From 0ba56a68c7220e2ad6772b9bac3ac175a5c36ce0 Mon Sep 17 00:00:00 2001 From: Isaac Virshup Date: Mon, 23 Jan 2023 15:31:43 +0100 Subject: [PATCH 1/3] move 10x reader tests --- anndata/tests/test_read_10x.py | 128 +++++++++++++++++++++++++++++++++ 1 file changed, 128 insertions(+) create mode 100644 anndata/tests/test_read_10x.py diff --git a/anndata/tests/test_read_10x.py b/anndata/tests/test_read_10x.py new file mode 100644 index 000000000..79e320d92 --- /dev/null +++ b/anndata/tests/test_read_10x.py @@ -0,0 +1,128 @@ +from pathlib import Path + +import h5py +import pytest +import anndata as ad +from anndata.tests.helpers import assert_equal +import shutil + + +ROOT = Path(__file__).parent +ROOT = ROOT / "data" / "10x_data" + + +@pytest.mark.parametrize( + ["mtx_path", "h5_path"], + [ + pytest.param( + ROOT / "1.2.0" / "filtered_gene_bc_matrices" / "hg19_chr21", + ROOT / "1.2.0" / "filtered_gene_bc_matrices_h5.h5", + ), + pytest.param( + ROOT / "3.0.0" / "filtered_feature_bc_matrix", + ROOT / "3.0.0" / "filtered_feature_bc_matrix.h5", + ), + ], +) +@pytest.mark.parametrize("prefix", [None, "prefix_"]) +def test_read_10x(tmp_path, mtx_path, h5_path, prefix): + if prefix is not None: + # Build files named "prefix_XXX.xxx" in a temporary directory. + mtx_path_orig = mtx_path + mtx_path = tmp_path / "filtered_gene_bc_matrices_prefix" + mtx_path.mkdir() + for item in mtx_path_orig.iterdir(): + if item.is_file(): + shutil.copyfile(item, mtx_path / f"{prefix}{item.name}") + + mtx = ad.read_10x_mtx(mtx_path, var_names="gene_symbols", prefix=prefix) + h5 = ad.read_10x_h5(h5_path) + + # Drop genome column for comparing v3 + if "3.0.0" in str(h5_path): + h5.var.drop(columns="genome", inplace=True) + + # Check equivalence + assert_equal(mtx, h5) + + # Test that it can be written: + from_mtx_pth = tmp_path / "from_mtx.h5ad" + from_h5_pth = tmp_path / "from_h5.h5ad" + + mtx.write(from_mtx_pth) + h5.write(from_h5_pth) + + assert_equal(ad.read_h5ad(from_mtx_pth), ad.read_h5ad(from_h5_pth)) + + +def test_read_10x_h5_v1(): + spec_genome_v1 = ad.read_10x_h5( + ROOT / "1.2.0" / "filtered_gene_bc_matrices_h5.h5", + genome="hg19_chr21", + ) + nospec_genome_v1 = ad.read_10x_h5( + ROOT / "1.2.0" / "filtered_gene_bc_matrices_h5.h5" + ) + assert_equal(spec_genome_v1, nospec_genome_v1) + + +def test_read_10x_h5_v2_multiple_genomes(): + genome1_v1 = ad.read_10x_h5( + ROOT / "1.2.0" / "multiple_genomes.h5", + genome="hg19_chr21", + ) + genome2_v1 = ad.read_10x_h5( + ROOT / "1.2.0" / "multiple_genomes.h5", + genome="another_genome", + ) + # the test data are such that X is the same shape for both "genomes", + # but the values are different + assert (genome1_v1.X != genome2_v1.X).sum() > 0, ( + "loading data from two different genomes in 10x v2 format. " + "should be different, but is the same. " + ) + + +def test_read_10x_h5(): + spec_genome_v3 = ad.read_10x_h5( + ROOT / "3.0.0" / "filtered_feature_bc_matrix.h5", + genome="GRCh38_chr21", + ) + nospec_genome_v3 = ad.read_10x_h5(ROOT / "3.0.0" / "filtered_feature_bc_matrix.h5") + assert_equal(spec_genome_v3, nospec_genome_v3) + + +def test_error_10x_h5_legacy(tmp_path): + onepth = ROOT / "1.2.0" / "filtered_gene_bc_matrices_h5.h5" + twopth = tmp_path / "two_genomes.h5" + with h5py.File(onepth, "r") as one, h5py.File(twopth, "w") as two: + one.copy("hg19_chr21", two) + one.copy("hg19_chr21", two, name="hg19_chr21_copy") + with pytest.raises(ValueError): + ad.read_10x_h5(twopth) + ad.read_10x_h5(twopth, genome="hg19_chr21_copy") + + +def test_error_missing_genome(): + legacy_pth = ROOT / "1.2.0" / "filtered_gene_bc_matrices_h5.h5" + v3_pth = ROOT / "3.0.0" / "filtered_feature_bc_matrix.h5" + with pytest.raises(ValueError, match=r".*hg19_chr21.*"): + ad.read_10x_h5(legacy_pth, genome="not a genome") + with pytest.raises(ValueError, match=r".*GRCh38_chr21.*"): + ad.read_10x_h5(v3_pth, genome="not a genome") + + +def test_read_visium_counts(): + # Test that checks the read_visium function + visium_pth = ROOT / "../visium_data/1.0.0" + spec_genome_v3 = ad.read_visium(visium_pth, genome="GRCh38") + nospec_genome_v3 = ad.read_visium(visium_pth) + assert_equal(spec_genome_v3, nospec_genome_v3) + + +def test_10x_h5_gex(): + # Tests that gex option doesn't, say, make the function return None + h5_pth = ROOT / "3.0.0" / "filtered_feature_bc_matrix.h5" + assert_equal( + ad.read_10x_h5(h5_pth, gex_only=True), ad.read_10x_h5(h5_pth, gex_only=False) + ) From 8eefb7c159133448d0062aceed1808a84623b025 Mon Sep 17 00:00:00 2001 From: Isaac Virshup Date: Mon, 23 Jan 2023 15:47:09 +0100 Subject: [PATCH 2/3] Initial implementation --- anndata/__init__.py | 2 + anndata/_io/__init__.py | 2 + anndata/_io/read.py | 281 ++++++++++++++++++++++++++++++++- anndata/tests/test_read_10x.py | 16 +- 4 files changed, 288 insertions(+), 13 deletions(-) diff --git a/anndata/__init__.py b/anndata/__init__.py index ad7e4c68b..3ffa56ff0 100644 --- a/anndata/__init__.py +++ b/anndata/__init__.py @@ -17,6 +17,8 @@ read_text, read_mtx, read_zarr, + read_10x_h5, + read_10x_mtx, ) from ._warnings import OldFormatWarning, WriteWarning, ImplicitModificationWarning diff --git a/anndata/_io/__init__.py b/anndata/_io/__init__.py index f54f6c558..1de1d9a09 100644 --- a/anndata/_io/__init__.py +++ b/anndata/_io/__init__.py @@ -8,6 +8,8 @@ read_text, read_zarr, read_h5ad, + read_10x_h5, + read_10x_mtx, ) from .write import write_csvs, write_loom, _write_h5ad, write_zarr from . import h5ad diff --git a/anndata/_io/read.py b/anndata/_io/read.py index 43383ab8a..951f380dc 100644 --- a/anndata/_io/read.py +++ b/anndata/_io/read.py @@ -1,7 +1,9 @@ +from __future__ import annotations + from pathlib import Path from os import PathLike, fspath from types import MappingProxyType -from typing import Union, Optional, Mapping, Tuple +from typing import Union, Optional, Literal, Mapping, Tuple from typing import Iterable, Iterator, Generator from collections import OrderedDict import gzip @@ -491,3 +493,280 @@ def del_sparse_matrix_keys(mapping, key_csr): del