Read and write the PLINK BED format, simply and efficiently.
Features:
- Fast multi-threaded Rust engine.
- Supports all Python indexing methods. Slice data by individuals (samples) and/or SNPs (variants).
- Used by PySnpTools, FaST-LMM, and PyStatGen.
- Supports PLINK 1.9.
pip install bed-reader
Read genomic data from a .bed file.
>>> import numpy as np
>>> from bed_reader import open_bed, sample_file
>>>
>>> file_name = sample_file("small.bed")
>>> bed = open_bed(file_name)
>>> val = bed.read()
>>> print(val)
[[ 1. 0. nan 0.]
[ 2. 0. nan 2.]
[ 0. 1. 2. 0.]]
>>> del bedRead every second individual and SNPs (variants) from 20 to 30.
>>> file_name2 = sample_file("some_missing.bed")
>>> bed2 = open_bed(file_name2)
>>> val2 = bed2.read(index=np.s_[::2,20:30])
>>> print(val2.shape)
(50, 10)
>>> del bed2List the first 5 individual (sample) ids, the first 5 SNP (variant) ids, and every unique chromosome. Then, read every value in chromosome 5.
>>> with open_bed(file_name2) as bed3:
... print(bed3.iid[:5])
... print(bed3.sid[:5])
... print(np.unique(bed3.chromosome))
... val3 = bed3.read(index=np.s_[:,bed3.chromosome=='5'])
... print(val3.shape)
['iid_0' 'iid_1' 'iid_2' 'iid_3' 'iid_4']
['sid_0' 'sid_1' 'sid_2' 'sid_3' 'sid_4']
['1' '10' '11' '12' '13' '14' '15' '16' '17' '18' '19' '2' '20' '21' '22'
'3' '4' '5' '6' '7' '8' '9']
(100, 6)
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent