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Annotate RegionDS

After getting an RegionDS from DMR calling or any other genome region sets, we can annotate the regions with other epigenomic profiles or genomic features stored in the BigWig or BED format.

For example, in this section, we will annotate the DMR RegionDS with chromatin accessibility profiles and some general genomic features.

Import

import pandas as pd
import pathlib
from ALLCools.mcds import RegionDS

Open RegionDS

dmr_ds = RegionDS.open('test_HIP')
dmr_ds

Using dmr as region_dim

<xarray.RegionDS>
Dimensions:      (count_type: 2, dmr: 132, sample: 20)
Coordinates:
  * count_type   (count_type) <U3 'mc' 'cov'
  * dmr          (dmr) <U9 'chr1-0' 'chr1-1' ... 'chr19-122' 'chr19-123'
    dmr_chrom    (dmr) <U5 'chr1' 'chr1' 'chr1' ... 'chr19' 'chr19' 'chr19'
    dmr_end      (dmr) int64 10002172 10003542 10003967 ... 5099203 5099952
    dmr_length   (dmr) int64 2 305 54 2 2 2 2 ... 589 924 632 842 195 399 335
    dmr_ndms     (dmr) int64 1 7 2 1 1 1 1 13 3 2 1 ... 2 1 2 7 13 19 9 9 3 6 13
    dmr_start    (dmr) int64 10002170 10003237 10003913 ... 5098804 5099617
  * sample       (sample) <U18 'snm3C_ASC' 'snm3C_CA1' ... 'snmC_ODC' 'snmC_OPC'
Data variables:
    dmr_da       (sample, dmr, count_type) uint32 4294967295 ... 4294967295
    dmr_da_frac  (sample, dmr) float32 1.0 1.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0
    dmr_state    (sample, dmr) int8 -1 0 0 1 -1 -1 -1 0 0 ... 0 0 0 0 0 0 0 0 0
Attributes:
    region_dim:          dmr
    region_ds_location:  /home/hanliu/pkg/ALLCools_pycharm/docs/allcools/clus...
    chrom_size_path:     /home/hanliu/pkg/ALLCools_pycharm/docs/allcools/clus...

xarray.RegionDS

• Dimensions:
  • count_type: 2
  • dmr: 132
  • sample: 20
• Coordinates: (8)
  • count_type
    (count_type)
    <U3
    'mc' 'cov'

    array(['mc', 'cov'], dtype='<U3')

  • dmr
    (dmr)
    <U9
    'chr1-0' 'chr1-1' ... 'chr19-123'

    array(['chr1-0', 'chr1-1', 'chr1-2', 'chr1-3', 'chr1-4', 'chr1-5', 'chr1-6',
           'chr1-7', 'chr19-0', 'chr19-1', 'chr19-2', 'chr19-3', 'chr19-4',
           'chr19-5', 'chr19-6', 'chr19-7', 'chr19-8', 'chr19-9', 'chr19-10',
           'chr19-11', 'chr19-12', 'chr19-13', 'chr19-14', 'chr19-15', 'chr19-16',
           'chr19-17', 'chr19-18', 'chr19-19', 'chr19-20', 'chr19-21', 'chr19-22',
           'chr19-23', 'chr19-24', 'chr19-25', 'chr19-26', 'chr19-27', 'chr19-28',
           'chr19-29', 'chr19-30', 'chr19-31', 'chr19-32', 'chr19-33', 'chr19-34',
           'chr19-35', 'chr19-36', 'chr19-37', 'chr19-38', 'chr19-39', 'chr19-40',
           'chr19-41', 'chr19-42', 'chr19-43', 'chr19-44', 'chr19-45', 'chr19-46',
           'chr19-47', 'chr19-48', 'chr19-49', 'chr19-50', 'chr19-51', 'chr19-52',
           'chr19-53', 'chr19-54', 'chr19-55', 'chr19-56', 'chr19-57', 'chr19-58',
           'chr19-59', 'chr19-60', 'chr19-61', 'chr19-62', 'chr19-63', 'chr19-64',
           'chr19-65', 'chr19-66', 'chr19-67', 'chr19-68', 'chr19-69', 'chr19-70',
           'chr19-71', 'chr19-72', 'chr19-73', 'chr19-74', 'chr19-75', 'chr19-76',
           'chr19-77', 'chr19-78', 'chr19-79', 'chr19-80', 'chr19-81', 'chr19-82',
           'chr19-83', 'chr19-84', 'chr19-85', 'chr19-86', 'chr19-87', 'chr19-88',
           'chr19-89', 'chr19-90', 'chr19-91', 'chr19-92', 'chr19-93', 'chr19-94',
           'chr19-95', 'chr19-96', 'chr19-97', 'chr19-98', 'chr19-99', 'chr19-100',
           'chr19-101', 'chr19-102', 'chr19-103', 'chr19-104', 'chr19-105',
           'chr19-106', 'chr19-107', 'chr19-108', 'chr19-109', 'chr19-110',
           'chr19-111', 'chr19-112', 'chr19-113', 'chr19-114', 'chr19-115',
           'chr19-116', 'chr19-117', 'chr19-118', 'chr19-119', 'chr19-120',
           'chr19-121', 'chr19-122', 'chr19-123'], dtype='<U9')

  • dmr_chrom
    (dmr)
    <U5
    'chr1' 'chr1' ... 'chr19' 'chr19'

    array(['chr1', 'chr1', 'chr1', 'chr1', 'chr1', 'chr1', 'chr1', 'chr1',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19'], dtype='<U5')

