@@ -51,7 +50,8 @@
Metadata Files
Synapse ID |
Category |
- Num Items |
+ Num Records |
+ Percent Complete Metadata |
@@ -60,6 +60,7 @@ Metadata Files
{{ meta_file.id }} |
{{ meta_file.category }} |
{{ meta_file.num_items }} |
+ {{ "%.2f"|format(100 * meta_file.percent_meta_data_complete) }}% |
{% endfor %}
diff --git a/hdash/util/__init__.py b/hdash/util/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/hdash/util/heatmap_util.py b/hdash/util/heatmap_util.py
index 0c668b1..cda46af 100644
--- a/hdash/util/heatmap_util.py
+++ b/hdash/util/heatmap_util.py
@@ -1,6 +1,8 @@
"""HeatMap Utility."""
import pandas as pd
+from natsort import natsorted
from hdash.util.heatmap import HeatMap
+from hdash.stats.completeness_summary import CompletenessSummary
from hdash.validator.categories import Categories
import seaborn as sns
import matplotlib.pyplot as plt
@@ -16,11 +18,12 @@ class HeatMapUtil:
IMAGE_OTHER = "image_other"
VISIUM = "visium"
- CAPTION = "Values indicate fraction of meta-data fields that have data."
+ CAPTION = "Value of 1 Indicates that data is present."
- def __init__(self, project):
- """Initialize the specified HTAN Project."""
- self.project = project
+ def __init__(self, atlas_id, completeness_summary: CompletenessSummary):
+ """Default Constructor."""
+ self.atlas_id = atlas_id
+ self.completeness_summary = completeness_summary
self.heatmaps = []
self.categories = Categories()
@@ -41,7 +44,7 @@ def __init__(self, project):
)
# Heatmap 3
- self.single_cell_assay_list = [self.categories.BIOSPECIMEN]
+ self.single_cell_assay_list = []
self.single_cell_assay_list.extend(self.categories.sc_rna_list)
self.single_cell_assay_list.extend(self.categories.sc_atac_list)
self.__build_assay_heatmap(
@@ -52,7 +55,7 @@ def __init__(self, project):
)
# Heatmap 4
- self.bulk_assay_list = [self.categories.BIOSPECIMEN]
+ self.bulk_assay_list = []
self.bulk_assay_list.extend(self.categories.bulk_rna_list)
self.bulk_assay_list.extend(self.categories.bulk_wes_list)
self.__build_assay_heatmap(
@@ -63,7 +66,7 @@ def __init__(self, project):
)
# Heatmap 5
- self.image_assay_list = [self.categories.BIOSPECIMEN]
+ self.image_assay_list = []
self.image_assay_list.extend(self.categories.image_list)
self.image_assay_list.extend(self.categories.other_assay_list)
self.__build_assay_heatmap(
@@ -74,7 +77,7 @@ def __init__(self, project):
)
# Heatmap 5
- self.visium_assay_list = [self.categories.BIOSPECIMEN]
+ self.visium_assay_list = []
self.visium_assay_list.extend(self.categories.visium_list)
self.__build_assay_heatmap(
HeatMapUtil.VISIUM,
@@ -94,35 +97,36 @@ def __build_clinical_heatmap(self, heatmap_type, category_list, label, bg_color)
headers.append(shorter)
else:
headers.append(category)
- for participant_id in self.project.participant_id_set:
+ for participant_id in self.completeness_summary.graph_flat.participant_id_set:
current_row = [participant_id]
for category in category_list:
- key = participant_id + ":" + category
- current_row.append(self.project.df_stats_map.get(key, 0))
+ value = 0
+ if self.completeness_summary.has_data(participant_id, category):
+ value = 1
+ current_row.append(value)
data.append(current_row)
self.__create_heatmap(heatmap_type, data, headers, label, bg_color)
def __build_assay_heatmap(self, heatmap_type, category_list, label, bg_color):
"""Build Assay Data Heatmap."""