mapping[f"{key_csr}_indices"] del mapping[f"{key_csr}_indptr"] del mapping[f"{key_csr}_shape"] + + +# Reading 10x formats + + +def read_10x_h5( + filename: Union[str, Path], + *, + genome: Optional[str] = None, + feature_types: str | list[str] | None = None, +) -> AnnData: + """\ + Read 10x-Genomics-formatted hdf5 file. + + Parameters + ---------- + filename + Path to a 10x hdf5 file. + genome + Filter expression to genes within this genome. For legacy 10x h5 + files, this must be provided if the data contains more than one genome. + Feature types + Which feature types to read in. Reads all in by default. + + Returns + ------- + Annotated data matrix, where observations/cells are named by their + barcode and variables/genes by gene name. Stores the following information: + + :attr:`~anndata.AnnData.X` + The data matrix is stored + :attr:`~anndata.AnnData.obs_names` + Cell names + :attr:`~anndata.AnnData.var_names` + Gene names + :attr:`~anndata.AnnData.var`\\ `['gene_ids']` + Gene IDs + :attr:`~anndata.AnnData.var`\\ `['feature_types']` + Feature types + """ + # Coerce feature_type to be either list of string or None + if feature_types is not None: + if isinstance(feature_types, str): + feature_types = [feature_types] + + with h5py.File(str(filename), "r") as f: + v3 = "/matrix" in f + if v3: + adata = _read_v3_10x_h5(filename) + if genome: + if genome not in adata.var["genome"].values: + raise ValueError( + f"Could not find data corresponding to genome '{genome}' in '{filename}'. " + f'Available genomes are: {list(adata.var["genome"].unique())}.' + ) + adata = adata[:, adata.var["genome"] == genome] + if feature_types is not None: + adata = adata[:, adata.var["feature_types"].isin(feature_types)] + if adata.is_view: + adata = adata.copy() + else: + adata = _read_legacy_10x_h5(filename, genome=genome) + return adata + + +def _read_v3_10x_h5(filename): + """ + Read hdf5 file from Cell Ranger v3 or later versions. + """ + with h5py.File(str(filename), "r") as f: + dsets = {} + _collect_datasets(dsets, f["matrix"]) + + from scipy.sparse import csr_matrix + + M, N = dsets["shape"] + data = dsets["data"] + if dsets["data"].dtype == np.dtype("int32"): + data = dsets["data"].view("float32") + data[:] = dsets["data"] + matrix = csr_matrix( + (data, dsets["indices"], dsets["indptr"]), + shape=(N, M), + ) + adata = AnnData( + matrix, + obs=dict(obs_names=dsets["barcodes"].astype(str)), + var=dict( + var_names=dsets["name"].astype(str), + gene_ids=dsets["id"].astype(str), + feature_types=dsets["feature_type"].astype(str), + genome=dsets["genome"].astype(str), + ), + ) + return adata + + +def _read_legacy_10x_h5(filename, *, genome=None): + """ + Read hdf5 file from Cell Ranger v2 or earlier versions. + """ + with h5py.File(str(filename), "r") as f: + children = list(f.keys()) + if not genome: + if len(children) > 1: + raise ValueError( + f"'{filename}' contains more than one genome. For legacy 10x h5 " + "files you must specify the genome if more than one is present. " + f"Available