  • dmr_end
    (dmr)
    int64
    10002172 10003542 ... 5099952

    array([10002172, 10003542, 10003967, 10005479, 10007099, 10007758,
           10008881, 10009927,  5000194,  5000343,  5000715,  5001506,
            5001549,  5003862,  5004785,  5005319,  5005816,  5006789,
            5008015,  5008084,  5008130,  5008805,  5010091,  5011268,
            5011724,  5011926,  5012429,  5012955,  5013312,  5013603,
            5014250,  5014562,  5014921,  5015099,  5016145,  5016791,
            5017181,  5017656,  5018165,  5018340,  5019014,  5019656,
            5020498,  5021894,  5022034,  5022299,  5023452,  5025645,
            5026013,  5026581,  5028070,  5029223,  5029469,  5029930,
            5031623,  5032343,  5033665,  5035273,  5036180,  5036656,
            5037800,  5040294,  5040872,  5042216,  5042541,  5043207,
            5043818,  5045206,  5046083,  5046469,  5047139,  5050164,
            5051764,  5054110,  5055419,  5056089,  5056189,  5056309,
            5056642,  5057152,  5057233,  5059280,  5059541,  5060286,
            5060636,  5061033,  5061586,  5062181,  5062652,  5063270,
            5064727,  5065461,  5065765,  5066074,  5066405,  5067916,
            5069149,  5070132,  5071656,  5071800,  5073983,  5074921,
            5076037,  5076379,  5077207,  5078490,  5078805,  5080040,
            5080229,  5081032,  5081240,  5081796,  5082893,  5083285,
            5083313,  5083586,  5084274,  5084686,  5086323,  5087101,
            5087539,  5089466,  5089734,  5090283,  5091820,  5092737,
            5094022,  5095601,  5097380,  5097870,  5099203,  5099952])

  • dmr_length
    (dmr)
    int64
    2 305 54 2 2 ... 842 195 399 335

    array([   2,  305,   54,    2,    2,    2,    2,  440,  171,   12,    2,
              2,   22,  504,  128,  146,  201,    2,    2,    2,    2,  182,
              2,  246,    2,    2,  101,  343,   49,  183,    2,   88,    2,
              2,   89,  385,   55,    2,    2,   48,  144,    2,    2,  821,
              2,    2,  306,  913,    2,   71,   91,   22,   21,  149,    2,
              2,    2,    2,   57,   76,    2,  532,  552,  211,    2,  243,
              2,    2,  322,   63,    2, 2314, 1029, 2090,    2,   58,    2,
             67,    2,  253,    2, 1351,    2,  478,    2,  127,   42,   43,
              2,   46,    2,  482,   14,    2,    2,  773,  760,    2,  661,
            126,  345,  687,  537,    2,  469,  866,    2,    2,   59,  315,
              2,  368, 1053,  367,    2,    2,  186,    2,  391,  108,  323,
             31,    2,  138,  434,  589,  924,  632,  842,  195,  399,  335])

  • dmr_ndms
    (dmr)
    int64
    1 7 2 1 1 1 1 ... 13 19 9 9 3 6 13

    array([ 1,  7,  2,  1,  1,  1,  1, 13,  3,  2,  1,  1,  2,  5,  2,  3,  2,
            1,  1,  1,  1,  4,  1,  2,  1,  1,  3,  6,  4,  3,  1,  4,  1,  1,
            3,  7,  4,  1,  1,  2,  4,  1,  1,  8,  1,  1,  9, 14,  1,  5,  3,
            2,  2,  2,  1,  1,  1,  1,  2,  2,  1, 17, 11,  3,  1,  5,  1,  1,
            9,  4,  1, 33, 28, 56,  1,  2,  1,  2,  1,  4,  1, 20,  1,  7,  1,
            2,  2,  2,  1,  2,  1,  7,  3,  1,  1, 15, 29,  1, 20,  4,  8, 13,
            4,  1,  5, 15,  1,  1,  4,  6,  1, 10, 47,  9,  1,  1,  2,  1,  3,
            4,  8,  2,  1,  2,  7, 13, 19,  9,  9,  3,  6, 13])

  • dmr_start
    (dmr)
    int64
    10002170 10003237 ... 5099617

    array([10002170, 10003237, 10003913, 10005477, 10007097, 10007756,
           10008879, 10009487,  5000023,  5000331,  5000713,  5001504,
            5001527,  5003358,  5004657,  5005173,  5005615,  5006787,
            5008013,  5008082,  5008128,  5008623,  5010089,  5011022,
            5011722,  5011924,  5012328,  5012612,  5013263,  5013420,
            5014248,  5014474,  5014919,  5015097,  5016056,  5016406,
            5017126,  5017654,  5018163,  5018292,  5018870,  5019654,
            5020496,  5021073,  5022032,  5022297,  5023146,  5024732,
            5026011,  5026510,  5027979,  5029201,  5029448,  5029781,
            5031621,  5032341,  5033663,  5035271,  5036123,  5036580,
            5037798,  5039762,  5040320,  5042005,  5042539,  5042964,
            5043816,  5045204,  5045761,  5046406,  5047137,  5047850,
            5050735,  5052020,  5055417,  5056031,  5056187,  5056242,
            5056640,  5056899,  5057231,  5057929,  5059539,  5059808,
            5060634,  5060906,  5061544,  5062138,  5062650,  5063224,
            5064725,  5064979,  5065751,  5066072,  5066403,  5067143,
            5068389,  5070130,  5070995,  5071674,  5073638,  5074234,
            5075500,  5076377,  5076738,  5077624,  5078803,  5080038,
            5080170,  5080717,  5081238,  5081428,  5081840,  5082918,
            5083311,  5083584,  5084088,  5084684,  5085932,  5086993,
            5087216,  5089435,  5089732,  5090145,  5091386,  5092148,
            5093098,  5094969,  5096538,  5097675,  5098804,  5099617])

  • sample
    (sample)
    <U18
    'snm3C_ASC' ... 'snmC_OPC'

    array(['snm3C_ASC', 'snm3C_CA1', 'snm3C_CA23', 'snm3C_CGE-VipLamp5',
           'snm3C_DG', 'snm3C_MGC', 'snm3C_MGE-PvSst', 'snm3C_NonN', 'snm3C_ODC',
           'snm3C_OPC', 'snmC_ASC', 'snmC_CA1', 'snmC_CA23', 'snmC_CGE-VipLamp5',
           'snmC_DG', 'snmC_MGC', 'snmC_MGE-PvSst', 'snmC_NonN', 'snmC_ODC',
           'snmC_OPC'], dtype='<U18')

• Data variables: (3)
  • dmr_da
    (sample, dmr, count_type)
    uint32
    ...

    array([[[4294967295, 4294967295],
            [4294967295, 4294967295],
            ...,
            [4294967295, 4294967295],
            [4294967295, 4294967295]],
    
