted something incorrectly.

I tried to format everything similar to the tutorial files provided in the github. My metadata files used in the previous commands are here: metabolite-metadata-v2.txt (339.2 KB) taxonomy_v2.tsv (608.0 KB) . When I tried uploading the qza files, I got an alert saying I could not post more than two links (since I’m a new user). So, I’ll try posting those in a separate comment below.
Thank you,
Jacob

My qza files are large and exceeded the limit for a post, so I created a shareable OneDrive folder: https://sooners-my.sharepoint.com/:f:/g/personal/jacob_haffner_ou_edu/EgkJNQUL-sRGpLYOtkKVK38BCMZiR8-rOCl7qKsXO20A1A. Let me know if there are issues with the OneDrive link and I can try fixing it. Sorry for any confusion and thank you for your help.

Best,
Jacob

Hmm. The error says that the file doesn’t exist.
So I wager that it is still the problem.

If you ls that file path, does it say the files exists?

Or maybe you need to explicitly import it as a Taxonomy type via qiime tools import --input-file taxonomy_v2.tsv...

I’d double check the taxonomy format

I tried ls in the terminal and it reported the taxonomy_v2.tsv file is in the current working directory, so I’m not entirely sure why QIIME is saying it is not.

I tried importing the file as a Taxonomy type (I was not sure what format best fit, but I went with FeatureData[Taxonomy] – this is a metadata file, but that category seemed most suitable):
$ qiime tools import --type FeatureData[Taxonomy] --input-format TSVTaxonomyFormat --input-path ./taxonomy_v2.tsv --output-path ./TEST.tsv
Imported ./taxonomy_v2.tsv as TSVTaxonomyFormat to ./TEST.tsv

I then tried the first command again and got this error:
(qiime2) ekram-ws4:mmvec_test mccall_lab_imac$ qiime mmvec heatmap --i-ranks ranks.qza --m-microbe-metadata-file TEST.tsv.qza --m-microbe-metadata-column Taxon --m-metabolite-metadata-file metabolite-metadata-v2.txt --m-metabolite-metadata-column Compound_Source --p-level 5 --o-visualization ranks-heatmap.qzv --verbose

/opt/anaconda3/envs/qiime2/lib/python3.6/site-packages/mmvec/heatmap.py:314: UserWarning: Conditional probabilities table and microbe metadata will be filtered to contain only the intersection of IDs in each. If this behavior is undesired, ensure that all microbe IDs are present in both the table and the metadata file warnings.warn(warning, UserWarning) /opt/anaconda3/envs/qiime2/lib/python3.6/site-packages/mmvec/heatmap.py:314: UserWarning: Conditional probabilities table and metabolite metadata will be filtered to contain only the intersection of IDs in each. If this behavior is undesired, ensure that all metabolite IDs are present in both the table and the metadata file warnings.warn(warning, UserWarning) Traceback (most recent call last): File "/opt/anaconda3/envs/qiime2/lib/python3.6/site-packages/q2cli/commands.py", line 328, in __call__ results = action(**arguments) File "</opt/anaconda3/envs/qiime2/lib/python3.6/site-packages/decorator.py:decorator-gen-492>", line 2, in heatmap File "/opt/anaconda3/envs/qiime2/lib/python3.6/site-packages/qiime2/sdk/action.py", line 240, in bound_callable output_types, provenance) File "/opt/anaconda3/envs/qiime2/lib/python3.6/site-packages/qiime2/sdk/action.py", line 445, in _callable_executor_ ret_val = self._callable(output_dir=temp_dir, **view_args) File "/opt/anaconda3/envs/qiime2/lib/python3.6/site-packages/mmvec/q2/_visualizers.py", line 36, in heatmap x_labels, y_labels, level) File "/opt/anaconda3/envs/qiime2/lib/python3.6/site-packages/mmvec/heatmap.py", line 83, in ranks_heatmap cbar_kws={'label': 'Log Conditional\nProbability'}) File "/opt/anaconda3/envs/qiime2/lib/python3.6/site-packages/seaborn/matrix.py", line 1295, in clustermap mask=mask) File "/opt/anaconda3/envs/qiime2/lib/python3.6/site-packages/seaborn/matrix.py", line 776, in __init__ self._preprocess_colors(data, col_colors, axis=1) File "/opt/anaconda3/envs/qiime2/lib/python3.6/site-packages/seaborn/matrix.py", line 842, in _preprocess_colors colors = _convert_colors(colors) File "/opt/anaconda3/envs/qiime2/lib/python3.6/site-packages/seaborn/matrix.py", line 52, in _convert_colors to_rgb(colors[0]) IndexError: index 0 is out of bounds for axis 0 with size 0 Plugin error from mmvec: index 0 is out of bounds for axis 0 with size 0 See above for debug info