genomes are: {children}" + ) + genome = children[0] + elif genome not in children: + raise ValueError( + f"Could not find genome '{genome}' in '{filename}'. " + f"Available genomes are: {children}" + ) + + dsets = {} + _collect_datasets(dsets, f[genome]) + + # AnnData works with csr matrices + # 10x stores the transposed data, so we do the transposition right away + from scipy.sparse import csr_matrix + + M, N = dsets["shape"] + data = dsets["data"] + if dsets["data"].dtype == np.dtype("int32"): + data = dsets["data"].view("float32") + data[:] = dsets["data"] + matrix = csr_matrix( + (data, dsets["indices"], dsets["indptr"]), + shape=(N, M), + ) + # the csc matrix is automatically the transposed csr matrix + # as scanpy expects it, so, no need for a further transpostion + adata = AnnData( + matrix, + obs=dict(obs_names=dsets["barcodes"].astype(str)), + var=dict( + var_names=dsets["gene_names"].astype(str), + gene_ids=dsets["genes"].astype(str), + ), + ) + return adata + + +def _collect_datasets(dsets: dict, group: h5py.Group): + for k, v in group.items(): + if isinstance(v, h5py.Dataset): + dsets[k] = v[()] + else: + _collect_datasets(dsets, v) + + +def read_10x_mtx( + path: Union[Path, str], + *, + var_names: Literal["gene_symbols", "gene_ids"] = "gene_symbols", + make_unique: bool = True, + gex_only: bool = True, + prefix: str = None, +) -> AnnData: + """\ + Read 10x-Genomics-formatted mtx directory. + + Parameters + ---------- + path + Path to directory for `.mtx` and `.tsv` files, + e.g. './filtered_gene_bc_matrices/hg19/'. + var_names + The variables index. + make_unique + Whether to make the variables index unique by appending '-1', + '-2' etc. or not. + cache + If `False`, read from source, if `True`, read from fast 'h5ad' cache. + cache_compression + See the h5py :ref:`dataset_compression`. + (Default: `settings.cache_compression`) + gex_only + Only keep 'Gene Expression' data and ignore other feature types, + e.g. 'Antibody Capture', 'CRISPR Guide Capture', or 'Custom' + prefix + Any prefix before `matrix.mtx`, `genes.tsv` and `barcodes.tsv`. For instance, + if the files are named `patientA_matrix.mtx`, `patientA_genes.tsv` and + `patientA_barcodes.tsv` the prefix is `patientA_`. + (Default: no prefix) + + Returns + ------- + An :class:`~anndata.AnnData` object + """ + path = Path(path) + prefix = "" if prefix is None else prefix + genefile_exists = (path / f"{prefix}genes.tsv").is_file() + read = _read_legacy_10x_mtx if genefile_exists else _read_v3_10x_mtx + adata = read( + str(path), + var_names=var_names, + make_unique=make_unique, + prefix=prefix, + ) + if genefile_exists or not gex_only: + return adata + else: + gex_rows = list( + map(lambda x: x == "Gene Expression", adata.var["feature_types"]) + ) + return adata[:, gex_rows].copy() + + +def _read_legacy_10x_mtx( + path, + var_names="gene_symbols", + make_unique=True, + *, + prefix="", +): + """ + Read mex from output from Cell Ranger v2 or earlier versions + """ + from anndata.utils import