           [[4294967295, 4294967295],
            [4294967295, 4294967295],
            ...,
            [4294967295, 4294967295],
            [4294967295, 4294967295]],
    
           ...,
    
           [[4294967295, 4294967295],
            [4294967295, 4294967295],
            ...,
            [4294967295, 4294967295],
            [4294967295, 4294967295]],
    
           [[4294967295, 4294967295],
            [4294967295, 4294967295],
            ...,
            [4294967295, 4294967295],
            [4294967295, 4294967295]]], dtype=uint32)

  • dmr_da_frac
    (sample, dmr)
    float32
    ...

    array([[1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           ...,
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.]], dtype=float32)

  • dmr_state
    (sample, dmr)
    int8
    ...

    array([[-1,  0,  0, ...,  0,  0,  0],
           [ 0,  1,  0, ...,  0, -1,  0],
           [ 0,  1,  0, ..., -1, -1,  0],
           ...,
           [ 0,  0, -1, ...,  0,  0,  0],
           [ 1,  0,  0, ...,  0,  1,  0],
           [ 0,  0, -1, ...,  0,  0,  0]], dtype=int8)

• Attributes: (3)

  region_dim :

  dmr

  region_ds_location :

  /home/hanliu/pkg/ALLCools_pycharm/docs/allcools/cluster_level/RegionDS/test_HIP

  chrom_size_path :

  /home/hanliu/pkg/ALLCools_pycharm/docs/allcools/cluster_level/RegionDS/test_HIP/chrom_sizes.txt

DMR Chromatin Accessibility Profile (BigWig)

For example, here we annotate cluster-matched chromatin accessibility profiles from a mouse hippocampus snATAC-seq dataset. Each profile is stored in BigWig format. The annotate_by_bigwigs method of RegionDS can help scan the regions on each BigWig file, resulting a new data variable stored in the RegionDS

# prepare the bigwig tab-separated table, first column is cluster name, second column is BigWig path
bigwig_dir = '../../data/HIPBulk/atac_bulk/'
bigwigs = pd.Series({
    p.name.split('.')[0].split('_')[-1]: str(p)
    for p in pathlib.Path(bigwig_dir).glob('HIP_snATAC_*.bw')
})
bigwigs.to_csv('test_bigwig.csv', header=False)
bigwigs

CA23    ../../data/HIPBulk/atac_bulk/HIP_snATAC_CA23.bw
CGE      ../../data/HIPBulk/atac_bulk/HIP_snATAC_CGE.bw
ASC      ../../data/HIPBulk/atac_bulk/HIP_snATAC_ASC.bw
MGE      ../../data/HIPBulk/atac_bulk/HIP_snATAC_MGE.bw
CA1      ../../data/HIPBulk/atac_bulk/HIP_snATAC_CA1.bw
ODC      ../../data/HIPBulk/atac_bulk/HIP_snATAC_ODC.bw
MGC      ../../data/HIPBulk/atac_bulk/HIP_snATAC_MGC.bw
NonN    ../../data/HIPBulk/atac_bulk/HIP_snATAC_NonN.bw
OPC      ../../data/HIPBulk/atac_bulk/HIP_snATAC_OPC.bw
DG        ../../data/HIPBulk/atac_bulk/HIP_snATAC_DG.bw
dtype: object

dmr_ds.annotate_by_bigwigs(slop=250,
                           bigwig_table='test_bigwig.csv',
                           dim='snATAC',
                           cpu=30)

Use chunk size 1

# the annotated matrix are stored in a new data variable
dmr_ds['dmr_snATAC_da']

<xarray.DataArray 'dmr_snATAC_da' (dmr: 132, snATAC: 10)>
dask.array<open_dataset-03cdf5fb902771957a3508f7758e6aeedmr_snATAC_da, shape=(132, 10), dtype=float32, chunksize=(132, 1), chunktype=numpy.ndarray>
Coordinates:
  * dmr         (dmr) <U9 'chr1-0' 'chr1-1' 'chr1-2' ... 'chr19-122' 'chr19-123'
    dmr_chrom   (dmr) <U5 'chr1' 'chr1' 'chr1' ... 'chr19' 'chr19' 'chr19'
    dmr_end     (dmr) int64 10002172 10003542 10003967 ... 5099203 5099952
    dmr_length  (dmr) int64 2 305 54 2 2 2 2 440 ... 589 924 632 842 195 399 335
    dmr_ndms    (dmr) int64 1 7 2 1 1 1 1 13 3 2 1 ... 2 1 2 7 13 19 9 9 3 6 13
    dmr_start   (dmr) int64 10002170 10003237 10003913 ... 5098804 5099617
  * snATAC      (snATAC) <U4 'CA23' 'CGE' 'ASC' 'MGE' ... 'NonN' 'OPC' 'DG'

xarray.DataArray

'dmr_snATAC_da'

• dmr: 132
• snATAC: 10

• dask.array<chunksize=(132, 1), meta=np.ndarray>

  Array Chunk Bytes 5.28 kB 528 B Shape (132, 10) (132, 1) Count 11 Tasks 10 Chunks Type float32 numpy.ndarray

• Coordinates: (7)
  • dmr
    (dmr)
    <U9
    'chr1-0' 'chr1-1' ... 'chr19-123'

