Mercurial > repos > workflow4metabolomics > kmd_hmdb_data_plot
changeset 0:59c8bad5f6bc draft default tip
planemo upload for repository https://github.com/workflow4metabolomics/tools-metabolomics/blob/master/tools/kmd_hmdb_data_plot/ commit 7fa454b6a4268b89fe18043e8dd10f30a7b4c7ca
| author | workflow4metabolomics |
|---|---|
| date | Tue, 29 Aug 2023 09:45:16 +0000 |
| parents | |
| children | |
| files | kmd_hmdb_data_plot.xml kmd_hmdb_interrogator.py kmd_hmdb_plot_generator.py macro.xml test-data/get_data_tol_0.01.tsv |
| diffstat | 5 files changed, 863 insertions(+), 0 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/kmd_hmdb_data_plot.xml Tue Aug 29 09:45:16 2023 +0000 @@ -0,0 +1,176 @@ +<tool id="kmd_hmdb_data_plot" name="KMD HMDB Data Plot" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="21.09"> + <description> + retrieves data from KMD HMDB API and produce plot and tsv file + </description> + <macros> + <import>macro.xml</import> + <token name="@TOOL_VERSION@">1.0.0</token> + <token name="@VERSION_SUFFIX@">0</token> + </macros> + <edam_topics> + <edam_topic>topic_0091</edam_topic> + </edam_topics> + <edam_operations> + <edam_operation>operation_3803</edam_operation> + </edam_operations> + <requirements> + <requirement type="package" version="3.10">python</requirement> + <requirement type="package" version="2.0.3">pandas</requirement> + <requirement type="package" version="5.15.0">plotly</requirement> + <requirement type="package" version="1.0.1">kmd_hmdb_api_client</requirement> + </requirements> + <command detect_errors="exit_code"> +<![CDATA[ +#if "get_data" in str($what.to_do) + python3 '$__tool_directory__/kmd_hmdb_interrogator.py' compound + --mz-ratio '$what.mz_ratio' + --database '$what.database' + --mass-tolerance '$what.mass_tolerance' + #for adduct in $what.adducts + --adducts '$adduct' + #end for + --output-path '$output_path' +#end if + +#if $what.to_do == "get_data_and_produce_plot" + && +#end if + +#if "produce_plot" in str($what.to_do) + python3 '$__tool_directory__/kmd_hmdb_plot_generator.py' plot + + #if "get_data" in str($what.to_do) + --input '$output_path' + #else + --input '$what.tsv_input' + #end if + + #if $what.x_columns + #for x in $what.x_columns + --x-column '$x' + #end for + #end if + + #if $what.y_columns + #for y in $what.y_columns + --y-column '$y' + #end for + #end if + + #if $what.annotation_columns + #for annotation_column in $what.annotation_columns + --annotation-column '$annotation_column' + #end for + #end if + + --output 'out.html' + + && cat 'out.html' > '$output' +#end if +]]> + </command> + + <inputs> + <conditional name="what"> + <param name="to_do" type="select" + label="What to do" + > + <option value="get_data">Only get data</option> + <option value="produce_plot">Only produce plot</option> + <option value="get_data_and_produce_plot" selected="true"> + Get data from database + Produce Plot + </option> + </param> + <when value="produce_plot"> + <expand macro="produce_plot_inputs" /> + <expand macro="not_get_data" /> + </when> + <when value="get_data"> + <expand macro="get_data_inputs" /> + <expand macro="not_produce_plot" /> + </when> + <when value="get_data_and_produce_plot"> + <expand macro="get_data_inputs" /> + <expand macro="not_produce_plot" /> + </when> + </conditional> + </inputs> + + <outputs> + <expand macro="get_data_outputs" /> + <expand macro="produce_plot_outputs" /> + </outputs> + + <tests> + <test> + <!