pfam-molstar
Version:
A component for embedding molstar 3D viewer in Pfam
151 lines (126 loc) • 6.13 kB
text/typescript
/**
* Copyright (c) 2018-2020 mol* contributors, licensed under MIT, See LICENSE file for more info.
*
* @author David Sehnal <david.sehnal@gmail.com>
* @author Alexander Rose <alexander.rose@weirdbyte.de>
*/
import { Column, Table } from 'molstar/lib/mol-data/db';
import { toTable } from 'molstar/lib/mol-io/reader/cif/schema';
import { Model, ResidueIndex, Unit, IndexedCustomProperty } from 'molstar/lib/mol-model/structure';
import { StructureElement, Structure } from 'molstar/lib/mol-model/structure/structure';
import { ParamDefinition as PD } from 'molstar/lib/mol-util/param-definition';
import { MmcifFormat } from 'molstar/lib/mol-model-formats/structure/mmcif';
import { PropertyWrapper } from 'molstar/lib/mol-model-props/common/wrapper';
import { CustomProperty } from 'molstar/lib/mol-model-props/common/custom-property';
import { CustomModelProperty } from 'molstar/lib/mol-model-props/common/custom-model-property';
import { CustomPropertyDescriptor } from 'molstar/lib/mol-model/custom-property';
import { dateToUtcString } from 'molstar/lib/mol-util/date';
import { arraySetAdd } from 'molstar/lib/mol-util/array';
export { AfConfidence };
type AfConfidence = PropertyWrapper<{
score: IndexedCustomProperty.Residue<[number, string]>,
category: string[]
}| undefined>
namespace AfConfidence {
export const DefaultServerUrl = '';
export function isApplicable(model?: Model): boolean {
return !!model && Model.isFromPdbArchive(model);
}
export interface Info {
timestamp_utc: string
}
export const Schema = {
local_metric_values: {
label_asym_id: Column.Schema.str,
label_comp_id: Column.Schema.str,
label_seq_id: Column.Schema.int,
metric_id: Column.Schema.int,
metric_value: Column.Schema.float,
model_id: Column.Schema.int,
ordinal_id: Column.Schema.int
}
};
export type Schema = typeof Schema
function tryGetInfoFromCif(categoryName: string, model: Model): undefined | Info {
if (!MmcifFormat.is(model.sourceData) || !model.sourceData.data.frame.categoryNames.includes(categoryName)) {
return;
}
const timestampField = model.sourceData.data.frame.categories[categoryName].getField('metric_value');
if (!timestampField || timestampField.rowCount === 0) return;
return { timestamp_utc: timestampField.str(0) || dateToUtcString(new Date()) };
}
export function fromCif(ctx: CustomProperty.Context, model: Model): AfConfidence | undefined {
let info = tryGetInfoFromCif('ma_qa_metric_local', model);
if (!info) return;
const data = getCifData(model);
const metricMap = createScoreMapFromCif(model, data.residues);
return { info, data: metricMap };
}
export async function fromCifOrServer(ctx: CustomProperty.Context, model: Model, props: AfConfidenceProps): Promise<any> {
const cif = fromCif(ctx, model);
return { value: cif };
}
export function getConfidenceScore(e: StructureElement.Location) {
if (!Unit.isAtomic(e.unit)) return [-1, 'No Score'];
const prop = AfConfidenceProvider.get(e.unit.model).value;
if (!prop || !prop.data) return [-1, 'No Score'];
const rI = e.unit.residueIndex[e.element];
return prop.data.score.has(rI) ? prop.data.score.get(rI)! : [-1, 'No Score'];
}
const _emptyArray: string[] = [];
export function getCategories(structure?: Structure) {
if (!structure) return _emptyArray;
const prop = AfConfidenceProvider.get(structure.models[0]).value;
if (!prop || !prop.data) return _emptyArray;
return prop.data.category;
}
function getCifData(model: Model) {
if (!MmcifFormat.is(model.sourceData)) throw new Error('Data format must be mmCIF.');
return {
residues: toTable(Schema.local_metric_values, model.sourceData.data.frame.categories.ma_qa_metric_local),
};
}
}
export const AfConfidenceParams = {
serverUrl: PD.Text(AfConfidence.DefaultServerUrl, { description: 'JSON API Server URL' })
};
export type AfConfidenceParams = typeof AfConfidenceParams
export type AfConfidenceProps = PD.Values<AfConfidenceParams>
export const AfConfidenceProvider: CustomModelProperty.Provider<AfConfidenceParams, AfConfidence> = CustomModelProperty.createProvider({
label: 'AF Confidence Score',
descriptor: CustomPropertyDescriptor({
name: 'af_confidence_score'
}),
type: 'static',
defaultParams: AfConfidenceParams,
getParams: (data: Model) => AfConfidenceParams,
isApplicable: (data: Model) => AfConfidence.isApplicable(data),
obtain: async (ctx: CustomProperty.Context, data: Model, props: Partial<AfConfidenceProps>) => {
const p = { ...PD.getDefaultValues(AfConfidenceParams), ...props };
return await AfConfidence.fromCifOrServer(ctx, data, p);
}
});
function createScoreMapFromCif(modelData: Model,
residueData: Table<typeof AfConfidence.Schema.local_metric_values>): AfConfidence['data'] | undefined {
const ret = new Map<ResidueIndex, [number, string]>();
const { label_asym_id, label_seq_id, metric_value, _rowCount } = residueData;
const categories: string[] = [];
for (let i = 0; i < _rowCount; i++) {
const confidenceScore = metric_value.value(i);
const idx = modelData.atomicHierarchy.index.findResidue('1', label_asym_id.value(i), label_seq_id.value(i), '');
let confidencyCategory = 'Very low';
if(confidenceScore > 50 && confidenceScore <= 70) {
confidencyCategory = 'Low';
} else if(confidenceScore > 70 && confidenceScore <= 90) {
confidencyCategory = 'Medium';
} else if(confidenceScore > 90) {
confidencyCategory = 'High';
}
ret.set(idx, [confidenceScore, confidencyCategory]);
arraySetAdd(categories, confidencyCategory);
}
return {
score: IndexedCustomProperty.fromResidueMap(ret),
category: categories
};
}