    array(['chr1-0', 'chr1-1', 'chr1-2', 'chr1-3', 'chr1-4', 'chr1-5', 'chr1-6',
           'chr1-7', 'chr19-0', 'chr19-1', 'chr19-2', 'chr19-3', 'chr19-4',
           'chr19-5', 'chr19-6', 'chr19-7', 'chr19-8', 'chr19-9', 'chr19-10',
           'chr19-11', 'chr19-12', 'chr19-13', 'chr19-14', 'chr19-15', 'chr19-16',
           'chr19-17', 'chr19-18', 'chr19-19', 'chr19-20', 'chr19-21', 'chr19-22',
           'chr19-23', 'chr19-24', 'chr19-25', 'chr19-26', 'chr19-27', 'chr19-28',
           'chr19-29', 'chr19-30', 'chr19-31', 'chr19-32', 'chr19-33', 'chr19-34',
           'chr19-35', 'chr19-36', 'chr19-37', 'chr19-38', 'chr19-39', 'chr19-40',
           'chr19-41', 'chr19-42', 'chr19-43', 'chr19-44', 'chr19-45', 'chr19-46',
           'chr19-47', 'chr19-48', 'chr19-49', 'chr19-50', 'chr19-51', 'chr19-52',
           'chr19-53', 'chr19-54', 'chr19-55', 'chr19-56', 'chr19-57', 'chr19-58',
           'chr19-59', 'chr19-60', 'chr19-61', 'chr19-62', 'chr19-63', 'chr19-64',
           'chr19-65', 'chr19-66', 'chr19-67', 'chr19-68', 'chr19-69', 'chr19-70',
           'chr19-71', 'chr19-72', 'chr19-73', 'chr19-74', 'chr19-75', 'chr19-76',
           'chr19-77', 'chr19-78', 'chr19-79', 'chr19-80', 'chr19-81', 'chr19-82',
           'chr19-83', 'chr19-84', 'chr19-85', 'chr19-86', 'chr19-87', 'chr19-88',
           'chr19-89', 'chr19-90', 'chr19-91', 'chr19-92', 'chr19-93', 'chr19-94',
           'chr19-95', 'chr19-96', 'chr19-97', 'chr19-98', 'chr19-99', 'chr19-100',
           'chr19-101', 'chr19-102', 'chr19-103', 'chr19-104', 'chr19-105',
           'chr19-106', 'chr19-107', 'chr19-108', 'chr19-109', 'chr19-110',
           'chr19-111', 'chr19-112', 'chr19-113', 'chr19-114', 'chr19-115',
           'chr19-116', 'chr19-117', 'chr19-118', 'chr19-119', 'chr19-120',
           'chr19-121', 'chr19-122', 'chr19-123'], dtype='<U9')

  • dmr_chrom
    (dmr)
    <U5
    'chr1' 'chr1' ... 'chr19' 'chr19'

    array(['chr1', 'chr1', 'chr1', 'chr1', 'chr1', 'chr1', 'chr1', 'chr1',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19'], dtype='<U5')

  • dmr_end
    (dmr)
    int64
    10002172 10003542 ... 5099952

    array([10002172, 10003542, 10003967, 10005479, 10007099, 10007758,
           10008881, 10009927,  5000194,  5000343,  5000715,  5001506,
            5001549,  5003862,  5004785,  5005319,  5005816,  5006789,
            5008015,  5008084,  5008130,  5008805,  5010091,  5011268,
            5011724,  5011926,  5012429,  5012955,  5013312,  5013603,
            5014250,  5014562,  5014921,  5015099,  5016145,  5016791,
            5017181,  5017656,  5018165,  5018340,  5019014,  5019656,
            5020498,  5021894,  5022034,  5022299,  5023452,  5025645,
            5026013,  5026581,  5028070,  5029223,  5029469,  5029930,
            5031623,  5032343,  5033665,  5035273,  5036180,  5036656,
            5037800,  5040294,  5040872,  5042216,  5042541,  5043207,
            5043818,  5045206,  5046083,  5046469,  5047139,  5050164,
            5051764,  5054110,  5055419,  5056089,  5056189,  5056309,
            5056642,  5057152,  5057233,  5059280,  5059541,  5060286,
            5060636,  5061033,  5061586,  5062181,  5062652,  5063270,
            5064727,  5065461,  5065765,  5066074,  5066405,  5067916,
            5069149,  5070132,  5071656,  5071800,  5073983,  5074921,
            5076037,  5076379,  5077207,  5078490,  5078805,  5080040,
            5080229,  5081032,  5081240,  5081796,  5082893,  5083285,
            5083313,  5083586,  5084274,  5084686,  5086323,  5087101,
            5087539,  5089466,  5089734,  5090283,  5091820,  5092737,
            5094022,  5095601,  5097380,  5097870,  5099203,  5099952])

  • dmr_length
    (dmr)
    int64
    2 305 54 2 2 ... 842 195 399 335

    array([   2,  305,   54,    2,    2,    2,    2,  440,  171,   12,    2,
              2,   22,  504,  128,  146,  201,    2,    2,    2,    2,  182,
              2,  246,    2,    2,  101,  343,   49,  183,    2,   88,    2,
              2,   89,  385,   55,    2,    2,   48,  144,    2,    2,  821,
              2,    2,  306,  913,    2,   71,   91,   22,   21,  149,    2,
              2,    2,    2,   57,   76,    2,  532,  552,  211,    2,  243,
              2,    2,  322,   63,    2, 2314, 1029, 2090,    2,   58,    2,
             67,    2,  253,    2, 1351,    2,  478,    2,  127,   42,   43,
              2,   46,    2,  482,   14,    2,    2,  773,  760,    2,  661,
            126,  345,  687,  537,    2,  469,  866,    2,    2,   59,  315,
              2,  368, 1053,  367,    2,    2,  186,    2,  391,  108,  323,
             31,    2,  138,  434,  589,  924,  632,  842,  195,  399,  335])

  • dmr_ndms
    (dmr)
    int64
    1 7 2 1 1 1 1 ... 13 19 9 9 3 6 13

    array([ 1,  7,  2,  1,  1,  1,  1, 13,  3,  2,  1,  1,  2,  5,  2,  3,  2,
            1,  1,  1,  1,  4,  1,  2,  1,  1,  3,  6,  4,  3,  1,  4,  1,  1,
            3,  7,  4,  1,  1,  2,  4,  1,  1,  8,  1,  1,  9, 14,  1,  5,  3,
            2,  2,  2,  1,  1,  1,  1,  2,  2,  1, 17, 11,  3,  1,  5,  1,  1,
            9,  4,  1, 33, 28, 56,  1,  2,  1,  2,  1,  4,  1, 20,  1,  7,  1,
            2,  2,  2,  1,  2,  1,  7,  3,  1,  1, 15, 29,  1, 20,  4,  8, 13,
            4,  1,  5, 15,  1,  1,  4,  6,  1, 10, 47,  9,  1,  1,  2,  1,  3,
            4,  8,  2,  1,  2,  7, 13, 19,  9,  9,  3,  6, 13])

