Published
Edited
Apr 27, 2021
reshaped_rnaseq_data = reshape_rnaseq_data(rnaseq_data)
reshaped_normalized_rnaseq_data = reshape_normalized_rnaseq_data(normalized_rnaseq_data)
timepoints = ["24h", "48h", "72h", "144h"]
reshape_rnaseq_data = function(data) {
let i, j;
const arr = [];
//const processedEnsemblIds = new Set()
for (i = 0; i < data.length; i++) {
//const ensemblId = data[i].Ensembl_IDs
//if (!processedEnsemblIds.has(ensemblId)) {
//processedEnsemblIds.add(ensemblId)
for (j = 0; j < timepoints.length; j++) {
const item = data[i];
const timepoint = timepoints[j];
const count_column_name = timepoint;
var new_item = {
"SYMBOL": item.SYMBOL,
"ENSEMBL": item.Ensembl_IDs,
"PATHWAY": item.Pathway,
"TIMEPOINT": timepoint,
"COUNT": item[count_column_name],
"RESCALED_COUNT": item[count_column_name] / max_count,
"SAMPLE": item.SYMBOL + ", " + item.Ensembl_IDs,
};
arr.push(new_item);
}
//}
}
return arr;
}
replicates = [1, 2, 3]
reshape_normalized_rnaseq_data = function(data) {
var i, j, k;
var arr = [];
for (i = 0; i < data.length; i++) {
for (j = 0; j < timepoints.length; j++) {
var item = data[i];
var timepoint = timepoints[j];
var average_count = 0;
for (k = 0; k < replicates.length; k++) {
var count_column_name = timepoint + "_Replicate" + replicates[k];
average_count = average_count + item[count_column_name];
}
average_count = average_count / (replicates.length);
var new_item = {
"SYMBOL": item.SYMBOL,
"ENSEMBL": item.Ensembl_IDs,
"PATHWAY": item.Pathway,
"TIMEPOINT": timepoint,
"COUNT": average_count,
"SAMPLE": item.SYMBOL + ", " + item.Ensembl_IDs,
};
arr.push(new_item);
}
}
return arr;
}
normalized_rnaseq_data = fetch_dataset_to_array(normalized_dataset_url, query_options_for_rnaseq_data)
rnaseq_data = fetch_dataset_to_array(dataset_url, query_options_for_rnaseq_data)
query_options_for_rnaseq_data = {
return {
method: 'POST',
body: JSON.stringify({
condition: {
containedIn: [
{column: ["Ensembl_IDs"]}, selected_gene_objects.map(item => item.Ensembl_IDs),
]
},
})
}
}
gene_list = gene_objects_with_names.map(item => item.NAME)
gene_objects_with_names = _.chain(gene_objects).uniqBy(item => item.Ensembl_IDs).map(item => {item.NAME = item.SYMBOL + ", " + item.Ensembl_IDs; return item}).value()
max_count = {
var maximums = [];
var i;
for (i = 0; i < timepoints.length; i++) {
var timepoint = timepoints[i];
maximums.push(
Math.max(...gene_objects.map(item => item[timepoint]))
)
}
return Math.max(...maximums);
}
gene_objects = fetch_dataset_to_array(dataset_url, query_options_for_gene_list)
function dynamicSort(property) {
var sortOrder = 1;
if(property[0] === "-") {
sortOrder = -1;
property = property.substr(1);
}
return function (a,b) {
/* next line works with strings and numbers,
* and you may want to customize it to your needs
*/
var result = (a[property] < b[property]) ? -1 : (a[property] > b[property]) ? 1 : 0;
return result * sortOrder;
}
}
function fetch_dataset_to_array(dataset_url, query_options) {
return fetch(dataset_url, query_options).then(response_dataset => {
if (!response_dataset.ok) throw new Error(response_dataset.status);
return response_dataset.json();}).then(json => json.results.map(x => x.data));
}
mutable gene_fragments = ["CYP"]