I got the same error when using taxonomy_v2.tsv instead of TEST.tsv.qza. Did I pick the wrong format when importing, or is there something else I need to fix?

Thank you!

alright, there is probably something weird going on in your files…

What does the first few lines of your taxonomy_v2.tsv and metabolite-metadata-v2.txt look like?
Your error suggests that something is mislabeled - so either your microbe ids or your metabolite ids are not matching.

Running the following, these are your microbe/metabolite ids in your tables

from biom import Table
import pandas as pd
import qiime2
art = qiime2.Artifact.load('metab_feat_qiime2.qza')
met = art.view(pd.DataFrame)
art = qiime2.Artifact.load('microbe_qiime2.qza')
micro = art.view(pd.DataFrame)
print(met.columns[:10])
print(micro.columns[:10])

Metabolite ids
['1', '3', '4', '5', '6', '7', '9', '10', '11', '12']
Microbe ids
['Parse2906', 'Parse612', 'Parse28', 'Parse1256', 'Parse1026', 'Parse1939', 'Parse2740', 'Parse843', 'Parse1031', 'Parse797']

So somewhere, your microbe ids got fudged and probably don’t agree with your taxonomy output (you should be having hashes). I think you’ll also have issues with taxonomy barplots given the tables you shared.

Okay, so if I’m understanding correctly, there’s mismatched names between the microbe feature table (.qza) and my metadata? Specifically, the taxonomy names don’t match the provided IDs? If that understanding is correct, is this something I can fix in the metadata tables themselves or will I need to redo some of the mmvec analyses I’ve done so far? I thought I had identified and fixed a mismatched name issue previously, but perhaps that just made things worse.

Here’s what my metadata files look like when checking the first few lines:

$ head taxonomy_v2.tsv
Feature ID	Taxon	16S_ID	Kingdom	Phylum	Class	Order	Family	Genus	Species
    Parse1	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella	Prevotella	Bacteria	Bacteroidetes	Bacteroidia	Bacteroidales	Prevotellaceae	Prevotella	
    Parse2	Bacteria;Firmicutes;Clostridia;Clostridiales;Ruminococcaceae;Ruminococcus_g2	Ruminococcus_g2	Bacteria	Firmicutes	Clostridia	Clostridiales	Ruminococcaceae	Ruminococcus_g2	
    Parse3	Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella	Prevotella	Bacteria	Bacteroidetes	Bacteroidia	Bacteroidales	Prevotellaceae	Prevotella	
    Parse4	Bacteria;Firmicutes;Clostridia;Clostridiales;Ruminococcaceae;Faecalibacterium	Faecalibacterium	Bacteria	Firmicutes	Clostridia	Clostridiales	Ruminococcaceae	Faecalibacterium	
    Parse5	Bacteria;Proteobacteria;Gammaproteobacteria;Enterobacteriales;Enterobacteriaceae	Enterobacteriaceae	Bacteria	Proteobacteria	Gammaproteobacteria	Enterobacteriales	Enterobacteriaceae		
    Parse6	Bacteria;Spirochaetes;Spirochaetes_c;Spirochaetales;Spirochaetaceae;Treponema	Treponema	Bacteria	Spirochaetes	Spirochaetes_c	Spirochaetales	Spirochaetaceae	Treponema	
    Parse7	Bacteria;Firmicutes;Erysipelotrichi;Erysipelotrichales;Erysipelotrichaceae;Coprobacillus	Coprobacillus	Bacteria	Firmicutes	Erysipelotrichi	Erysipelotrichales	Erysipelotrichaceae	Coprobacillus	
    Parse8	Bacteria;Proteobacteria;Gammaproteobacteria;Aeromonadales;Succinivibrionaceae;Succinivibrio	Succinivibrio	Bacteria	Proteobacteria	Gammaproteobacteria	Aeromonadales	Succinivibrionaceae	Succinivibrio	
    Parse9	Bacteria;Spirochaetes;Spirochaetes_c;Spirochaetales;Spirochaetaceae;Treponema	Treponema	Bacteria	Spirochaetes	Spirochaetes_c	Spirochaetales	Spirochaetaceae	Treponema	