- participant_2_bipspecimens = self.project.participant_2_biopsecimens
- df_stats_map = self.project.df_stats_map
+ participant_2_bipspecimens = (
+ self.completeness_summary.graph_flat.participant_2_biopsecimens
+ )
headers = ["ParticipantID", "BiospecimenID"]
data = []
for category in category_list:
headers.append(category)
- for participant_id in self.project.participant_id_set:
+ for participant_id in self.completeness_summary.graph_flat.participant_id_set:
b_ids = participant_2_bipspecimens.get(participant_id, [])
+ b_ids = natsorted(b_ids)
for biospecimen_id in b_ids:
- total_coverage = 0
current_row = [participant_id, biospecimen_id]
for category in category_list:
- key = biospecimen_id + ":" + category
- coverage = df_stats_map.get(key, 0)
- if category != Categories.BIOSPECIMEN:
- total_coverage += coverage
- current_row.append(coverage)
- if total_coverage > 0:
- data.append(current_row)
+ value = 0
+ if self.completeness_summary.has_data(biospecimen_id, category):
+ value = 1
+ current_row.append(value)
+ data.append(current_row)
self.__create_heatmap(heatmap_type, data, headers, label, bg_color)
def __create_heatmap(self, heatmap_type, data, headers, label, bg_color):
@@ -132,7 +136,7 @@ def __create_heatmap(self, heatmap_type, data, headers, label, bg_color):
index=False, justify="left", classes="table table-striped table-sm"
)
caption = HeatMapUtil.CAPTION
- heatmap_id = self.project.atlas_id + "_" + heatmap_type
+ heatmap_id = self.atlas_id + "_" + heatmap_type
heatmap = HeatMap(heatmap_id, label, caption, data, df, df_html, bg_color)
self.heatmaps.append(heatmap)
diff --git a/hdash/validator/id_util.py b/hdash/util/id_util.py
similarity index 100%
rename from hdash/validator/id_util.py
rename to hdash/util/id_util.py
diff --git a/hdash/validator/categories.py b/hdash/validator/categories.py
index 4894751..21db10d 100644
--- a/hdash/validator/categories.py
+++ b/hdash/validator/categories.py
@@ -188,7 +188,7 @@ def __init__(self):
Categories.VISIUM_LEVEL_1: "VS1",
Categories.VISIUM_LEVEL_2: "VS2",
Categories.VISIUM_AUX_LEVEL_2: "VS2_A",
- Categories.VISIUM_LEVEL_3: "VS3"
+ Categories.VISIUM_LEVEL_3: "VS3",
}
self.all_assays = []
diff --git a/hdash/validator/htan_validator.py b/hdash/validator/htan_validator.py
index 6a4cb08..aad58c4 100644
--- a/hdash/validator/htan_validator.py
+++ b/hdash/validator/htan_validator.py
@@ -1,9 +1,7 @@
"""Core HTAN Validator."""
-import pandas as pd
-
from typing import List
-from hdash.validator.categories import Categories
+from hdash.graph.htan_graph import HtanGraph
from hdash.validator.validation_rule import ValidationRule
from hdash.validator.validate_demographics import ValidateDemographics
from hdash.validator.validate_biospecimens import ValidateBiospecimens
@@ -13,38 +11,23 @@
from hdash.validator.validate_links import ValidateLinks
from hdash.validator.validate_categories import ValidateCategories
from hdash.synapse.meta_map import MetaMap
-from hdash.synapse.meta_file import MetaFile
class HtanValidator:
"""Core HTAN Validator."""
- def __init__(self, atlas_id, meta_data_file_list: List[MetaFile]):
+ def __init__(self, atlas_id, meta_map: MetaMap, htan_graph: HtanGraph):
"""Construct a new HTAN Validator for one atlas."""
self.atlas_id = atlas_id
+ self.meta_map = meta_map
+ self.graph = htan_graph
self.validation_list = []
- self.node_map = {}
- self.meta_map = MetaMap()
-
- # Review all the metadata files and bin them within the MetaMap
- for meta_file in meta_data_file_list:
- self.meta_map.add_meta_file(meta_file)
-
- # Then validate
self.__validate()
def get_validation_list(self) -> List[ValidationRule]:
"""Get the list of validation rules applied."""
return self.validation_list
- def get_node_map(self):
- """Get the graph map of all nodes."""