query_options_for_gene_list = {
let condition;
if (toxicologicalCategory === "") {
if (majorPathwayDropdown !== "" || majorMinorPathwayDropdown !== "") {
condition = ({
and: [
({ fuzzySearch: [({"column": ["Pathway"]}), majorPathwayDropdown]}),
({ fuzzySearch: [({"column": ["Pathway"]}), majorMinorPathwayDropdown]}),
]
})
}
else {
let conditionFragments = []
if (gene_fragments.length > 0) {
conditionFragments = (gene_fragments.map(item => ({fuzzySearch: [({ "column": ["SYMBOL"] }), item]})))
}
if (pathwaySearch !== "") {
conditionFragments.push(({fuzzySearch: [({ "column": ["Pathway"] }), pathwaySearch]}))
}
if (conditionFragments.length > 0) {
condition = ({ and: conditionFragments
})
}
}
}
else {
condition = ({
exactSearch: [({"column": ["Toxicological.categories"]}), toxicologicalCategory]
})
}
return {
method: 'POST',
body: JSON.stringify({
//columns: ["Ensembl_IDs", "SYMBOL"],
condition: condition,
orderBy: [{ expression: { column: ["SYMBOL"] }, ordering: "ascending" }],
})
}
}
pathways_dropdown = unique_pathways.unshift("", "NA")
unique_pathways = Array.from(new Set(all_pathways.map(item => item.Pathway)))
all_pathways = fetch_dataset_to_array(dataset_url, {
method: 'POST',
body: JSON.stringify({
columns: ["Pathway"],
condition: {
"not": [
{ "exactSearch": [{ "column": ["Pathway"] }, "NA"] }
]
},
orderBy: [{ expression: { column: ["Pathway"] }, ordering: "ascending" }],
})
})
toxicologicalCategoryVocuabulary = [
"",
"Efflux transporter(hepatocyte to bile canaliculi)",
"Uptake transporters (Blood to hepatocytes)",
"Important liver CYPs (Less abundant)",
"Efflux transporters (Hepatocytes to blood)",
"Important liver CYPs (Most abundant)"
]
normalized_dataset_url = api_url + dataset_id + "/versions/3/data"
dataset_url = api_url + dataset_id + "/versions/9/data"
api_url = "https://api.edelweissdata.com/datasets/"
dataset_id = "7bff53eb-7c1a-4875-b6b1-cd002e7e9c4c"
unshift = {major_pathways.unshift("")}
inshift2 = {major_minor_pathways.unshift("")}
major_pathways = major_pathways_records.map(item => item["Major pathways"])
major_minor_pathways = major_minor_pathways_records.map(item => item["Maroj and Minor Pathways"])
major_minor_pathways_records = fetch_dataset_to_array(major_minor_pathway_dataset_url, {
method: 'POST',
body: JSON.stringify({
columns: ["Maroj and Minor Pathways"],
orderBy: [{ expression: { column: ["Maroj and Minor Pathways"] }, ordering: "ascending" }],
})
})
major_pathways_records = fetch_dataset_to_array(major_pathway_dataset_url, {
method: 'POST',
body: JSON.stringify({
columns: ["Major pathways"],
orderBy: [{ expression: { column: ["Major pathways"] }, ordering: "ascending" }],
})
})
major_minor_pathway_dataset_url = api_url + major_minor_pathway_dataset_id + "/versions/latest/data"
major_pathway_dataset_url = api_url + major_pathway_dataset_id + "/versions/latest/data"
major_pathway_dataset_id = "7f87c58f-be80-4f91-8c86-57493e1f1fa6"
major_minor_pathway_dataset_id = "962c1d9c-ae72-4f1f-aa57-435d3097a2cd"
import {Select, Range, Toggle, Search, Table, Text} from "@observablehq/inputs"
_ = require("lodash");
import {vl} from "@vega/vega-lite-api"
import {html} from "@observablehq/htl"
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