-- #1 get_data with tolerance = 0.01 --> + <param name="to_do" value="get_data" /> + <param name="mass_tolerance" value="0.01" /> + <param name="mz_ratio" value="303.05" /> + <param name="database" value="hmdb" /> + <param name="adducts" value="M+H" /> + <output name="output_path" file="get_data_tol_0.01.tsv" /> + </test> + </tests> + + <help><![CDATA[ + +This tool includes two utilities. +One that retrieves data from the KMD HMDB API formated as a tsv file, +and the other plots those data in a plotly graph. + +The default behavior of the plot is to produce a plot of the kmd in +in function of the nominal mass of the compound. + +Compounds are retrieved using a query with default parameters: + - mz default to @DEFAULT_MZ@ + - mz tolerance defaults to @DEFAULT_TOLERENCE@ + - adduct list defaults to "@DEFAULT_ADDUCT@" + - database default to "@DEFAULT_DATABASE@", and possible values are one of: + + - KMD Metabolites + - HMDB + +Those two utilities are usable independently, or sequentially in galaxy. + +Multiple X / Y values in the X/Y column selection can be +selected to produce a lot of graphs at once. + +For example, imagine you have 5 columns in you tsv file, +and those columns are named: A, B, C, D and F. + +If you choose X = [A, C] and Y = [B], +then you will get two graphs (in one single HTML file) with: + + - f(A) = B + - f(C) = B + +But if you choose multiple values for both X and Y, you get +all combinations of columns X and Y. For example, if you +select X = [A, B] and Y = [C, D, E], then you will get six +graphs on the same plot: + + - f(A) = C + - f(A) = D + - f(A) = E + - f(B) = C + - f(B) = D + - f(B) = E + +All those graph's traces will be tooglable in the HTML page. +So don't hesitate to select a lot of parameters for X and Y! + +]]> + </help> + <citations></citations> + <creator> + <person + honorificPrefix="Mx." + givenName="Lain" + familyName="Pavot" + email="lain.pavot@inrae.fr" + identifier="https://orcid.org/0009-0007-1841-4358" + /> + </creator> + +</tool>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/kmd_hmdb_interrogator.py Tue Aug 29 09:45:16 2023 +0000 @@ -0,0 +1,328 @@ +#!/usr/bin/env python3 + +import csv +import operator + +import click + +import kmd_hmdb_api_client.client +from kmd_hmdb_api_client.api.default import ( + api_annotation_get, + api_compound_find, + api_taxonomy_get, +) + +__version__ = "1.0.0" + + +kmd_hmdb_client = kmd_hmdb_api_client.client.Client( + "https://kmd-hmdb-rest-api.metabolomics-chopin.e-metabohub.fr", + verify_ssl=False, + timeout=500, +) + +find_compound = ( + lambda *args, **kwargs: + api_compound_find.sync(*args, **kwargs, client=kmd_hmdb_client) +) +get_taxonomy = ( + lambda *args, **kwargs: + api_taxonomy_get.sync(*args, **kwargs, client=kmd_hmdb_client) +) +get_annotation = ( + lambda *args, **kwargs: + api_annotation_get.sync(*args, **kwargs, client=kmd_hmdb_client) +) + +positive_adducts = [ + "M+H", + "M+2H", + "M+H+NH4", + "M+H+Na", + "M+H+K", + "M+ACN+2H", + "M+2Na", + "M+H-2H2O", + "M+H-H2O", + "M+NH4", + "M+Na", + "M+CH3OH+H", + "M+K", + "M+ACN+H", + "M+2Na-H", + "M+IsoProp+H", + "M+ACN+Na", + "M+2K+H", + "M+DMSO+H", + "M+2ACN+H", + "2M+H", + "2M+NH4", + "2M+Na", + "2M+K", +] + +negative_adducts = [ + "M-H", + "M-2H", + "M-H2O-H", + "M+Cl", + "M+FA-H", + "M+Hac-H", + "M-H+HCOONa", + "M+Br", + "M+TFA-H", + "2M-H", + "2M+FA-H", + "2M+Hac-H", +] + +adduct_choices = positive_adducts + negative_adducts + +taxonomy_column_choices = [ + "class", + "kingdom", + "molecular_framework", + "sub_class", + "super_class", + "id", +] + +annotation_column_choices = [ + "adduct", + "kendricks_mass", + "kendricks_mass_defect", + "monisotopic_molecular_weight", + "nominal_mass", + "polarity", + "annotation_id", +] + +compound_column_choices = [ + + "database", + "metabolite_name", + "chemical_formula", + "hmdb_id", + "inchikey", + "compound_id", +] + annotation_column_choices + + +@click.group() +def cli(): + pass + + +@cli.command(help="") +@click.option( + "--version", + is_flag=True, +) +@click.option( + "--mz-ratio", + default=[303.05], + show_default=True, + multiple=True, + help="Provide the mz-ratio." +) +@click.option( + "--database", + default=["farid"], + show_default=True, + multiple=True, + help="Provide the database." +) +@click.option( + "--mass-tolerance", + default=10.5, + show_default=True, + help="Provide the mass-tolerance." +) +@click.option( + "--adducts", + default=["M+H"], + type=click.Choice(adduct_choices), + multiple=True, + show_default=True, + show_choices=False, + help="Provide the adducts." +) +@click.option( + "--columns", + default=compound_column_choices[:], + type=click.Choice(compound_column_choices), + multiple=True, + show_default=True, + show_choices=False, + help="Provide the outputed columns." +) +@click.option( + "--output-path", + help="Provide the output path." +) +def compound(*args, **kwargs): + + if kwargs.pop("version"): + print(__version__) + exit(0) + + adducts = kwargs.pop("adducts") + polarity = get_polarity(adducts) + + other_kwargs, compound_kwargs = build_kwargs( + adducts=adducts, + polarity=polarity, + **kwargs + ) + columns = other_kwargs["columns"] + result = find_compound(**compound_kwargs) + result = explode_compounds( + result, + with_annotations=any(map( + columns.__contains__, + annotation_column_choices + )) + ) + check_columns_in_result(result, columns) + output_csv_result( + result, + columns, + other_kwargs.get("output_path"), + delimiter="\t", + ) + + +def explode_compounds(result, with_annotations): + if with_annotations: + return [{ + "database": cpd.database, + "metabolite_name": cpd.metabolite_name, + "chemical_formula": cpd.chemical_formula, + "hmdb_id": cpd.hmdb_id, + "inchikey": cpd.inchikey, + "compound_id": cpd.id, + "adduct": annotation.name, + "kendricks_mass": annotation.kendricks_mass, + "kendricks_mass_defect": annotation.kendricks_mass_defect, + "monisotopic_molecular_weight": + annotation.monisotopic_molecular_weight, + "nominal_mass": annotation.nominal_mass, + "polarity": annotation.polarity, + "annotation_id": annotation.id, + } + for cpd in result + for annotation in cpd.annotations + ] + else: + return [{ + "database": cpd.database, + "metabolite_name": cpd.metabolite_name, + "chemical_formula": cpd.chemical_formula, + "hmdb_id": cpd.hmdb_id, + "inchikey": cpd.inchikey, + "compound_id": cpd.id, + } + for cpd in result + ] + + +@cli.command(help="") +@click.option( + "--id", + type=int, + help="Provide the wanted annotation's id." +) +@click.option( + "--columns", + default=annotation_column_choices[:], + type=click.Choice(annotation_column_choices), + multiple=True, + show_default=True, + show_choices=False, + help="Provide the outputed columns." +) +@click.option( + "--output-path", + help="Provide the output path." +) +def annotation(*args, **kwargs): + result = get_annotation(id=kwargs.pop("id")) + result = [result] + columns = kwargs["columns"] + check_columns_in_result(result, columns) + output_csv_result( + result, + columns, + kwargs.get("output_path") + ) + + +def get_polarity(adducts): + if any(map(positive_adducts.