- return self.links1.node_map
-
- def get_edge_list(self):
- """Get the list of all edges."""
- return self.links1.edge_list
-
def __validate(self):
# Categories Validation
c0 = ValidateCategories(self.meta_map)
@@ -67,9 +50,9 @@ def __validate(self):
self.validation_list.append(id1)
# Link Integrity
- self.links1 = ValidateLinks(self.meta_map)
- self.validation_list.append(self.links1)
+ links1 = ValidateLinks(self.graph)
+ self.validation_list.append(links1)
# Synapse IDs
- self.synapseIds1 = ValidateEntityIds(self.meta_map)
- self.validation_list.append(self.synapseIds1)
+ synapseIds1 = ValidateEntityIds(self.meta_map)
+ self.validation_list.append(synapseIds1)
diff --git a/hdash/validator/validate_categories.py b/hdash/validator/validate_categories.py
index 2907514..f372ae2 100644
--- a/hdash/validator/validate_categories.py
+++ b/hdash/validator/validate_categories.py
@@ -8,7 +8,7 @@
class ValidateCategories(ValidationRule):
"""Verify that Atlas is using Categories supported by the Dashhoard."""
- def __init__(self, meta_file_map: MetaMap):
+ def __init__(self, meta_file_map: MetaMap):
"""Construct new Validation Rule."""
super().__init__(
"H_CATEGORIES",
@@ -21,4 +21,4 @@ def __init__(self, meta_file_map: MetaMap):
self.add_error_message(
f"{category} is not yet supported by the Dashboard. "
"Please notify Ethan to update the code!"
- )
\ No newline at end of file
+ )
diff --git a/hdash/validator/validate_demographics.py b/hdash/validator/validate_demographics.py
index e77fd50..dd15d11 100644
--- a/hdash/validator/validate_demographics.py
+++ b/hdash/validator/validate_demographics.py
@@ -4,6 +4,7 @@
from hdash.validator.categories import Categories
from hdash.synapse.meta_map import MetaMap
+
class ValidateDemographics(ValidationRule):
"""Verify that Demographics File is Present."""
diff --git a/hdash/validator/validate_entity_ids.py b/hdash/validator/validate_entity_ids.py
index 95acae4..a2f4ed7 100644
--- a/hdash/validator/validate_entity_ids.py
+++ b/hdash/validator/validate_entity_ids.py
@@ -30,7 +30,7 @@ def __init__(self, meta_file_map: MetaMap):
)
self.add_error(msg, meta_file)
- def __check_synapse_ids(self, meta_file: MetaFile, category, synapse_ids):
+ def __check_synapse_ids(self, meta_file: MetaFile, category, synapse_ids):
for synapse_id in synapse_ids:
if not str(synapse_id).startswith("syn"):
msg = "%s has invalid Synapse ID: %s." % (category, synapse_id)
diff --git a/hdash/validator/validate_links.py b/hdash/validator/validate_links.py
index d83bc3e..7d3f338 100644
--- a/hdash/validator/validate_links.py
+++ b/hdash/validator/validate_links.py
@@ -1,118 +1,48 @@
"""Validation Rule."""
from hdash.validator.validation_rule import ValidationRule
-from hdash.graph.graph import Node, Edge
-from hdash.validator.id_util import IdUtil
-from hdash.validator.categories import Categories
-from hdash.synapse.meta_map import MetaMap
-from hdash.synapse.meta_file import MetaFile
-import logging
+from hdash.graph.htan_graph import HtanGraph
class ValidateLinks(ValidationRule):
"""Validate all internal links."""
- def __init__(self, meta_file_map: MetaMap):
+ def __init__(self, htan_graph: HtanGraph):
"""Construct new Validation Rule."""
super().__init__("H_LINKS", "Validate all internal links.")