make_index_unique + + path = Path(path) + adata = read_mtx( + path / f"{prefix}matrix.mtx", + ).T # transpose the data + genes = pd.read_csv(path / f"{prefix}genes.tsv", header=None, sep="\t") + if var_names == "gene_symbols": + var_names = genes[1].values + if make_unique: + var_names = make_index_unique(pd.Index(var_names)) + adata.var_names = var_names + adata.var["gene_ids"] = genes[0].values + elif var_names == "gene_ids": + adata.var_names = genes[0].values + adata.var["gene_symbols"] = genes[1].values + else: + raise ValueError("`var_names` needs to be 'gene_symbols' or 'gene_ids'") + adata.obs_names = pd.read_csv(path / f"{prefix}barcodes.tsv", header=None)[0].values + return adata + + +def _read_v3_10x_mtx( + path, + *, + var_names="gene_symbols", + make_unique=True, + prefix="", +): + """ + Read mtx from output from Cell Ranger v3 or later versions + """ + from anndata.utils import make_index_unique + + path = Path(path) + adata = read_mtx( + path / f"{prefix}matrix.mtx.gz", + ).T # transpose the data + genes = pd.read_csv(path / f"{prefix}features.tsv.gz", header=None, sep="\t") + if var_names == "gene_symbols": + var_names = genes[1].values + if make_unique: + var_names = make_index_unique(pd.Index(var_names)) + adata.var_names = var_names + adata.var["gene_ids"] = genes[0].values + elif var_names == "gene_ids": + adata.var_names = genes[0].values + adata.var["gene_symbols"] = genes[1].values + else: + raise ValueError("`var_names` needs to be 'gene_symbols' or 'gene_ids'") + adata.var["feature_types"] = genes[2].values + adata.obs_names = pd.read_csv(path / f"{prefix}barcodes.tsv.gz", header=None)[ + 0 + ].values + return adata diff --git a/anndata/tests/test_read_10x.py b/anndata/tests/test_read_10x.py index 79e320d92..f96466356 100644 --- a/anndata/tests/test_read_10x.py +++ b/anndata/tests/test_read_10x.py @@ -7,8 +7,7 @@ import shutil -ROOT = Path(__file__).parent -ROOT = ROOT / "data" / "10x_data" +ROOT = Path(__file__).parent / "data" / "10x" @pytest.mark.parametrize( @@ -112,17 +111,10 @@ def test_error_missing_genome(): ad.read_10x_h5(v3_pth, genome="not a genome") -def test_read_visium_counts(): - # Test that checks the read_visium function - visium_pth = ROOT / "../visium_data/1.0.0" - spec_genome_v3 = ad.read_visium(visium_pth, genome="GRCh38") - nospec_genome_v3 = ad.read_visium(visium_pth) - assert_equal(spec_genome_v3, nospec_genome_v3) - - -def test_10x_h5_gex(): +def test_10x_h5_feature_types(): # Tests that gex option doesn't, say, make the function return None h5_pth = ROOT / "3.0.0" / "filtered_feature_bc_matrix.h5" assert_equal( - ad.read_10x_h5(h5_pth, gex_only=True), ad.read_10x_h5(h5_pth, gex_only=False) + ad.read_10x_h5(h5_pth, feature_types="Gene Expression"), + ad.read_10x_h5(h5_pth, feature_types=["Gene Expression"]), ) From 694a103bc2a83391df4f79ed102eb944cbf0709c Mon Sep 17 00:00:00 2001 From: Isaac Virshup Date: Mon, 23 Jan 2023 16:41:35 +0100 Subject: [PATCH 3/3] Add test data --- .../hg19_chr21/barcodes.tsv | 12 + .../hg19_chr21/genes.tsv | 343 ++++++++++++++++++ .../hg19_chr21/matrix.mtx | 15 + .../10x/1.2.0/filtered_gene_bc_matrices_h5.h5 | Bin 0 -> 26745 bytes .../tests/data/10x/1.2.0/multiple_genomes.h5 | Bin 0 -> 54138 bytes .../10x/3.0.0/filtered_feature_bc_matrix.h5 | Bin 0 -> 100207 bytes .../barcodes.tsv.gz | Bin 0 -> 6423 bytes .../features.tsv.gz | Bin 0 -> 4774 bytes .../filtered_feature_bc_matrix/matrix.mtx.gz | Bin 0 -> 73946 bytes 9 files changed, 370 insertions(+) create mode 100644 anndata/tests/data/10x/1.2.0/filtered_gene_bc_matrices/hg19_chr21/barcodes.tsv create mode 100644 anndata/tests/data/10x/1.2.0/filtered_gene_bc_matrices/hg19_chr21/genes.tsv create mode 100644 anndata/tests/data/10x/1.2.0/filtered_gene_bc_matrices/hg19_chr21/matrix.mtx create mode 100644 anndata/tests/data/10x/1.2.0/filtered_gene_bc_matrices_h5.h5 create mode 100644 anndata/tests/data/10x/1.2.0/multiple_genomes.h5 create mode 100644 anndata/tests/data/10x/3.0.0/filtered_feature_bc_matrix.h5 create mode 100644 anndata/tests/data/10x/3.0.0/filtered_feature_bc_matrix/barcodes.tsv.gz create mode 100644 anndata/tests/data/10x/3.0.0/filtered_feature_bc_matrix/features.tsv.gz create mode 100644 anndata/tests/data/10x/3.0.0/filtered_feature_bc_matrix/matrix.mtx.gz diff --git a/anndata/tests/data/10x/1.2.0/filtered_gene_bc_matrices/hg19_chr21/barcodes.tsv b/anndata/tests/data/10x/1.2.0/filtered_gene_bc_matrices/hg19_chr21/barcodes.tsv new file mode 100644 index 000000000..273b3521b --- /dev/null +++ b/anndata/tests/data/10x/1.2.0/filtered_gene_bc_matrices/hg19_chr21/barcodes.tsv @@ -0,0 +1,12 @@ +AACACGTGTACGCTGC-1 +AAGGAGCTCCGATATG-1 +AGGCCGTAGTGAAGTT-1 +CCTATTACAACGCACC-1 +CCTTTCTAGGGCTTCC-1 +CGTGTAAAGGATGGAA-1 +GACGCGTCAATGTAAG-1 +GACTACAAGATCACGG-1 +GGTGCGTGTTAAGACA-1 +TAGCCGGGTTAGATGA-1 +TCCACACCATGAGCGA-1 +TTTATGCCATCCGTGG-1 diff --git a/anndata/tests/data/10x/1.2.0/filtered_gene_bc_matrices/hg19_chr21/genes.tsv b/anndata/tests/data/10x/1.2.0/filtered_gene_bc_matrices/hg19_chr21/genes.tsv new file mode 100644 index 000000000..f29e9c8ed --- /dev/null +++ b/anndata/tests/data/10x/1.2.0/filtered_gene_bc_matrices/hg19_chr21/genes.tsv @@ -0,0 +1,343 @@ +DSCAM DSCAM +MIR99AHG MIR99AHG +APP APP +USP16 USP16 +ADAMTS5 ADAMTS5 +TIAM1 TIAM1 +LOC339622 LOC339622 +IFNAR2 IFNAR2 +DYRK1A DYRK1A +MORC3 MORC3 +ERG ERG +RRP1B RRP1B +TEKT4P2 TEKT4P2 +ANKRD30BP2 ANKRD30BP2 +RBM11 RBM11 +ANKRD20A11P ANKRD20A11P +SAMSN1 SAMSN1 +NRIP1 NRIP1 +LOC388813 LOC388813 +USP25 USP25 +CHODL CHODL +TMPRSS15 TMPRSS15 +MIR548XHG MIR548XHG +NCAM2 NCAM2 +LINC00320 LINC00320 +LOC101927843 LOC101927843 +LOC101927869 LOC101927869 +GABPA GABPA +CYYR1 CYYR1 +MIR5009 MIR5009 +LINC00113 LINC00113 +LOC284825 LOC284825 +LOC101927973 LOC101927973 +GRIK1 GRIK1 +MAP3K7CL MAP3K7CL +CLDN8 CLDN8 +HUNK HUNK +SYNJ1 SYNJ1 +URB1 URB1 +TCP10L TCP10L +EVA1C EVA1C +MRAP MRAP +ITSN1 ITSN1 +CRYZL1 CRYZL1 +RUNX1 RUNX1 +RCAN1 RCAN1 +CLIC6 CLIC6 +DOPEY2 DOPEY2 +LOC100506403 LOC100506403 +LOC100133286 LOC100133286 +LOC101928269 LOC101928269 +CLDN14 CLDN14 +TTC3 TTC3 +HLCS HLCS +DSCR4 DSCR4 +KCNJ6 KCNJ6 +LINC01423 LINC01423 +BRWD1 BRWD1 +WRB WRB +B3GALT5 B3GALT5 +PCP4 PCP4 +IGSF5 IGSF5 +FAM3B FAM3B +TMPRSS2 TMPRSS2 +BACE2 BACE2 +UMODL1 UMODL1 +PRDM15 PRDM15 +ABCG1 ABCG1 +RSPH1 RSPH1 +PDE9A PDE9A +PKNOX1 PKNOX1 +HSF2BP HSF2BP +AGPAT3 AGPAT3 +TRAPPC10 TRAPPC10 +TSPEAR TSPEAR +PFKL PFKL +RRP1 RRP1 +ADARB1 ADARB1 +COL18A1 COL18A1 +YBEY YBEY +PCBP3 PCBP3 +DIP2A DIP2A +PCNT PCNT +MIR3648-1 MIR3648-1 +MIR3687-1 MIR3687-1 +MIR3648-2 MIR3648-2 +MIR3687-2 MIR3687-2 +TPTE TPTE +BAGE BAGE +BAGE4 BAGE4 +BAGE3 BAGE3 +BAGE5 BAGE5 +BAGE2 BAGE2 +MIR3156-3 MIR3156-3 +LOC102724188 LOC102724188 +MIR3118-1 MIR3118-1 +POTED POTED +MIR8069-1 MIR8069-1 +MIR8069-2 MIR8069-2 +CYP4F29P CYP4F29P +LIPI LIPI +ABCC13 ABCC13 +HSPA13 HSPA13 +SAMSN1-AS1 SAMSN1-AS1 +MIR99A MIR99A +MIRLET7C MIRLET7C +MIR125B2 MIR125B2 +LINC01549 LINC01549 +CXADR CXADR +BTG3 BTG3 +C21orf91 C21orf91 +CHODL-AS1 CHODL-AS1 +C21orf91-OT1 C21orf91-OT1 +LINC00317 LINC00317 +LINC01425 LINC01425 +LINC00308 LINC00308 +D21S2088E D21S2088E +LINC00158 LINC00158 +MRPL39 MRPL39 +LINC00515 LINC00515 +MIR155 MIR155 +MIR155HG MIR155HG +ATP5J ATP5J +JAM2 JAM2 +ADAMTS1 ADAMTS1 +MIR4759 MIR4759 +LINC00314 LINC00314 +LINC00161 LINC00161 +N6AMT1 N6AMT1 +LTN1 LTN1 +RWDD2B RWDD2B +CCT8 CCT8 +LINC00189 LINC00189 +BACH1 BACH1 +BACH1-IT2 BACH1-IT2 +GRIK1-AS2 GRIK1-AS2 +GRIK1-AS1 GRIK1-AS1 +CLDN17 CLDN17 +LINC00307 LINC00307 +KRTAP27-1 KRTAP27-1 +KRTAP25-1 KRTAP25-1 +KRTAP24-1 KRTAP24-1 +KRTAP26-1 KRTAP26-1 +KRTAP13-4 KRTAP13-4 +KRTAP15-1 KRTAP15-1 +KRTAP13-3 KRTAP13-3 +MIR4327 MIR4327 +KRTAP13-1 KRTAP13-1 +KRTAP23-1 KRTAP23-1 +KRTAP13-2 KRTAP13-2 +KRTAP6-2 KRTAP6-2 +KRTAP19-7 KRTAP19-7 +KRTAP19-5 KRTAP19-5 +KRTAP19-4 KRTAP19-4 +KRTAP19-3 KRTAP19-3 +KRTAP19-2 KRTAP19-2 +KRTAP19-6 KRTAP19-6 +KRTAP22-2 KRTAP22-2 +KRTAP6-3 KRTAP6-3 +KRTAP22-1 KRTAP22-1 +KRTAP19-1 KRTAP19-1 +KRTAP6-1 KRTAP6-1 +KRTAP20-2 KRTAP20-2 +KRTAP20-1 KRTAP20-1 +KRTAP20-4 KRTAP20-4 +KRTAP20-3 KRTAP20-3 +KRTAP21-3 KRTAP21-3 +KRTAP21-1 KRTAP21-1 +KRTAP21-2 KRTAP21-2 +KRTAP8-1 KRTAP8-1 +KRTAP7-1 KRTAP7-1 +KRTAP11-1 KRTAP11-1 +KRTAP19-8 KRTAP19-8 +SCAF4 SCAF4 +SOD1 SOD1 +LINC00159 LINC00159 +MIS18A MIS18A +URB1-AS1 URB1-AS1 +SNORA80A SNORA80A +C21orf59 C21orf59 +PAXBP1 PAXBP1 +C21orf62 C21orf62 +C21orf62-AS1 C21orf62-AS1 +PAXBP1-AS1 PAXBP1-AS1 +OLIG1 OLIG1 +OLIG2 OLIG2 +LINC00945 LINC00945 +LINC01548 LINC01548 +LOC101928107 LOC101928107 +IFNAR1 IFNAR1 +IL10RB IL10RB +IL10RB-AS1 IL10RB-AS1 +DNAJC28 DNAJC28 +TMEM50B TMEM50B +IFNGR2 IFNGR2 +GART GART +SON SON +DONSON DONSON +MIR6501 MIR6501 +ATP5O ATP5O +LINC00649 LINC00649 +MRPS6 MRPS6 +SLC5A3 SLC5A3 +LINC00310 LINC00310 +KCNE2 KCNE2 +C21orf140 C21orf140 +SMIM11A SMIM11A +SMIM11B SMIM11B +KCNE1 KCNE1 +LINC00160 LINC00160 +LINC01426 LINC01426 +RUNX1-IT1 RUNX1-IT1 +MIR802 MIR802 +SETD4 SETD4 +CBR1 CBR1 +LINC01436 LINC01436 +CBR3 CBR3 +CBR3-AS1 CBR3-AS1 +CHAF1B CHAF1B +SIM2 SIM2 +RIPPLY3 RIPPLY3 +PIGP PIGP +LOC105372795 LOC105372795 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