__contains__, adducts)): + return "positive" + if any(map(negative_adducts.__contains__, adducts)): + return "negative" + # polarity = [] + # if any(map(positive_adducts.__contains__, adducts)): + # polarity.append("positive") + # if any(map(negative_adducts.__contains__, adducts)): + # polarity.append("negative") + + +def build_kwargs(**kwargs): + for original, replacement in ( + ("database", "database_list"), + ("polarity", "polarity_list"), + ): + if original in kwargs: + kwargs[replacement] = kwargs.pop(original) + other_kwargs = { + other_arg: kwargs.pop(other_arg) + for other_arg in ("columns", "output_path", "with_annotations") + if other_arg in kwargs + } + return other_kwargs, kwargs + + +def check_columns_in_result(result, columns): + if not result: + return + if not isinstance(result[0], dict): + result = [item.to_dict() for item in result] + keys = result[0].keys() + missing = [ + column for column in columns + if column not in keys + ] + if missing: + if len(missing) == 1: + raise ValueError( + f"Could not find the column {missing[0]} in the results." + ) + else: + raise ValueError( + "Could not find any of the columns " + + ','.join(missing) + + " in the results." + ) + + +def output_csv_result(result, columns, output_path, **csv_parameters): + if not output_path: + raise ValueError("Missing output path. Cannot output CSV results.") + with open(output_path, mode="w", newline='') as output_file: + writer = csv.writer(output_file, **csv_parameters) + write_result(result, columns, writer) + + +def write_result(result, columns, writer): + getters = list(map(operator.itemgetter, columns)) + writer.writerow(columns) + writer.writerows( + (getter(compound) for getter in getters) + for compound in result + ) + + +if __name__ == "__main__": + cli()
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/kmd_hmdb_plot_generator.py Tue Aug 29 09:45:16 2023 +0000 @@ -0,0 +1,174 @@ +#!/usr/bin/env python3 + +import csv +import itertools +import os + +import click + +import plotly.express +import plotly.graph_objects + +__version__ = "1.0.0" + + +@click.group() +def cli(): + pass + + +@cli.command(help="") +@click.option( + "--version", + is_flag=True, + default=False, +) +@click.option( + "--input", + default="./test.tsv", + help="Provide the mz-ratio." +) +@click.option( + "--output", + default="./test.html", + help="Provide the database." +) +@click.option( + "--x-column", + default=["nominal_mass"], + multiple=True, + help="Provide the column names for the X axis.", +) +@click.option( + "--y-column", + default=["kendricks_mass_defect"], + multiple=True, + help="Provide the column names for the Y axis.", +) +@click.option( + "--annotation-column", + multiple=True, + default=[ + "metabolite_name", + "chemical_formula", + ], + help="Provide the columns name for the annotation." +) +def plot(*args, **kwargs): + + if kwargs.pop("version"): + print(__version__) + exit(0) + + input_path = kwargs.pop("input") + data = read_input(input_path, kwargs) + fig = build_fig(*data) + build_html_plot(fig, kwargs.get("output")) + + +def read_input(path: str, kwargs: {}): + if not os.path.exists(path): + raise ValueError(f"The path '{path}' does not exist.") + sep = detect_sep(path) + with open(path) as csv_file: + line_generator = csv.reader(csv_file, delimiter=sep) + first_line = next(line_generator) + all_lines = list(line_generator) + hover_names = ( + "metabolite_name", + "chemical_formula", + ) + annotation_indexes = get_index_of(first_line, hover_names) + ( + x_index, + y_index, + x_column, + y_column, + ) = get_indexes_names( + first_line, + list(kwargs.get("x_column")), + list(kwargs.get("y_column")), + ) + x_lists = [[] for i in range(len(x_index))] + y_lists = [[] for i in range(len(y_index))] + x_column = list(map(first_line.