- self.id_util = IdUtil()
- self.meta_map = meta_file_map
- self.node_map = {}
- self.edge_list = []
- self.categories = Categories()
- self.__gather_nodes()
- self.__gather_edges()
-
- def __gather_nodes(self):
- self.__gather_nodes_by_category(self.categories.DEMOGRAPHICS)
- self.__gather_nodes_by_category(self.categories.BIOSPECIMEN)
- self.__gather_nodes_by_category(self.categories.SRRS_BIOSPECIMEN)
- for category in self.categories.all_assays:
- self.__gather_nodes_by_category(category)
-
- def __gather_nodes_by_category(self, category):
- meta_file_list = self.meta_map.get_meta_file_list(category)
- for meta_file in meta_file_list:
- df = meta_file.df
- primary_id = self.id_util.get_primary_id_column(category)
- id_list = df[primary_id].to_list()
- for current_id in id_list:
- current_id = str(current_id)
- node = Node()
- node.id = current_id
- node.label = current_id
- node.category = category
- self.node_map[current_id] = node
-
- def __gather_edges(self):
- for category in self.categories.all_categories:
- self.__gather_edges_by_category(category)
-
- def __gather_edges_by_category(self, category):
- meta_file_list = self.meta_map.get_meta_file_list(category)
- for meta_file in meta_file_list:
- logging.info("Validating links in: %s", meta_file.id)
- df = meta_file.df
- primary_id_col = self.id_util.get_primary_id_column(category)
- parent_id_col = self.id_util.get_parent_id_column(category)
- adj_id_col = self.id_util.get_adjacent_id_column(category)
- if parent_id_col is not None:
- for index, row in df.iterrows():
- chunk = str(row[parent_id_col])
-
- # Handle Special HTAPP/DFCI Cases
- if chunk.startswith("Not Applicable"):
- try:
- chunk = str(row[IdUtil.HTAN_PARENT_BIOSPECIMEN_ID])
- except KeyError:
- chunk = "NOT_APPLICABLE"
-
- id = str(row[primary_id_col])
- self.__check_parents(meta_file, id, chunk, category)
- if adj_id_col is not None:
- if adj_id_col in df.columns:
- for index, row in df.iterrows():
- chunk = str(row[adj_id_col])
- id = str(row[primary_id_col])
- self.__check_adjacents(meta_file, id, chunk, category)
- else:
- msg = "%s is missing column: %s" % (category, adj_id_col)
- self.add_error(msg, meta_file)
-
- def __check_parents(self, meta_file: MetaFile, id, parent_id_chunk, category):
- # We can have multiple parents!
- parent_id_chunk = parent_id_chunk.replace(";", " ").replace(",", " ")
- parts = parent_id_chunk.split()
- for part in parts:
- parent_id = part.strip()
- parent_exists = parent_id in self.node_map
- if not parent_exists:
- m = "%s references parent ID: %s, but no such ID exists" % (
- category,
- parent_id
- )
- self.add_error(m, meta_file)
- elif id == parent_id:
- m = "%s references itself: %s as parent." % (category, id)
- self.add_error(m, meta_file)
- else:
- edge = Edge()
- edge.source_id = parent_id
- edge.target_id = id
- self.edge_list.append(edge)
-
- def __check_adjacents(self, meta_file: MetaFile, id, adj_id_chunk, category):
- # We can have multiple adjacents!
- if adj_id_chunk == "nan":
- return
- adj_id_chunk = adj_id_chunk.replace(";", " ").replace(",", " ")
- parts = adj_id_chunk.split()
- for part in parts:
- adjacent_id = part.strip()
- adjacent_exists = adjacent_id in self.node_map
- if not adjacent_exists:
- m = "%s references adjacent ID: %s, but no such ID exists" % (
- category,
- adjacent_id
- )
- self.add_error(m, meta_file)
+ self._htan_graph = htan_graph
+ self._validate_edges()
+ self._validate_adjacent_edges()
+
+ def _validate_edges(self):
+ """Validate Edges."""
+ edge_list = self._htan_graph.edge_list
+ directed_graph = self._htan_graph.directed_graph
+ for edge in edge_list:
+ parent_id = edge[0]
+ child_id = edge[1]
+ child_node = directed_graph.nodes[child_id]
+
+ if parent_id not in directed_graph.nodes:
+ m = f"{child_id} references parent ID="
+ m += f"{parent_id}, but no such ID exists."
+ self.add_error(m, child_node[HtanGraph.DATA_KEY].meta_file)
+
+ if child_id == parent_id:
+ m = f"{child_id} references itself as a parent."