    $ head metabolite-metadata-v2.txt 
sampleid	m/z	RT	Adduct	Compound_Name	MassDiff	ATTRIBUTE_16s_ID	ATTRIBUTE_16S_shortID	ATTRIBUTE_Country	ATTRIBUTE_IndusScore	ATTRIBUTE_NumIndusScore	ATTRIBUTE_OriginalFileName	ATTRIBUTE_Population	ATTRIBUTE_SampleID	charge	cluster index	componentindex	Compound_Source	Data_Collector	GNPSGROUP:BurkinaFaso	GNPSGROUP:Guayabo	GNPSGROUP:Isolated Traditional (4)	GNPSGROUP:Matses	GNPSGROUP:Norman	GNPSGROUP:Peru	GNPSGROUP:Rural Industrial (2)	GNPSGROUP:Rural Traditional (3)	GNPSGROUP:TamboDeMora	GNPSGROUP:Tunapuco	GNPSGROUP:Urban Industrial (1)	GNPSGROUP:USA	GNPSLibraryURL	GNPSLinkout_Cluster	GNPSLinkout_Network	Instrument	Ion_Source	IonMode	Library_Class	MQScore	MZErrorPPM	name	number of spectra	parent mass	PI	RTMean	shared name	SharedPeaks	Smiles	SpectrumID	sum(precursor intensity)
137.046_0.3805	137.046	0.3805	M+H	HYPOXANTHINE	0.0039978	NA	NA	"USA,BurkinaFaso,Peru"	"Isolated Traditional (4),Rural Industrial (2),Urban Industrial (1),Rural Traditional (3)"	"4,3,2,1"	NA	"Norman,Guayabo,TamboDeMora,Matses,BurkinaFaso,Tunapuco"	NA	0	11178	239	Commercial standard	Prasad	3287.253717	3086.928938	NA	3232.343733	1780.195425	NA	NA	NA	2341.534378	3308.863934	1780.195425	NA	http://gnps.ucsd.edu/ProteoSAFe/gnpslibraryspectrum.jsp?SpectrumID=CCMSLIB00000577903	"https://gnps.ucsd.edu/ProteoSAFe/result.jsp?task=45672509f37244b89c33d0afe8935c88&view=view_all_clusters_withID&show=true#{""main.cluster index_lowerinput"":""11178.0"",""main.cluster index_upperinput"":""11178.0""}"	https://gnps.ucsd.edu/ProteoSAFe/result.jsp?view=network_displayer&componentindex=239&task=45672509f37244b89c33d0afe8935c88&show=true	Q-Exactive Plus	LC-ESI	Positive	1	0.975775	29.1704	11178	108	137.046	Alexandrov Theodore	0.3805	11178	5	C1=NC2=C(N1)C(=O)N=CN2	CCMSLIB00000577903	308143.7386
139.0503_0.3108	139.0503	0.3108	M+H	Spectral Match to Nicotinamide N-oxide from NIST14	0.000289917	NA	NA	"USA,BurkinaFaso,Peru"	"Isolated Traditional (4),Rural Industrial (2),Urban Industrial (1),Rural Traditional (3)"	"4,3,2,1"	NA	"Norman,Guayabo,TamboDeMora,Matses,BurkinaFaso,Tunapuco"	NA	0	1791	-1	Isolated	Data deposited by mjmeehan	556.2729524	958.0821205	NA	625.2442196	684.3900649	NA	NA	NA	663.1911842	785.1071473	684.3900649	NA	http://gnps.ucsd.edu/ProteoSAFe/gnpslibraryspectrum.jsp?SpectrumID=CCMSLIB00003136964	"https://gnps.ucsd.edu/ProteoSAFe/result.jsp?task=45672509f37244b89c33d0afe8935c88&view=view_all_clusters_withID&show=true#{""main.cluster index_lowerinput"":""1791.0"",""main.cluster index_upperinput"":""1791.0""}"	This Node is a Singleton	IT/ion trap	ESI	Positive	3	0.999779	2.08498	1791	108	139.0503	Data from Gabriel Haddad	0.3108	1791	8	N/A	CCMSLIB00003136964	75862.31072