__getitem__, x_index)) + y_column = list(map(first_line.__getitem__, y_index)) + trace_names = [ + f"f({x_column[i]}) = {y_column[i]}" + for i in range(len(x_index)) + ] + hover_names = kwargs["annotation_column"] + annotation_indexes = [ + get_index_of(first_line, column)[0] + for column in hover_names + ] + hover_names = list(map(first_line.__getitem__, annotation_indexes)) + annotations = list() + for line in all_lines: + for i in range(len(x_index)): + x_lists[i].append(float(line[x_index[i]])) + y_lists[i].append(float(line[y_index[i]])) + annotations.append("<br>".join( + f"{hover_names[hover_index]}: {line[index]}" + for hover_index, index in enumerate(annotation_indexes) + )) + return x_lists, y_lists, annotations, trace_names + + +def get_indexes_names(first_line, x_column, y_column): + x_column, y_column = map(list, zip(*itertools.product(x_column, y_column))) + x_index = get_index_of(first_line, x_column) + y_index = get_index_of(first_line, y_column) + for i in range(len(x_index))[::-1]: + if x_index[i] == y_index[i]: + del x_index[i], x_column[i], y_index[i], y_column[i], + return ( + x_index, + y_index, + x_column, + y_column, + ) + + +def get_index_of(first_line, column): + if isinstance(column, (tuple, list)): + return [get_index_of(first_line, x)[0] for x in list(column)] + try: + return [int(column) - 1] + except ValueError: + return [first_line.index(column)] + + +def build_fig(x_lists, y_lists, annotations, trace_names): + fig = plotly.express.scatter() + for i in range(len(x_lists)): + fig.add_trace( + plotly.graph_objects.Scatter( + name=trace_names[i], + x=x_lists[i], + y=y_lists[i], + hovertext=annotations, + mode="markers", + ) + ) + return fig + + +def detect_sep(tabular_file: str) -> str: + with open(tabular_file, "r") as file: + first_line = file.readline() + if len(first_line.split(',')) > len(first_line.split('\t')): + return ',' + return '\t' + + +def build_html_plot(fig, output: str): + return plotly.offline.plot( + fig, + filename=output, + auto_open=False, + ) + + +if __name__ == "__main__": + cli()
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/macro.xml Tue Aug 29 09:45:16 2023 +0000 @@ -0,0 +1,170 @@ +<macros> + + <token name="@DEFAULT_MZ@">303.05</token> + <token name="@DEFAULT_TOLERENCE@">10.0</token> + <token name="@DEFAULT_ADDUCT@">M+H</token> + <token name="@DEFAULT_DATABASE@">HMDB</token> + + <xml name="get_data_inputs"> + <param argument="--mz-ratio" type="float" min="1" max="1000" value="@DEFAULT_MZ@" + help=" + The database will give us all compounds with m/z = + m/zRatio±MassTolerance and we will plot those + compounds. + Choose the mass tolerance according to this information. + " + label="M/z Ratio" + /> + + <param argument="--mass-tolerance" type="float" value="@DEFAULT_TOLERENCE@" + help=" + The database will give us all compounds with m/z = + m/zRatio±MassTolerance and we will plot those + compounds. + Choose the mass tolerance according to this