+ self.add_error(m, child_node[HtanGraph.DATA_KEY].meta_file)
+
+
+ def _validate_adjacent_edges(self):
+ """Validate Adjacent Edges."""
+ adjacent_edge_list = self._htan_graph.adjacent_list
+ directed_graph = self._htan_graph.directed_graph
+ for edge in adjacent_edge_list:
+ source_id = edge[0]
+ adjacent_id = edge[1]
+ source_node = directed_graph.nodes[source_id]
+
+ if adjacent_id not in directed_graph.nodes:
+ m = f"{source_id} references adjacent ID="
+ m += f"{adjacent_id}, but no such ID exists."
+ self.add_error(m, source_node[HtanGraph.DATA_KEY].meta_file)
diff --git a/hdash/validator/validate_non_demographics.py b/hdash/validator/validate_non_demographics.py
index 50bb878..ae9d25c 100644
--- a/hdash/validator/validate_non_demographics.py
+++ b/hdash/validator/validate_non_demographics.py
@@ -2,7 +2,7 @@
from hdash.validator.categories import Categories
from hdash.validator.validation_rule import ValidationRule
-from hdash.validator.id_util import IdUtil
+from hdash.util.id_util import IdUtil
from hdash.synapse.meta_map import MetaMap
diff --git a/hdash/validator/validate_primary_ids.py b/hdash/validator/validate_primary_ids.py
index 856ad0f..539194e 100644
--- a/hdash/validator/validate_primary_ids.py
+++ b/hdash/validator/validate_primary_ids.py
@@ -1,6 +1,6 @@
"""Validation Rule."""
-from hdash.validator.id_util import IdUtil
+from hdash.util.id_util import IdUtil
from hdash.validator.categories import Categories
from hdash.validator.validation_rule import ValidationRule
from hdash.synapse.meta_map import MetaMap
@@ -36,9 +36,11 @@ def __validate_ids(self, atlas_id, category):
meta_file, category, current_id, atlas_id
)
else:
- self.__check_primary_id(meta_file, category, current_id, atlas_id)
+ self.__check_primary_id(
+ meta_file, category, current_id, atlas_id
+ )
- def __check_participant_id(self, meta_file: MetaFile, category, id, atlas_id):
+ def __check_participant_id(self, meta_file: MetaFile, category, id, atlas_id):
parts = id.split("_")
label = category + ": " + id
if parts[0] != atlas_id:
@@ -54,7 +56,7 @@ def __check_participant_id(self, meta_file: MetaFile, category, id, atlas_id):
msg = label + " does not match HTAN spec."
self.add_error(msg, meta_file)
- def __check_primary_id(self, meta_file: MetaFile, category, id, atlas_id):
+ def __check_primary_id(self, meta_file: MetaFile, category, id, atlas_id):
parts = id.split("_")
label = category + ": " + id
if parts[0] != atlas_id:
diff --git a/hdash/validator/validation_rule.py b/hdash/validator/validation_rule.py
index c123739..b865382 100644
--- a/hdash/validator/validation_rule.py
+++ b/hdash/validator/validation_rule.py
@@ -26,4 +26,4 @@ def add_error_message(self, msg):
def _create_error_msg(self, msg, meta_file: MetaFile):
"""Creates Error Message with Synapse ID."""