  • dmr_start
    (dmr)
    int64
    10002170 10003237 ... 5099617

    array([10002170, 10003237, 10003913, 10005477, 10007097, 10007756,
           10008879, 10009487,  5000023,  5000331,  5000713,  5001504,
            5001527,  5003358,  5004657,  5005173,  5005615,  5006787,
            5008013,  5008082,  5008128,  5008623,  5010089,  5011022,
            5011722,  5011924,  5012328,  5012612,  5013263,  5013420,
            5014248,  5014474,  5014919,  5015097,  5016056,  5016406,
            5017126,  5017654,  5018163,  5018292,  5018870,  5019654,
            5020496,  5021073,  5022032,  5022297,  5023146,  5024732,
            5026011,  5026510,  5027979,  5029201,  5029448,  5029781,
            5031621,  5032341,  5033663,  5035271,  5036123,  5036580,
            5037798,  5039762,  5040320,  5042005,  5042539,  5042964,
            5043816,  5045204,  5045761,  5046406,  5047137,  5047850,
            5050735,  5052020,  5055417,  5056031,  5056187,  5056242,
            5056640,  5056899,  5057231,  5057929,  5059539,  5059808,
            5060634,  5060906,  5061544,  5062138,  5062650,  5063224,
            5064725,  5064979,  5065751,  5066072,  5066403,  5067143,
            5068389,  5070130,  5070995,  5071674,  5073638,  5074234,
            5075500,  5076377,  5076738,  5077624,  5078803,  5080038,
            5080170,  5080717,  5081238,  5081428,  5081840,  5082918,
            5083311,  5083584,  5084088,  5084684,  5085932,  5086993,
            5087216,  5089435,  5089732,  5090145,  5091386,  5092148,
            5093098,  5094969,  5096538,  5097675,  5098804,  5099617])

  • snATAC
    (snATAC)
    <U4
    'CA23' 'CGE' 'ASC' ... 'OPC' 'DG'

    array(['CA23', 'CGE', 'ASC', 'MGE', 'CA1', 'ODC', 'MGC', 'NonN', 'OPC', 'DG'],
          dtype='<U4')

• Attributes: (0)

DMR Overlapping Genome Features (BED)

Next, we overlap the DMR regions with a set of BED files that containing different kinds of genome features (e.g. CGI, promoter). The annotate_by_beds method of RegionDS can help scan the regions on each BigWig file, resulting a new data variable stored in the RegionDS. The output dataset is a boolean matrix recording whether a DMR is overlapping with one feature.

genome_feature_dir = '../../data/genome/genome_feature/'
genome_feature_beds = {
    '.'.join(p.name.split('.')[:-4]): str(p)
    for p in pathlib.Path(genome_feature_dir).glob('*.bed.gz')
}

beds = pd.Series(genome_feature_beds)
beds.to_csv('test_genome_featue_bed.csv', header=False)
beds

CGI                          ../../data/genome/genome_feature/CGI.merge.sor...
CGI_Shore                    ../../data/genome/genome_feature/CGI_Shore.mer...
blacklist                    ../../data/genome/genome_feature/blacklist.mm1...
gene.all                     ../../data/genome/genome_feature/gene.all.merg...
gene.lincRNA                 ../../data/genome/genome_feature/gene.lincRNA....
intron.all                   ../../data/genome/genome_feature/intron.all.me...
intron.first                 ../../data/genome/genome_feature/intron.first....
intron.protein_coding        ../../data/genome/genome_feature/intron.protei...
promoter.all                 ../../data/genome/genome_feature/promoter.all....
splicing_site_slop100        ../../data/genome/genome_feature/splicing_site...
exon.all                     ../../data/genome/genome_feature/exon.all.merg...
exon.first                   ../../data/genome/genome_feature/exon.first.me...
stop_codon.all               ../../data/genome/genome_feature/stop_codon.al...
start_codon.all              ../../data/genome/genome_feature/start_codon.a...
exon.protein_coding          ../../data/genome/genome_feature/exon.protein_...
transcript.all               ../../data/genome/genome_feature/transcript.al...
TSS.all                      ../../data/genome/genome_feature/TSS.all.merge...
TSS.protein_coding           ../../data/genome/genome_feature/TSS.protein_c...
UTR3.all                     ../../data/genome/genome_feature/UTR3.all.merg...
UTR3.protein_coding          ../../data/genome/genome_feature/UTR3.protein_...
UTR5.all                     ../../data/genome/genome_feature/UTR5.all.merg...
UTR5.protein_coding          ../../data/genome/genome_feature/UTR5.protein_...
gene.protein_coding          ../../data/genome/genome_feature/gene.protein_...
promoter.protein_coding      ../../data/genome/genome_feature/promoter.prot...
transcript.protein_coding    ../../data/genome/genome_feature/transcript.pr...
dtype: object

dmr_ds.annotate_by_beds(slop=250,
                        bed_table='test_genome_featue_bed.csv',
                        dim='genome-features',
                        bed_sorted=False,
                        cpu=30)

Use chunk size 1

# the annotated matrix are stored in a new data variable
dmr_ds['dmr_genome-features_da']

<xarray.DataArray 'dmr_genome-features_da' (dmr: 132, genome-features: 25)>
dask.array<open_dataset-50fa93a20cd098fbd6ef8798079cfba4dmr_genome-features_da, shape=(132, 25), dtype=bool, chunksize=(132, 1), chunktype=numpy.ndarray>
Coordinates:
  * dmr              (dmr) <U9 'chr1-0' 'chr1-1' ... 'chr19-122' 'chr19-123'
    dmr_chrom        (dmr) <U5 'chr1' 'chr1' 'chr1' ... 'chr19' 'chr19' 'chr19'
    dmr_end          (dmr) int64 10002172 10003542 10003967 ... 5099203 5099952
    dmr_length       (dmr) int64 2 305 54 2 2 2 2 ... 924 632 842 195 399 335
    dmr_ndms         (dmr) int64 1 7 2 1 1 1 1 13 3 2 ... 1 2 7 13 19 9 9 3 6 13
    dmr_start        (dmr) int64 10002170 10003237 10003913 ... 5098804 5099617
  * genome-features  (genome-features) <U25 'CGI' ... 'transcript.protein_cod...

xarray.DataArray

'dmr_genome-features_da'