information. + " + label="Mass Tolerance" + /> + + <param argument="--database" type="select" value="@DEFAULT_DATABASE@" + label="Which database to interrogate" + help=" + Those databases are sub-databases of KMD-HMDB Metabolites + and contains compounds with their KMD. + " + > + <option selected="true" value="hmdb">HMDB</option> + <option value="farid">KMD Metabolites</option> + </param> + + <param argument="--adducts" type="select" multiple="true" + label="Adducts" + help="Which adducts to retrieve" + > + <option selected="true" value="M+H">M+H</option> + <option value="M+2H">M+2H</option> + <option value="M+H+NH4">M+H+NH4</option> + <option value="M+H+Na">M+H+Na</option> + <option value="M+H+K">M+H+K</option> + <option value="M+ACN+2H">M+ACN+2H</option> + <option value="M+2Na">M+2Na</option> + <option value="M+H-2H2O">M+H-2H2O</option> + <option value="M+H-H2O">M+H-H2O</option> + <option value="M+NH4">M+NH4</option> + <option value="M+Na">M+Na</option> + <option value="M+CH3OH+H">M+CH3OH+H</option> + <option value="M+K">M+K</option> + <option value="M+ACN+H">M+ACN+H</option> + <option value="M+2Na-H">M+2Na-H</option> + <option value="M+IsoProp+H">M+IsoProp+H</option> + <option value="M+ACN+Na">M+ACN+Na</option> + <option value="M+2K+H">M+2K+H</option> + <option value="M+DMSO+H">M+DMSO+H</option> + <option value="M+2ACN+H">M+2ACN+H</option> + <option value="2M+H">2M+H</option> + <option value="2M+NH4">2M+NH4</option> + <option value="2M+Na">2M+Na</option> + <option value="2M+K">2M+K</option> + <option value="M-H">M-H</option> + <option value="M-2H">M-2H</option> + <option value="M-H2O-H">M-H2O-H</option> + <option value="M+Cl">M+Cl</option> + <option value="M+FA-H">M+FA-H</option> + <option value="M+Hac-H">M+Hac-H</option> + <option value="M-H+HCOONa">M-H+HCOONa</option> + <option value="M+Br">M+Br</option> + <option value="M+TFA-H">M+TFA-H</option> + <option value="2M-H">2M-H</option> + <option value="2M+FA-H">2M+FA-H</option> + <option value="2M+Hac-H">2M+Hac-H</option> + </param> + </xml> + + <xml name="produce_plot_inputs"> + <param name="tsv_input" type="data" format="tsv" + help="Tabular file to use to produce the plot." + label="A Tabular Input File" + /> + <param + name="annotation_columns" + type="data_column" + data_ref="tsv_input" + use_header_names="true" + multiple="true" + optional="true" + help="Select columns to show when a point of the graph is hovered" + label="Annotation columns" + /> + <param + name="x_columns" + type="data_column" + data_ref="tsv_input" + use_header_names="true" + optional="true" + multiple="true" + help=" + Select one or multiple column to use as X values + to generate the graph. See the help section to better + understand the usage of multiple values + " + label="X Axis" + /> + <param + name="y_columns" + type="data_column" + data_ref="tsv_input" + use_header_names="true" + optional="true" + multiple="true" + help=" + Select one or multiple column to use as Y values + to generate the graph. See the help section to better + understand the usage of multiple values + " + label="Y Axis" + /> + </xml> + + <xml name="not_get_data"> + <param name="mz_ratio" value="unknown" type="hidden" /> + <param name="mass_tolerance" value="unknown" type="hidden" /> + <param name="database" value="unknown" type="hidden" /> + <param name="adducts" value="unknown" type="hidden" /> + </xml> + + <xml name="not_produce_plot"> + <param name="tsv_input" value="unknown" type="hidden" /> + <param