- return f"{msg} [synapse id: {meta_file.id}]"
+ return f"{msg} [category: {meta_file.category}, synapse_id: {meta_file.id}]"
diff --git a/pytest.ini b/pytest.ini
new file mode 100644
index 0000000..88044e5
--- /dev/null
+++ b/pytest.ini
@@ -0,0 +1,5 @@
+[pytest]
+filterwarnings =
+ ignore::DeprecationWarning
+markers =
+ smoke: marks smoke tests
diff --git a/tests/conftest.py b/tests/conftest.py
index 8d040ce..75ddf37 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -2,6 +2,8 @@
import pytest
from hdash.synapse.htan_project import HTANProject
from hdash.synapse.meta_file import MetaFile
+from hdash.synapse.meta_map import MetaMap
+from hdash.synapse.table_util import TableUtil
@pytest.fixture
@@ -21,6 +23,36 @@ def init_annotated_project_list():
project.meta_list.append(meta_file)
return project_list
+@pytest.fixture
+def sample_meta_map():
+ path_list = [
+ "tests/data/demographics.csv",
+ "tests/data/biospecimens.csv",
+ "tests/data/single_cell_level1.csv",
+ "tests/data/single_cell_level2.csv",
+ "tests/data/single_cell_level3.csv",
+ "tests/data/single_cell_level4.csv",
+ ]
+ meta_file_list = _create_meta_file_list(path_list)
+
+ meta_map = MetaMap()
+ for meta_file in meta_file_list:
+ meta_map.add_meta_file(meta_file)
+ return meta_map
+
+def _create_meta_file_list(path_list: list[str]):
+ meta_file_list = []
+ tableUtil = TableUtil()
+ synapse_id = 1
+ for path in path_list:
+ meta_file = MetaFile()
+ meta_file.path = path
+ meta_file.id = f"synapse_{synapse_id}"
+ tableUtil.annotate_meta_file(meta_file)
+ meta_file_list.append(meta_file)
+ synapse_id += 1
+ return meta_file_list
+
def _init_project_list():
project_list = []
diff --git a/tests/data/single_cell_level1.csv b/tests/data/single_cell_level1.csv
index 4e0cb29..fbf4ce2 100644
--- a/tests/data/single_cell_level1.csv
+++ b/tests/data/single_cell_level1.csv
@@ -1,101 +1,101 @@
-Component,Filename,HTAN Parent Biospecimen ID,HTAN Data File ID,File Format,Nucleic Acid Source,Cryopreserved Cells in Sample,Single Cell Isolation Method,Dissociation Method,Library Construction Method,Read Indicator,Read1,Read2,End Bias,Reverse Transcription Primer,Spike In,Sequencing Platform,Total Number of Input Cells,Input Cells and Nuclei,Library Preparation Days from Index,Single Cell Dissociation Days from Index,Sequencing Library Construction Days from Index,Nucleic Acid Capture Days from Index,Protocol Link,Technical Replicate Group,Both Spike in Mixes,Cell Barcode Length,Cell Barcode Offset,Empty Well Barcode,Feature Reference Id,Median UMIs per Cell Number,Spike In Concentration,Spike In Mix 1,Spike In Mix 2,UMI Barcode Length,UMI Barcode Offset,Valid Barcodes Cell Number,Well Index,cDNA Length,cDNA Offset,entityId
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case1/Ground-glass-opacity/Ground-glass-opacity_S8_L001_R1_001.fastq.gz,HTA3_8001_002,HTA3_8001_4651918348,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV2,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,34,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,155118,,,,10,16,,No,98,0,syn23665348
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case1/Ground-glass-opacity/Ground-glass-opacity_S8_L001_R2_001.fastq.gz,HTA3_8001_002,HTA3_8001_7837535366,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV2,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,34,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,155118,,,,10,16,,No,98,0,syn23665351
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case1/Ground-glass-opacity/Ground-glass-opacity_S8_L002_R1_001.fastq.gz,HTA3_8001_002,HTA3_8001_1769188461,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV2,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,34,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,155118,,,,10,16,,No,98,0,syn23665347
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case1/Ground-glass-opacity/Ground-glass-opacity_S8_L002_R2_001.fastq.gz,HTA3_8001_002,HTA3_8001_5222399563,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV2,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,34,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,155118,,,,10,16,,No,98,0,syn23665352
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case1/Normal-lung/Normal-lung_S7_L001_R1_001.fastq.gz,HTA3_8001_001,HTA3_8001_1067135576,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV2,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,34,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,101943,,,,10,16,,No,98,0,syn23665346
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case1/Normal-lung/Normal-lung_S7_L001_R2_001.fastq.gz,HTA3_8001_001,HTA3_8001_5548545798,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV2,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,34,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,101943,,,,10,16,,No,98,0,syn23665349
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case1/Normal-lung/Normal-lung_S7_L002_R1_001.fastq.gz,HTA3_8001_001,HTA3_8001_8850650337,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV2,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,34,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,101943,,,,10,16,,No,98,0,syn23665345
