bed-reader 1.0.6

Read and write the PLINK BED format, simply and efficiently.
Documentation

bed-reader

Read and write the PLINK BED format, simply and efficiently.

Highlights

  • Fast and multi-threaded
  • Supports many indexing methods. Slice data by individuals (samples) and/or SNPs (variants).
  • The Python-facing APIs for this library is used by PySnpTools, FaST-LMM, and PyStatGen.
  • Supports PLINK 1.9.
  • Read data locally or from the cloud, efficiently and directly.

Install

Full version: Can read local and cloud files

cargo add bed-reader

Minimal version: Can read local files, only

cargo add bed-reader --no-default-features

Examples

Read all genotype data from a .bed file.

use ndarray as nd;
use bed_reader::{Bed, ReadOptions, assert_eq_nan, sample_bed_file};

let file_name = sample_bed_file("small.bed")?;
let mut bed = Bed::new(file_name)?;
let val = ReadOptions::builder().f64().read(&mut bed)?;

assert_eq_nan(
    &val,
    &nd::array![
        [1.0, 0.0, f64::NAN, 0.0],
        [2.0, 0.0, f64::NAN, 2.0],
        [0.0, 1.0, 2.0, 0.0]
    ],
);
# use bed_reader::BedErrorPlus; // '#' needed for doctest
# Ok::<(), Box<BedErrorPlus>>(())

Read every second individual (samples) and SNPs (variants) 20 to 30.

use ndarray::s;

let file_name = sample_bed_file("some_missing.bed")?;
let mut bed = Bed::new(file_name)?;
let val = ReadOptions::builder()
    .iid_index(s![..;2])
    .sid_index(20..30)
    .f64()
    .read(&mut bed)?;

assert!(val.dim() == (50, 10));
# use bed_reader::{Bed, ReadOptions, BedErrorPlus, assert_eq_nan, sample_bed_file}; // '#' needed for doctest
# Ok::<(), Box<BedErrorPlus>>(())

List the first 5 individual (sample) ids, the first 5 SNP (variant) ids, and every unique chromosome. Then, read every genomic value in chromosome 5.

# use ndarray::s; // '#' needed for doctest
# use bed_reader::{Bed, ReadOptions, assert_eq_nan, sample_bed_file};
# let file_name = sample_bed_file("some_missing.bed")?;
use std::collections::HashSet;

let mut bed = Bed::new(file_name)?;
println!("{:?}", bed.iid()?.slice(s![..5])); // Outputs ndarray: ["iid_0", "iid_1", "iid_2", "iid_3", "iid_4"]
println!("{:?}", bed.sid()?.slice(s![..5])); // Outputs ndarray: ["sid_0", "sid_1", "sid_2", "sid_3", "sid_4"]
println!("{:?}", bed.chromosome()?.iter().collect::<HashSet<_>>());
// Outputs: {"12", "10", "4", "8", "19", "21", "9", "15", "6", "16", "13", "7", "17", "18", "1", "22", "11", "2", "20", "3", "5", "14"}
let val = ReadOptions::builder()
    .sid_index(bed.chromosome()?.map(|elem| elem == "5"))
    .f64()
    .read(&mut bed)?;

assert!(val.dim() == (100, 6));
# use bed_reader::BedErrorPlus; // '#' needed for doctest
# Ok::<(), Box<BedErrorPlus>>(())

From the cloud: open a file and read data for one SNP (variant) at index position 2. (See "Cloud URLs and CloudFile Examples" for details specifying a file in the cloud.)

use ndarray as nd;
use bed_reader::{assert_eq_nan, BedCloud, ReadOptions};
# #[cfg(feature = "tokio")] Runtime::new().unwrap().block_on(async { // '#' needed for doc test
let url = "https://raw.githubusercontent.com/fastlmm/bed-sample-files/main/small.bed";
let mut bed_cloud = BedCloud::new(url).await?;
let val = ReadOptions::builder().sid_index(2).f64().read_cloud(&mut bed_cloud).await?;
assert_eq_nan(&val, &nd::array![[f64::NAN], [f64::NAN], [2.0]]);
# Ok::<(), Box<dyn std::error::Error>>(()) }).unwrap();
# #[cfg(feature = "tokio")] use {tokio::runtime::Runtime, bed_reader::BedErrorPlus};

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