bbi-js

A parser for bigwig and bigbed file formats

Usage

If using locally

const { BigWig } = require('@gmod/bbi')
const file = new BigWig({
  path: 'volvox.bw',
})
;(async () => {
  await file.getHeader()
  const feats = await file.getFeatures('chr1', 0, 100, { scale: 1 })
})()

If using remotely, you can use it in combination with generic-filehandle2 or your own implementation of something like generic-filehandle2 https://github.com/GMOD/generic-filehandle2/

const { BigWig } = require('@gmod/bbi')
const { RemoteFile } = require('generic-filehandle2')

// if running in the browser or newer versions of node.js, RemoteFile will use
// the the global fetch
const file = new BigWig({
  filehandle: new RemoteFile('volvox.bw'),
})

// old versions of node.js without a global fetch, supply custom fetch function
const fetch = require('node-fetch')
const file = new BigWig({
  filehandle: new RemoteFile('volvox.bw', { fetch }),
})

;(async () => {
  await file.getHeader()
  const feats = await file.getFeatures('chr1', 0, 100, { scale: 1 })
})()

Documentation

BigWig/BigBed constructors

Accepts an object containing either

• path - path to a local file
• url - path to a url
• filehandle - a filehandle instance that you can implement as a custom class yourself. path and url are based on https://www.npmjs.com/package/generic-filehandle2 but by implementing a class containing the Filehandle interface specified therein, you can pass it to this module

BigWig

getFeatures(refName, start, end, opts)

• refName - a name of a chromosome in the file
• start - a 0-based half open start coordinate
• end - a 0-based half open end coordinate
• opts.scale - indicates zoom level to use, specified as pxPerBp, e.g. being zoomed out, you might have 100bp per pixel so opts.scale would be 1/100. the zoom level that is returned is the one which has reductionLevel<=2/opts.scale (reductionLevel is a property of the zoom level structure in the bigwig file data)
• opts.basesPerScale - optional, inverse of opts.scale e.g. bpPerPx
• opts.signal - optional, an AbortSignal to halt processing

Returns a promise to an array of features. If an incorrect refName or no features are found the result is an empty array.

Example:

const feats = await bigwig.getFeatures('chr1', 0, 100)
// returns array of features with start, end, score
// coordinates on returned data are are 0-based half open
// no conversion to 1-based as in wig is done)
// note refseq is not returned on the object, it is clearly chr1 from the query though

Understanding scale and reductionLevel

Here is what the reductionLevel structure looks like in a file. The zoomLevel that is chosen is the first reductionLevel<2*opts.basesPerScale (or reductionLevel<2/opts.scale) when scanning backwards through this list

  [ { reductionLevel: 40, ... },
    { reductionLevel: 160, ... },
    { reductionLevel: 640, ... },
    { reductionLevel: 2560, ... },
    { reductionLevel: 10240, ... },
    { reductionLevel: 40960, ... },
    { reductionLevel: 163840, ... } ]

getFeatureStream(refName, start, end, opts)

Same as getFeatures but returns an RxJS observable stream, useful for very large queries

const observer = await bigwig.getFeatureStream('chr1', 0, 100)
observer.subscribe(
  chunk => {
    /* chunk contains array of features with start, end, score */
  },
  error => {
    /* process error */
  },
  () => {
    /* completed */
  },
)

BigBed

getFeatures(refName, start, end, opts)

• refName - a name of a chromosome in the file
• start - a 0-based half open start coordinate
• end - a 0-based half open end coordinate
• opts.signal - optional, an AbortSignal to halt processing

returns a promise to an array of features. no concept of zoom levels is used with bigwig data

getFeatureStream(refName, start, end, opts)

Similar to BigWig, returns an RxJS observable for a observable stream

searchExtraIndex(name, opts)

Specific, to bigbed files, this method searches the bigBed "extra indexes", there can be multiple indexes e.g. for the gene ID and gene name columns. See the usage of -extraIndex in bedToBigBed here https://genome.ucsc.edu/goldenpath/help/bigBed.html

This function accepts two arguments

• name: a string to search for in the BigBed extra indices
• opts: an object that can optionally contain opts.signal, an abort signal

Returns a Promise to an array of Features, with an extra field indicating the field that was matched

How to parse BigBed results

The BigBed line contents are returned as a raw text line e.g. {start: 0, end:100, rest: "ENST00000456328.2\t1000\t..."} where "rest" contains tab delimited text for the fields from 4 and on in the BED format. Since BED files from BigBed format often come with autoSql (a description of all the columns) it can be useful to parse it with BED parser that can handle autoSql. The rest line can be parsed by the @gmod/bed module, which is not by default integrated with this module, but can be combined with it as follows

import { BigBed } from '@gmod/bbi'
import BED from '@gmod/bed'

const ti = new BigBed({
  filehandle: new LocalFile(require.resolve('./data/hg18.bb')),
})
const { autoSql } = await ti.getHeader()
const feats = await ti.getFeatures('chr7', 0, 100000)
const parser = new BED({ autoSql })
const lines = feats.map(f => {
  const { start, end, rest, uniqueId } = f
  return parser.parseLine(`chr7\t${start}\t${end}\t${rest}`, { uniqueId })
})
// @gmod/bbi returns features with {uniqueId, start, end, rest}
// we reconstitute this as a line for @gmod/bed with a template string
// note: the uniqueId is based on file offsets and helps to deduplicate exact feature copies if they exist

Features before parsing with @gmod/bed:

{
  "chromId": 0,
  "start": 64068,
  "end": 64107,
  "rest": "uc003sil.1\t0\t-\t64068\t64068\t255,0,0\t.\tDQ584609",
  "uniqueId": "bb-171"
}

Features after parsing with @gmod/bed:

{
  "uniqueId": "bb-0",
  "chrom": "chr7",
  "chromStart": 54028,
  "chromEnd": 73584,
  "name": "uc003sii.2",
  "score": 0,
  "strand": -1,
  "thickStart": 54028,
  "thickEnd": 54028,
  "reserved": "255,0,0",
  "spID": "AL137655"
}

Academic Use

This package was written with funding from the NHGRI as part of the JBrowse project. If you use it in an academic project that you publish, please cite the most recent JBrowse paper, which will be linked from jbrowse.org.

License

MIT © Colin Diesh