Published
Edited
Mar 16, 2021
1 fork
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) {
var i, j;
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 count_column_name = timepoint;
var new_item = {
"SYMBOL": item.SYMBOL,
"ENSEMBL": item.Ensembl_IDs,
"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,
"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),
]
},
})
}
}
//selected_gene_objects = gene_objects_with_names.filter(item => selected_genes.includes(item.NAME))
gene_list = gene_objects_with_names.map(item => item.NAME)
gene_objects_with_names = gene_objects.map(item => {item.NAME = item.SYMBOL + ", " + item.Ensembl_IDs; return item})
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));
}
query_options_for_gene_list = {
return {
method: 'POST',
body: JSON.stringify({
//columns: ["Ensembl_IDs", "SYMBOL"],
condition: {
or: [
{fuzzySearch: [{ "column": ["SYMBOL"] }, keyword]},
{fuzzySearch: [{ "column": ["SYMBOL"] }, keyword2]},
]
},
orderBy: [{ expression: { column: ["SYMBOL"] }, ordering: "ascending" }],
})
}
}
normalized_dataset_url = api_url + dataset_id + "/versions/3/data"
dataset_url = api_url + dataset_id + "/versions/4/data"
api_url = "https://api.edelweissdata.com/datasets/"
dataset_id = "7bff53eb-7c1a-4875-b6b1-cd002e7e9c4c"
import {Select, Range, Toggle, Search, Table, Text} from "@observablehq/inputs"
import {vl} from "@vega/vega-lite-api"
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