Public
Edited
Feb 26, 2022
1 fork
keyValuePairs = [
{"Parameter" : "Organ", "Value": summary_metadata["Assay"]["Organ"]},
{"Parameter" : "Organism", "Value": summary_metadata["Assay"]["Organism"]},
{"Parameter" : "Information domain", "Value": summary_metadata["Information domain"]},
{"Parameter" : "Exposure time", "Value": summary_metadata["Assay"]["Treatment"]["Exposure time"]},
{"Parameter" : "Modality", "Value": summary_metadata["Assay"]["Treatment"]["Treatment modality"]},
{"Parameter" : "Method name", "Value": summary_metadata["Method name"]},
]
compound_info = summary_metadata.Compound.filter(obj => obj["Compound name as used in metadata sheet"] == selected_compound)
compounds_table = {
var tbl = [];
var i = 0;
for (var compound of compound_info) {
tbl.push({
//'Compound': compound['Compound name of actual form used'], // removed, as several entries seem faulty. Which column represents the compound name in the form it has in the real data, form which the triplets have been created??
'Compound': compound['Compound name as used in metadata sheet'],
'Form': compound['Compound form'],
'CAS': compound['CAS number'],
'SMILES': compound['SMILES'],
'Mol': svgs[i],
})
i = i + 1
}
return tbl;
};
svgs = Promise.all(promises)
// Copied from PCR analysis notebook
promises = {
var promises = [];
for (var compound of compound_info) {
const smiles = compound.SMILES;
const safeSmiles = encodeURIComponent(smiles);
const svg_url = "https://chemidconvert.cloud.douglasconnect.com/v1/asSvg?width=200&height=200&smiles=" + safeSmiles;
const svg = fetch(svg_url).then(response => response.text());
promises.push(svg);
}
return promises;
}
endpoint1_data = summary_data.map(obj => {
return {
"Exposure time": obj["Exposure time"],
"BMC10": obj["Endpoint 1 BMC10"].toFixed(2),
"BMC25": obj["Endpoint 1 BMC25"].toFixed(2),
"BMC50": obj["Endpoint 1 BMC50"].toFixed(2),
"slope": obj["Endpoint 1 slope"].toFixed(2),
"hit call": obj["Endpoint 1 hit call"],
"warnings": obj["Endpoint 1 warnings"]
}
})
endpoint2_data = summary_data.map(obj => {
return {
"Exposure time": obj["Exposure time"],
"BMC10": obj["Endpoint 2 BMC10"].toFixed(2),
"BMC25": obj["Endpoint 2 BMC25"].toFixed(2),
"BMC50": obj["Endpoint 2 BMC50"].toFixed(2),
"slope": obj["Endpoint 2 slope"].toFixed(2),
"hit call": obj["Endpoint 2 hit call"],
"warnings": obj["Endpoint 2 warnings"]
}
})
timepoints = summary_data.map(row => row["Exposure time"])
compounds = summary_metadata.Compound.map(obj => obj["Compound name as used in metadata sheet"])
raw_data = fetch_dataset_to_array(base_url_edelweiss, raw_dataset_id, query)
raw_metadata = fetch_dataset_to_array(base_url_edelweiss, raw_dataset_id, {}, "metadata")
processed_data = fetch_dataset_to_array(base_url_edelweiss, processed_dataset_id, query)
processed_metadata = fetch_dataset_to_array(base_url_edelweiss, processed_dataset_id, {}, "metadata")
summary_data = fetch_dataset_to_array(base_url_edelweiss, summary_dataset_id, query)
summary_metadata = fetch_dataset_to_array(base_url_edelweiss, summary_dataset_id, {}, "metadata")
query = {
return {
method: 'POST',
body: JSON.stringify({
condition: {
exactSearch: [{ column: ["Compound"] }, selected_compound],
}
})
}
}
// Create function to fetch data. Query options defined in cell above
// Pass in an optional variable 'meta' to the function to make it request the metadata!
function fetch_dataset_to_array(base_url, dataset_id, query_options, datatype) {
if (datatype == "metadata") {
var dataset_url = base_url + dataset_id + "/versions/latest/metadata"
} else {
var dataset_url = base_url + dataset_id + "/versions/latest/data"
}
return fetch(dataset_url, query_options).then(response_dataset => {
if (!response_dataset.ok) throw new Error(response_dataset.status);
if (datatype == null)
return response_dataset.json().then(json => json.results.map(x => x.data));
else if (datatype == 'metadata' )
return response_dataset.json();
})
}
summary_dataset_id = "284fb3cc-13d5-4284-89c5-e6ede945bff5"
processed_dataset_id = "ef4840ac-d495-4409-8170-05055501848c"
raw_dataset_id = "b37eace9-3181-43a5-8da9-760607e5ba97"
// Set url for data base
base_url_edelweiss = 'https://api.develop.edelweiss.douglasconnect.com/datasets/'
// Import selection, range and toggle tools from inputs notebook
import {Select, Range, Toggle} from "@observablehq/inputs"
// Import vega-lite visualization library
import {vl} from "@vega/vega-lite-api"
// Import libraries for data table rendering
import {render_data_table} from '@info474/utilities'
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