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case1/Normal-lung/Normal-lung_S7_L002_R2_001.fastq.gz,HTA3_8001_001,HTA3_8001_6154142702,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV2,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,34,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,101943,,,,10,16,,No,98,0,syn23665350
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case2/GGO/Ground_glass_opacity_S2_L001_R1_001.fastq.gz,HTA3_8002_004,HTA3_8002_0204111591,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV2,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,27,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,91636,,,,10,16,,No,98,0,syn23665366
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case2/GGO/Ground_glass_opacity_S2_L001_R2_001.fastq.gz,HTA3_8002_004,HTA3_8002_3029856712,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV2,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,27,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,91636,,,,10,16,,No,98,0,syn23665373
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case2/GGO/Ground_glass_opacity_S2_L002_R1_001.fastq.gz,HTA3_8002_004,HTA3_8002_3124968787,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV2,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,27,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,91636,,,,10,16,,No,98,0,syn23665365
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case2/GGO/Ground_glass_opacity_S2_L002_R2_001.fastq.gz,HTA3_8002_004,HTA3_8002_0107230297,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV2,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,27,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,91636,,,,10,16,,No,98,0,syn23665372
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case2/Normal/Normal_lung_S1_L001_R1_001.fastq.gz,HTA3_8002_001,HTA3_8002_8412561470,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV2,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,27,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,74723,,,,10,16,,No,98,0,syn23665368
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case2/Normal/Normal_lung_S1_L001_R2_001.fastq.gz,HTA3_8002_001,HTA3_8002_1747883314,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV2,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,27,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,74723,,,,10,16,,No,98,0,syn23665374
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case2/Normal/Normal_lung_S1_L002_R1_001.fastq.gz,HTA3_8002_001,HTA3_8002_4074583392,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV2,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,27,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,74723,,,,10,16,,No,98,0,syn23665363
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case2/Normal/Normal_lung_S1_L002_R2_001.fastq.gz,HTA3_8002_001,HTA3_8002_1394371638,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV2,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,27,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,74723,,,,10,16,,No,98,0,syn23665371
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case2/Tumor/Tumor_lung_S3_L001_R1_001.fastq.gz,HTA3_8002_003,HTA3_8002_5567659150,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV2,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,27,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,68182,,,,10,16,,No,98,0,syn23665367
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case2/Tumor/Tumor_lung_S3_L001_R2_001.fastq.gz,HTA3_8002_003,HTA3_8002_3338382307,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV2,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,27,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,68182,,,,10,16,,No,98,0,syn23665369
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case2/Tumor/Tumor_lung_S3_L002_R1_001.fastq.gz,HTA3_8002_003,HTA3_8002_6144108126,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV2,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,27,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,68182,,,,10,16,,No,98,0,syn23665364
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case2/Tumor/Tumor_lung_S3_L002_R2_001.fastq.gz,HTA3_8002_003,HTA3_8002_1745718508,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV2,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,27,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,68182,,,,10,16,,No,98,0,syn23665370
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case3/GGO_Human_Lung/GGO_Human_Lung_S2_L001_R1_001.fastq.gz,HTA3_8003_002,HTA3_8003_6950359714,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,87,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,161151,,,,12,16,,No,91,0,syn23665410
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case3/GGO_Human_Lung/GGO_Human_Lung_S2_L001_R2_001.fastq.gz,HTA3_8003_002,HTA3_8003_3076428712,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,87,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,161151,,,,12,16,,No,91,0,syn23665425
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case3/GGO_Human_Lung/GGO_Human_Lung_S2_L002_R1_001.fastq.gz,HTA3_8003_002,HTA3_8003_4016979191,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,87,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,161151,,,,12,16,,No,91,0,syn23665414