name="annotation_columns" type="hidden" /> + <param name="x_columns" type="hidden" /> + <param name="y_columns" type="hidden" /> + </xml> + + <xml name="get_data_outputs"> + <data name="output_path" format="tsv" + label="tsv - ${tool.name} on ${what.mz_ratio}±${what.mass_tolerance} - ${what.database}" + > + <filter>"get_data" in str(what['to_do'])</filter> + <actions> + <action name="column_names" type="metadata" + default="database,metabolite_name,chemical_formula,hmdb_id,inchikey,compound_id,adduct,kendricks_mass,kendricks_mass_defect,monisotopic_molecular_weight,nominal_mass,polarity,annotation_id" + /> + </actions> + </data> + </xml> + + <xml name="produce_plot_outputs"> + <data name="output" format="html" + label="html - ${tool.name} on ${ + ' - ' + + str($what['mz_ratio']) + + '±' + str($what['mass_tolerance']) + + ' - ' + str($what['database']) + if 'get_data' in str($what['to_do']) + else ''' ' ''' + $what.csv_input.name + ''' ' ''' + }" + > + <filter>"produce_plot" in str(what['to_do'])</filter> + </data> + </xml> + +</macros> \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/get_data_tol_0.01.tsv Tue Aug 29 09:45:16 2023 +0000 @@ -0,0 +1,15 @@ +database metabolite_name chemical_formula hmdb_id inchikey compound_id adduct kendricks_mass kendricks_mass_defect monisotopic_molecular_weight nominal_mass polarity annotation_id +hmdb 5-(3',5'-Dihydroxyphenyl)-gamma-valerolactone-O-sulphate-O-methyl C12H14O7S HMDB0060031 FXGBBWWEXQWRKV-UHFFFAOYSA-N 193796 M+H 302.715 0.28509 303.053 303.0 positive 3982213 +hmdb Quercetin C15H10O7 HMDB0005794 REFJWTPEDVJJIY-UHFFFAOYSA-N 40965 M+H 302.712 0.288457 303.05 303.0 positive 4379351 +hmdb 8-Chloroinosine C10H11ClN4O5 HMDB0247428 ROPMUQKCJYNROP-UHFFFAOYSA-N 130732 M+H 302.711 0.289311 303.049 303.0 positive 4548699 +hmdb 5-((p-Hydroxybenzylidene)amino)-3-methylisothiazolo(5,4-d)pyrimidine-4,6(5H,7H)-dione C13H10N4O3S HMDB0253558 ALZDMJPUQGYCAX-UHFFFAOYSA-N 68215 M+H 302.716 0.283753 303.055 303.0 positive 4993233 +hmdb 2',4',5,7,8-Pentahydroxyisoflavone C15H10O7 HMDB0033264 LOLNVJIGYUJCIY-UHFFFAOYSA-N 101970 M+H 302.712 0.288457 303.05 303.0 positive 5292330 +hmdb 2-(2-Nitroimidazol-1-yl)-N-(2,2,3,3,3-pentafluoropropyl)acetamide C8H7F5N4O3 HMDB0251710 JGGDSDPOPRWSCX-UHFFFAOYSA-N 9228 M+H 302.713 0.28728 303.051 303.0 positive 7593628 +hmdb 5,6,7,3',4'-Pentahydroxyisoflavone C15H10O7 HMDB0041687 BIDDAFIPYBBDES-UHFFFAOYSA-N 134953 M+H 302.712 0.288457 303.05 303.0 positive 8100148 +hmdb Morin C15H10O7 HMDB0030796 YXOLAZRVSSWPPT-UHFFFAOYSA-N 141800 M+H 302.712 0.288457 303.05 303.0 positive 8184605 +hmdb Tricetin C15H10O7 HMDB0029620 ARSRJFRKVXALTF-UHFFFAOYSA-N 181210 M+H 302.712 0.288457 303.05 303.0 positive 8412749 +hmdb 9-(2,6-Dioxo-3H-purin-9-yl)-3H-purine-2,6-dione C10H6N8O4 HMDB0257773 LLFQXBCTHVBLEI-UHFFFAOYSA-N 108799 M+H 302.72 0.279918 303.058 303.0 positive 8782069 +hmdb 6-Hydroxyluteolin C15H10O7 HMDB0036632 VYAKIUWQLHRZGK-UHFFFAOYSA-N 74622 M+H 302.712 0.288457 303.05 303.0 positive 9521790 +hmdb Pollenin A C15H10O7 HMDB0303704 ZDOTZEDNGNPOEW-UHFFFAOYSA-N 3105 M+H 302.712 0.288457 303.05 303.0 positive 9722226 +hmdb 5,7,8,3',4'-Pentahydroxyisoflavone C15H10O7 HMDB0041689 USQGZNXXBDCNQF-UHFFFAOYSA-N 15604 M+H 302.712 0.288457 303.05 303.0 positive 9958013 +hmdb {2-methoxy-4-[(5-oxooxolan-2-yl)methyl]phenyl}oxidanesulfonic acid C12H14O7S HMDB0127769 FYRRHCSCZYSADR-UHFFFAOYSA-N 51990 M+H 302.715 0.285089 303.053 303.0 positive 10166087