148.0759_3.2191	148.0759	3.2191	M+H	3-METHYL-2-OXINDOLE	0.000106812	NA	NA	"USA,BurkinaFaso,Peru"	"Isolated Traditional (4),Rural Industrial (2),Urban Industrial (1),Rural Traditional (3)"	"4,3,2,1"	NA	"Norman,Guayabo,TamboDeMora,Matses,BurkinaFaso,Tunapuco"	NA	0	4056	596	Commercial	Fernando Vargas	212.78854	106.0768954	NA	107.3272897	57.71567023	NA	NA	NA	96.86660084	128.5895288	57.71567023	NA	http://gnps.ucsd.edu/ProteoSAFe/gnpslibraryspectrum.jsp?SpectrumID=CCMSLIB00005463646	"https://gnps.ucsd.edu/ProteoSAFe/result.jsp?task=45672509f37244b89c33d0afe8935c88&view=view_all_clusters_withID&show=true#{""main.cluster index_lowerinput"":""4056.0"",""main.cluster index_upperinput"":""4056.0""}"	https://gnps.ucsd.edu/ProteoSAFe/result.jsp?view=network_displayer&componentindex=596&task=45672509f37244b89c33d0afe8935c88&show=true	Orbitrap	ESI	Positive	1	0.926001	0.721329	4056	107	148.0759	Dorrestein	3.2191	4056	6	CC1C2=CC=CC=C2NC1=O	CCMSLIB00005463646	12013.46654
195.0651_3.0126	195.0651	3.0126	M+H	Spectral Match to trans-Ferulic acid from NIST14	9.16E-05	NA	NA	"USA,BurkinaFaso,Peru"	"Isolated Traditional (4),Rural Industrial (2),Urban Industrial (1),Rural Traditional (3)"	"4,3,2,1"	NA	"Norman,Guayabo,TamboDeMora,Matses,BurkinaFaso,Tunapuco"	NA	0	8500	165	Isolated	Data deposited by amelnik	9.142905189	10.95795092	NA	79.3812195	23.49560097	NA	NA	NA	11.48764718	57.9869729	23.49560097	NA	http://gnps.ucsd.edu/ProteoSAFe/gnpslibraryspectrum.jsp?SpectrumID=CCMSLIB00003137490	"https://gnps.ucsd.edu/ProteoSAFe/result.jsp?task=45672509f37244b89c33d0afe8935c88&view=view_all_clusters_withID&show=true#{""main.cluster index_lowerinput"":""8500.0"",""main.cluster index_upperinput"":""8500.0""}"	https://gnps.ucsd.edu/ProteoSAFe/result.jsp?view=network_displayer&componentindex=165&task=45672509f37244b89c33d0afe8935c88&show=true	Q-TOF	ESI	Positive	3	0.911395	0.469345	8500	107	195.0651	Data from Rob Knight	3.0126	8500	5	N/A	CCMSLIB00003137490	3871.357412
245.0983_2.3864	245.0983	2.3864	[M+H]+	BIOTIN	0.0032959	NA	NA	"USA,BurkinaFaso,Peru"	"Isolated Traditional (4),Rural Industrial (2),Urban Industrial (1),Rural Traditional (3)"	"4,3,2,1"	NA	"Norman,Guayabo,TamboDeMora,Matses,BurkinaFaso,Tunapuco"	NA	0	24636	2344	isolated	MoNA:VF-NPL-QEHF028111	4.515143699	1.645258231	NA	3.247397651	4.589561014	NA	NA	NA	3.481700531	6.144073684	4.589561014	NA	http://gnps.ucsd.edu/ProteoSAFe/gnpslibraryspectrum.jsp?SpectrumID=CCMSLIB00004721692	"https://gnps.ucsd.edu/ProteoSAFe/result.jsp?task=45672509f37244b89c33d0afe8935c88&view=view_all_clusters_withID&show=true#{""main.cluster index_lowerinput"":""24636.0"",""main.cluster index_upperinput"":""24636.0""}"	https://gnps.ucsd.edu/ProteoSAFe/result.jsp?view=network_displayer&componentindex=2344&task=45672509f37244b89c33d0afe8935c88&show=true	ESI-QFT	N/A	positive	3	0.867222	13.4474	24636	106	245.0983	MoNA	2.3864	24636	6	N/A	CCMSLIB00004721692	452.0527228