• dmr: 132
• genome-features: 25

• dask.array<chunksize=(132, 1), meta=np.ndarray>

  Array Chunk Bytes 3.30 kB 132 B Shape (132, 25) (132, 1) Count 26 Tasks 25 Chunks Type bool numpy.ndarray

• Coordinates: (7)
  • dmr
    (dmr)
    <U9
    'chr1-0' 'chr1-1' ... 'chr19-123'

    array(['chr1-0', 'chr1-1', 'chr1-2', 'chr1-3', 'chr1-4', 'chr1-5', 'chr1-6',
           'chr1-7', 'chr19-0', 'chr19-1', 'chr19-2', 'chr19-3', 'chr19-4',
           'chr19-5', 'chr19-6', 'chr19-7', 'chr19-8', 'chr19-9', 'chr19-10',
           'chr19-11', 'chr19-12', 'chr19-13', 'chr19-14', 'chr19-15', 'chr19-16',
           'chr19-17', 'chr19-18', 'chr19-19', 'chr19-20', 'chr19-21', 'chr19-22',
           'chr19-23', 'chr19-24', 'chr19-25', 'chr19-26', 'chr19-27', 'chr19-28',
           'chr19-29', 'chr19-30', 'chr19-31', 'chr19-32', 'chr19-33', 'chr19-34',
           'chr19-35', 'chr19-36', 'chr19-37', 'chr19-38', 'chr19-39', 'chr19-40',
           'chr19-41', 'chr19-42', 'chr19-43', 'chr19-44', 'chr19-45', 'chr19-46',
           'chr19-47', 'chr19-48', 'chr19-49', 'chr19-50', 'chr19-51', 'chr19-52',
           'chr19-53', 'chr19-54', 'chr19-55', 'chr19-56', 'chr19-57', 'chr19-58',
           'chr19-59', 'chr19-60', 'chr19-61', 'chr19-62', 'chr19-63', 'chr19-64',
           'chr19-65', 'chr19-66', 'chr19-67', 'chr19-68', 'chr19-69', 'chr19-70',
           'chr19-71', 'chr19-72', 'chr19-73', 'chr19-74', 'chr19-75', 'chr19-76',
           'chr19-77', 'chr19-78', 'chr19-79', 'chr19-80', 'chr19-81', 'chr19-82',
           'chr19-83', 'chr19-84', 'chr19-85', 'chr19-86', 'chr19-87', 'chr19-88',
           'chr19-89', 'chr19-90', 'chr19-91', 'chr19-92', 'chr19-93', 'chr19-94',
           'chr19-95', 'chr19-96', 'chr19-97', 'chr19-98', 'chr19-99', 'chr19-100',
           'chr19-101', 'chr19-102', 'chr19-103', 'chr19-104', 'chr19-105',
           'chr19-106', 'chr19-107', 'chr19-108', 'chr19-109', 'chr19-110',
           'chr19-111', 'chr19-112', 'chr19-113', 'chr19-114', 'chr19-115',
           'chr19-116', 'chr19-117', 'chr19-118', 'chr19-119', 'chr19-120',
           'chr19-121', 'chr19-122', 'chr19-123'], dtype='<U9')

  • dmr_chrom
    (dmr)
    <U5
    'chr1' 'chr1' ... 'chr19' 'chr19'

    array(['chr1', 'chr1', 'chr1', 'chr1', 'chr1', 'chr1', 'chr1', 'chr1',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19', 'chr19',
           'chr19', 'chr19', 'chr19', 'chr19', 'chr19'], dtype='<U5')

  • dmr_end
    (dmr)
    int64
    10002172 10003542 ... 5099952

    array([10002172, 10003542, 10003967, 10005479, 10007099, 10007758,
           10008881, 10009927,  5000194,  5000343,  5000715,  5001506,
            5001549,  5003862,  5004785,  5005319,  5005816,  5006789,
            5008015,  5008084,  5008130,  5008805,  5010091,  5011268,
            5011724,  5011926,  5012429,  5012955,  5013312,  5013603,
            5014250,  5014562,  5014921,  5015099,  5016145,  5016791,
            5017181,  5017656,  5018165,  5018340,  5019014,  5019656,
            5020498,  5021894,  5022034,  5022299,  5023452,  5025645,
            5026013,  5026581,  5028070,  5029223,  5029469,  5029930,
            5031623,  5032343,  5033665,  5035273,  5036180,  5036656,
            5037800,  5040294,  5040872,  5042216,  5042541,  5043207,
            5043818,  5045206,  5046083,  5046469,  5047139,  5050164,
            5051764,  5054110,  5055419,  5056089,  5056189,  5056309,
            5056642,  5057152,  5057233,  5059280,  5059541,  5060286,
            5060636,  5061033,  5061586,  5062181,  5062652,  5063270,
            5064727,  5065461,  5065765,  5066074,  5066405,  5067916,
            5069149,  5070132,  5071656,  5071800,  5073983,  5074921,
            5076037,  5076379,  5077207,  5078490,  5078805,  5080040,
            5080229,  5081032,  5081240,  5081796,  5082893,  5083285,
            5083313,  5083586,  5084274,  5084686,  5086323,  5087101,
            5087539,  5089466,  5089734,  5090283,  5091820,  5092737,
            5094022,  5095601,  5097380,  5097870,  5099203,  5099952])

  • dmr_length
    (dmr)
    int64
    2 305 54 2 2 ... 842 195 399 335

    array([   2,  305,   54,    2,    2,    2,    2,  440,  171,   12,    2,
              2,   22,  504,  128,  146,  201,    2,    2,    2,    2,  182,
              2,  246,    2,    2,  101,  343,   49,  183,    2,   88,    2,
              2,   89,  385,   55,    2,    2,   48,  144,    2,    2,  821,
              2,    2,  306,  913,    2,   71,   91,   22,   21,  149,    2,
              2,    2,    2,   57,   76,    2,  532,  552,  211,    2,  243,
              2,    2,  322,   63,    2, 2314, 1029, 2090,    2,   58,    2,
             67,    2,  253,    2, 1351,    2,  478,    2,  127,   42,   43,
              2,   46,    2,  482,   14,    2,    2,  773,  760,    2,  661,
            126,  345,  687,  537,    2,  469,  866,    2,    2,   59,  315,
              2,  368, 1053,  367,    2,    2,  186,    2,  391,  108,  323,
             31,    2,  138,  434,  589,  924,  632,  842,  195,  399,  335])

  • dmr_ndms
    (dmr)
    int64
    1 7 2 1 1 1 1 ... 13 19 9 9 3 6 13

    array([ 1,  7,  2,  1,  1,  1,  1, 13,  3,  2,  1,  1,  2,  5,  2,  3,  2,
            1,  1,  1,  1,  4,  1,  2,  1,  1,  3,  6,  4,  3,  1,  4,  1,  1,
            3,  7,  4,  1,  1,  2,  4,  1,  1,  8,  1,  1,  9, 14,  1,  5,  3,
            2,  2,  2,  1,  1,  1,  1,  2,  2,  1, 17, 11,  3,  1,  5,  1,  1,
            9,  4,  1, 33, 28, 56,  1,  2,  1,  2,  1,  4,  1, 20,  1,  7,  1,
            2,  2,  2,  1,  2,  1,  7,  3,  1,  1, 15, 29,  1, 20,  4,  8, 13,
            4,  1,  5, 15,  1,  1,  4,  6,  1, 10, 47,  9,  1,  1,  2,  1,  3,
            4,  8,  2,  1,  2,  7, 13, 19,  9,  9,  3,  6, 13])

  • dmr_start
    (dmr)
    int64
    10002170 10003237 ... 5099617

    array([10002170, 10003237, 10003913, 10005477, 10007097, 10007756,
           10008879, 10009487,  5000023,  5000331,  5000713,  5001504,
            5001527,  5003358,  5004657,  5005173,  5005615,  5006787,
            5008013,  5008082,  5008128,  5008623,  5010089,  5011022,
            5011722,  5011924,  5012328,  5012612,  5013263,  5013420,
            5014248,  5014474,  5014919,  5015097,  5016056,  5016406,
            5017126,  5017654,  5018163,  5018292,  5018870,  5019654,
            5020496,  5021073,  5022032,  5022297,  5023146,  5024732,
            5026011,  5026510,  5027979,  5029201,  5029448,  5029781,
            5031621,  5032341,  5033663,  5035271,  5036123,  5036580,
            5037798,  5039762,  5040320,  5042005,  5042539,  5042964,
            5043816,  5045204,  5045761,  5046406,  5047137,  5047850,
            5050735,  5052020,  5055417,  5056031,  5056187,  5056242,
            5056640,  5056899,  5057231,  5057929,  5059539,  5059808,
            5060634,  5060906,  5061544,  5062138,  5062650,  5063224,
            5064725,  5064979,  5065751,  5066072,  5066403,  5067143,
            5068389,  5070130,  5070995,  5071674,  5073638,  5074234,
            5075500,  5076377,  5076738,  5077624,  5078803,  5080038,
            5080170,  5080717,  5081238,  5081428,  5081840,  5082918,
            5083311,  5083584,  5084088,  5084684,  5085932,  5086993,
            5087216,  5089435,  5089732,  5090145,  5091386,  5092148,
            5093098,  5094969,  5096538,  5097675,  5098804,  5099617])

  • genome-features
    (genome-features)
    <U25
    'CGI' ... 'transcript.protein_co...

    array(['CGI', 'CGI_Shore', 'blacklist', 'gene.all', 'gene.lincRNA',
           'intron.all', 'intron.first', 'intron.protein_coding', 'promoter.all',
           'splicing_site_slop100', 'exon.all', 'exon.first', 'stop_codon.all',
           'start_codon.all', 'exon.protein_coding', 'transcript.all', 'TSS.all',
           'TSS.protein_coding', 'UTR3.all', 'UTR3.protein_coding', 'UTR5.all',
           'UTR5.protein_coding', 'gene.protein_coding', 'promoter.protein_coding',
           'transcript.protein_coding'], dtype='<U25')

• Attributes: (0)

After Annotation

After annotation, the RegionDS will contain additional dmr-by-feature matrix.

# note the dmr_genome-features and dmr_snATAC dir is newly added by the annotation functions
!tree -L 2 test_HIP/

test_HIP/
├── chrom_sizes.txt
├── dmr
│   ├── count_type
│   ├── dmr
│   ├── dmr_chrom
│   ├── dmr_da
│   ├── dmr_da_frac
│   ├── dmr_end
│   ├── dmr_length
│   ├── dmr_ndms
│   ├── dmr_start
│   ├── dmr_state
│   └── sample
├── dmr_genome-features
│   ├── dmr
│   ├── dmr_genome-features_da
│   └── genome-features
├── dmr_snATAC
│   ├── dmr
│   ├── dmr_snATAC_da
│   └── snATAC
└── dms
    ├── count_type
    ├── dms
    ├── dms_chrom
    ├── dms_contexts
    ├── dms_da
    ├── dms_da_frac
    ├── dms_pos
    ├── dms_p-values
    ├── dms_residual
    └── sample

31 directories, 1 file

Selectively open

When you open a RegionDS containing multiple annotation, you can select specific datasets with select_dir and select specific DMRs with use_regions.

# select 2 DMR and their snATAC annotation
RegionDS.open('test_HIP/', 
              select_dir=['dmr', 'dmr_snATAC'],
              use_regions=['chr1-0', 'chr1-1'])

Using dmr as region_dim

<xarray.RegionDS>
Dimensions:        (count_type: 2, dmr: 2, sample: 20, snATAC: 10)
Coordinates:
  * count_type     (count_type) <U3 'mc' 'cov'
  * dmr            (dmr) <U9 'chr1-0' 'chr1-1'
    dmr_chrom      (dmr) <U5 'chr1' 'chr1'
    dmr_end        (dmr) int64 10002172 10003542
    dmr_length     (dmr) int64 2 305
    dmr_ndms       (dmr) int64 1 7
    dmr_start      (dmr) int64 10002170 10003237
  * sample         (sample) <U18 'snm3C_ASC' 'snm3C_CA1' ... 'snmC_OPC'
  * snATAC         (snATAC) <U4 'CA23' 'CGE' 'ASC' 'MGE' ... 'NonN' 'OPC' 'DG'
Data variables:
    dmr_da         (sample, dmr, count_type) uint32 4294967295 ... 4294967295
    dmr_da_frac    (sample, dmr) float32 1.0 1.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0
    dmr_state      (sample, dmr) int8 -1 0 0 1 0 1 -1 0 -1 ... 0 1 0 0 1 0 0 0
    dmr_snATAC_da  (dmr, snATAC) float32 0.09983 0.02372 ... 0.02372 0.03385
Attributes:
    region_dim:          dmr
    region_ds_location:  /home/hanliu/pkg/ALLCools_pycharm/docs/allcools/clus...
    chrom_size_path:     /home/hanliu/pkg/ALLCools_pycharm/docs/allcools/clus...