263.2369_6.6799	263.2369	6.6799	M+H-H2O	"Spectral Match to Conjugated linoleic acid (9E,11E) from NIST14"	9.16E-05	NA	NA	"USA,BurkinaFaso,Peru"	"Isolated Traditional (4),Rural Industrial (2),Urban Industrial (1),Rural Traditional (3)"	"4,3,2,1"	NA	"Norman,Guayabo,TamboDeMora,Matses,BurkinaFaso,Tunapuco"	NA	0	5499	335	Isolated	Data deposited by amelnik	50.57413483	14.22096432	NA	24.39415133	28.23868293	NA	NA	NA	31.26233591	34.6367702	28.23868293	NA	http://gnps.ucsd.edu/ProteoSAFe/gnpslibraryspectrum.jsp?SpectrumID=CCMSLIB00003136691	"https://gnps.ucsd.edu/ProteoSAFe/result.jsp?task=45672509f37244b89c33d0afe8935c88&view=view_all_clusters_withID&show=true#{""main.cluster index_lowerinput"":""5499.0"",""main.cluster index_upperinput"":""5499.0""}"	https://gnps.ucsd.edu/ProteoSAFe/result.jsp?view=network_displayer&componentindex=335&task=45672509f37244b89c33d0afe8935c88&show=true	HCD	ESI	Positive	3	0.919096	0.347796	5499	108	263.2369	Data from P.Dorrestein	6.6799	5499	10	N/A	CCMSLIB00003136691	3217.37545
272.1711_0.3211	272.1711	0.3211	M+H	Spectral Match to Pro-Arg from NIST14	0.00012207	NA	NA	"USA,BurkinaFaso,Peru"	"Isolated Traditional (4),Rural Industrial (2),Urban Industrial (1),Rural Traditional (3)"	"4,3,2,1"	NA	"Norman,Guayabo,TamboDeMora,Matses,BurkinaFaso,Tunapuco"	NA	0	11602	-1	Isolated	Data deposited by fevargas	12.58430183	11.79805052	NA	31.12912398	15.54470568	NA	NA	NA	15.80852711	24.21593788	15.54470568	NA	http://gnps.ucsd.edu/ProteoSAFe/gnpslibraryspectrum.jsp?SpectrumID=CCMSLIB00003137278	"https://gnps.ucsd.edu/ProteoSAFe/result.jsp?task=45672509f37244b89c33d0afe8935c88&view=view_all_clusters_withID&show=true#{""main.cluster index_lowerinput"":""11602.0"",""main.cluster index_upperinput"":""11602.0""}"	This Node is a Singleton	Q-TOF	ESI	Positive	3	0.720953	0.448506	11602	98	272.1711	Data from Christopher A. Lowry	0.3211	11602	8	N/A	CCMSLIB00003137278	2064.89576
391.188_5.247	391.188	5.247	M-2H2O+H	"""(6R)-2-(hydroxymethyl)-6-((3R,5R,7R,8R,9S,10S,12S,13R,14S,17R)-3,7,12-trihydroxy-10,13-dimethylhexadecahydro-1H-cyclopenta[a]phenanthren-17-yl)heptanoic acid"""	0.00158691	NA	NA	"USA,BurkinaFaso,Peru"	"Isolated Traditional (4),Rural Industrial (2),Urban Industrial (1),Rural Traditional (3)"	"4,3,2,1"	NA	"Norman,Guayabo,TamboDeMora,Matses,BurkinaFaso,Tunapuco"	NA	0	14059	485	crude	Emily Gentry	64.56232761	12.02330053	NA	6.837557082	13.45614515	NA	NA	NA	18.17696299	7.954304517	13.45614515	NA	http://gnps.ucsd.edu/ProteoSAFe/gnpslibraryspectrum.jsp?SpectrumID=CCMSLIB00005465846	"https://gnps.ucsd.edu/ProteoSAFe/result.jsp?task=45672509f37244b89c33d0afe8935c88&view=view_all_clusters_withID&show=true#{""main.cluster index_lowerinput"":""14059.0"",""main.cluster index_upperinput"":""14059.0""}"	https://gnps.ucsd.edu/ProteoSAFe/result.jsp?view=network_displayer&componentindex=485&task=45672509f37244b89c33d0afe8935c88&show=true	qTof	ESI	Positive	1	0.864316	3.67924	14059	105	391.188Dorrestein	431.3176	14059	18	C[[email protected]@H]([[email protected]]1CC[[email protected]]2([H])[[email protected]]1(C)[[email protected]@H](O)C[[email protected]@]3([H])[[email protected]@]2([H])[[email protected]](O)C[[email protected]]4([H])[[email protected]]3(C)CC[[email protected]@H](O)C4)CCCC(CO)C(O)=O	CCMSLIB00005465846	1765.737543
314.2699_7.3373	314.2699	7.3373	M+H	Spectral Match to N-Palmitoylglycine from NIST14	0.00189209	NA	NA	"USA,BurkinaFaso,Peru"	"Isolated Traditional (4),Rural Industrial (2),Urban Industrial (1),Rural Traditional (3)"	"4,3,2,1"	NA	"Norman,Guayabo,TamboDeMora,Matses,BurkinaFaso,Tunapuco"	NA	0	19209	383	Isolated	Data deposited by mjmeehan	2.57055801	0.74362775	NA	1.604878946	0.490755632	NA	NA	NA	1.106978946	1.317783866	0.490755632	NA	http://gnps.ucsd.edu/ProteoSAFe/gnpslibraryspectrum.jsp?SpectrumID=CCMSLIB00003140124	"https://gnps.ucsd.edu/ProteoSAFe/result.jsp?task=da2a1bf6bb58455690219c0abc637a44&view=view_all_clusters_withID&show=true#{""main.cluster index_lowerinput"":""19209.0"",""main.cluster index_upperinput"":""19209.0""}"	https://gnps.ucsd.edu/ProteoSAFe/result.jsp?view=network_displayer&componentindex=383&task=da2a1bf6bb58455690219c0abc637a44&show=true	HCD	ESI	Positive	3	0.859573	6.02063	19209	102	314.2699	Data from Jessica Metcalf	7.3373	19209	6	N/A	CCMSLIB00003140124	130.8071214

Hi @jhaffner09, sorry if this wasn’t clear before, but your FeatureIDs don’t look like they were generated from a standard qiime2 workflow.

How did you perform your taxonomy classification and denoising? Did you perform these outside of the qiime2 workflow?

If you haven’t already, I’d recommend to check out the Moving pictures tutorial, in particular running DADA2 / Deblur and Taxonomy classification

https://docs.qiime2.org/2020.8/tutorials/moving-pictures/#option-1-dada2
https://docs.qiime2.org/2020.8/tutorials/moving-pictures/#taxonomic-analysis

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Hi @mortonjt, these files were created from a QIIME1 workflow. These 16S data were part of an earlier analysis from a few years ago and we wanted to try sticking to that original analysis as much as possible, so the files were reprocessed using the QIIME1 pipeline. So, things like taxonomic classification were done outside QIIME2. When preparing files for mmvec, I converted the new QIIME1 files to QIIME2 formats (ie, biom --> qza), but hadn’t considered that this might affect mmvec. Thank you for catching that – I will process these files through the QIIME2 workflow and get back to you.