xarray.RegionDS

• Dimensions:
  • count_type: 2
  • dmr: 2
  • sample: 20
  • snATAC: 10
• Coordinates: (9)
  • count_type
    (count_type)
    <U3
    'mc' 'cov'

    array(['mc', 'cov'], dtype='<U3')

  • dmr
    (dmr)
    <U9
    'chr1-0' 'chr1-1'

    array(['chr1-0', 'chr1-1'], dtype='<U9')

  • dmr_chrom
    (dmr)
    <U5
    'chr1' 'chr1'

    array(['chr1', 'chr1'], dtype='<U5')

  • dmr_end
    (dmr)
    int64
    10002172 10003542

    array([10002172, 10003542])

  • dmr_length
    (dmr)
    int64
    2 305

    array([  2, 305])

  • dmr_ndms
    (dmr)
    int64
    1 7

    array([1, 7])

  • dmr_start
    (dmr)
    int64
    10002170 10003237

    array([10002170, 10003237])

  • sample
    (sample)
    <U18
    'snm3C_ASC' ... 'snmC_OPC'

    array(['snm3C_ASC', 'snm3C_CA1', 'snm3C_CA23', 'snm3C_CGE-VipLamp5',
           'snm3C_DG', 'snm3C_MGC', 'snm3C_MGE-PvSst', 'snm3C_NonN', 'snm3C_ODC',
           'snm3C_OPC', 'snmC_ASC', 'snmC_CA1', 'snmC_CA23', 'snmC_CGE-VipLamp5',
           'snmC_DG', 'snmC_MGC', 'snmC_MGE-PvSst', 'snmC_NonN', 'snmC_ODC',
           'snmC_OPC'], dtype='<U18')

  • snATAC
    (snATAC)
    <U4
    'CA23' 'CGE' 'ASC' ... 'OPC' 'DG'

    array(['CA23', 'CGE', 'ASC', 'MGE', 'CA1', 'ODC', 'MGC', 'NonN', 'OPC', 'DG'],
          dtype='<U4')

• Data variables: (4)
  • dmr_da
    (sample, dmr, count_type)
    uint32
    ...

    array([[[4294967295, 4294967295],
            [4294967295, 4294967295]],
    
           [[4294967295, 4294967295],
            [4294967295, 4294967295]],
    
           [[4294967295, 4294967295],
            [4294967295, 4294967295]],
    
           [[4294967295, 4294967295],
            [4294967295, 4294967295]],
    
           [[4294967295, 4294967295],
            [4294967295, 4294967295]],
    
           [[4294967295, 4294967295],
            [4294967295, 4294967295]],
    
           [[4294967295, 4294967295],
            [4294967295, 4294967295]],
    
           [[4294967295, 4294967295],
            [4294967295, 4294967295]],
    
           [[4294967295, 4294967295],
            [4294967295, 4294967295]],
    
           [[4294967295, 4294967295],
            [4294967295, 4294967295]],
    
           [[4294967295, 4294967295],
            [4294967295, 4294967295]],
    
           [[4294967295, 4294967295],
            [4294967295, 4294967295]],
    
           [[4294967295, 4294967295],
            [4294967295, 4294967295]],
    
           [[4294967295, 4294967295],
            [4294967295, 4294967295]],
    
           [[4294967295, 4294967295],
            [4294967295, 4294967295]],
    
           [[4294967295, 4294967295],
            [4294967295, 4294967295]],
    
           [[4294967295, 4294967295],
            [4294967295, 4294967295]],
    
           [[4294967295, 4294967295],
            [4294967295, 4294967295]],
    
           [[4294967295, 4294967295],
            [4294967295, 4294967295]],
    
           [[4294967295, 4294967295],
            [4294967295, 4294967295]]], dtype=uint32)

  • dmr_da_frac
    (sample, dmr)
    float32
    ...

    array([[1., 1.],
           [1., 1.],
           [1., 1.],
           [1., 1.],
           [1., 1.],
           [1., 1.],
           [1., 1.],
           [1., 1.],
           [1., 1.],
           [1., 1.],
           [1., 1.],
           [1., 1.],
           [1., 1.],
           [1., 1.],
           [1., 1.],
           [1., 1.],
           [1., 1.],
           [1., 1.],
           [1., 1.],
           [1., 1.]], dtype=float32)

  • dmr_state
    (sample, dmr)
    int8
    ...

    array([[-1,  0],
           [ 0,  1],
           [ 0,  1],
           [-1,  0],
           [-1,  0],
           [-1, -1],
           [ 0,  0],
           [-1,  0],
           [-1,  0],
           [ 0,  0],
           [ 0,  0],
           [ 0,  1],
           [ 1,  1],
           [ 1,  0],
           [ 1,  0],
           [ 0, -1],
           [ 0,  1],
           [ 0,  0],
           [ 1,  0],
           [ 0,  0]], dtype=int8)

  • dmr_snATAC_da
    (dmr, snATAC)
    float32
    ...

    array([[0.099833, 0.023715, 0.030183,      nan, 0.045207,      nan, 0.040654,
                 nan,      nan, 0.034512],
           [0.03162 ,      nan,      nan,      nan, 0.041277,      nan, 0.082943,
                 nan, 0.023715, 0.033851]], dtype=float32)

• Attributes: (3)

  region_dim :

  dmr

  region_ds_location :

  /home/hanliu/pkg/ALLCools_pycharm/docs/allcools/cluster_level/RegionDS/test_HIP

  chrom_size_path :

  /home/hanliu/pkg/ALLCools_pycharm/docs/allcools/cluster_level/RegionDS/test_HIP/chrom_sizes.txt

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