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case3/GGO_Human_Lung/GGO_Human_Lung_S2_L002_R2_001.fastq.gz,HTA3_8003_002,HTA3_8003_7305634320,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,87,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,161151,,,,12,16,,No,91,0,syn23665418
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case3/GGO_Human_Lung/GGO_Human_Lung_S2_L003_R1_001.fastq.gz,HTA3_8003_002,HTA3_8003_1658769671,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,87,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,161151,,,,12,16,,No,91,0,syn23665411
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case3/GGO_Human_Lung/GGO_Human_Lung_S2_L003_R2_001.fastq.gz,HTA3_8003_002,HTA3_8003_0494660791,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,87,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,161151,,,,12,16,,No,91,0,syn23665424
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case3/GGO_Human_Lung/GGO_Human_Lung_S2_L004_R1_001.fastq.gz,HTA3_8003_002,HTA3_8003_2799437993,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,87,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,161151,,,,12,16,,No,91,0,syn23665407
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case3/GGO_Human_Lung/GGO_Human_Lung_S2_L004_R2_001.fastq.gz,HTA3_8003_002,HTA3_8003_3499345940,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,87,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,161151,,,,12,16,,No,91,0,syn23665421
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case3/Normal_Human_Lung/Normal_Human_Lung_S1_L001_R1_001.fastq.gz,HTA3_8003_001,HTA3_8003_4679266082,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,87,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,229332,,,,12,16,,No,91,0,syn23665409
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case3/Normal_Human_Lung/Normal_Human_Lung_S1_L001_R2_001.fastq.gz,HTA3_8003_001,HTA3_8003_5962165526,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,87,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,229332,,,,12,16,,No,91,0,syn23665422
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case3/Normal_Human_Lung/Normal_Human_Lung_S1_L002_R1_001.fastq.gz,HTA3_8003_001,HTA3_8003_6923390836,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,87,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,229332,,,,12,16,,No,91,0,syn23665413
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case3/Normal_Human_Lung/Normal_Human_Lung_S1_L002_R2_001.fastq.gz,HTA3_8003_001,HTA3_8003_0428836996,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,87,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,229332,,,,12,16,,No,91,0,syn23665423
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case3/Normal_Human_Lung/Normal_Human_Lung_S1_L003_R1_001.fastq.gz,HTA3_8003_001,HTA3_8003_0926562504,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,87,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,229332,,,,12,16,,No,91,0,syn23665412
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case3/Normal_Human_Lung/Normal_Human_Lung_S1_L003_R2_001.fastq.gz,HTA3_8003_001,HTA3_8003_6777845086,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,87,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,229332,,,,12,16,,No,91,0,syn23665420
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case3/Normal_Human_Lung/Normal_Human_Lung_S1_L004_R1_001.fastq.gz,HTA3_8003_001,HTA3_8003_6976371411,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,87,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,229332,,,,12,16,,No,91,0,syn23665408
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case3/Normal_Human_Lung/Normal_Human_Lung_S1_L004_R2_001.fastq.gz,HTA3_8003_001,HTA3_8003_7901345485,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,87,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,229332,,,,12,16,,No,91,0,syn23665419
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/GGO_Human_Lung-1_4/GGO_Human_Lung-1_4_S4_L001_R1_001.fastq.gz,HTA3_8004_003,HTA3_8004_1805351001,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,82846,,,,12,16,,No,91,0,syn23665447
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/GGO_Human_Lung-1_4/GGO_Human_Lung-1_4_S4_L001_R2_001.fastq.gz,HTA3_8004_003,HTA3_8004_0394843352,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,82846,,,,12,16,,No,91,0,syn23665455
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/GGO_Human_Lung-1_4/GGO_Human_Lung-1_4_S4_L002_R1_001.fastq.gz,HTA3_8004_003,HTA3_8004_7227527498,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,82846,,,,12,16,,No,91,0,syn23665446
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/GGO_Human_Lung-1_4/GGO_Human_Lung-1_4_S4_L002_R2_001.fastq.gz,HTA3_8004_003,HTA3_8004_0128439250,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,82846,,,,12,16,,No,91,0,syn23665470
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/GGO_Human_Lung-1_4/GGO_Human_Lung-1_4_S4_L003_R1_001.fastq.gz,HTA3_8004_003,HTA3_8004_6509386876,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,82846,,,,12,16,,No,91,0,syn23665453
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/GGO_Human_Lung-1_4/GGO_Human_Lung-1_4_S4_L003_R2_001.fastq.gz,HTA3_8004_003,HTA3_8004_1150471006,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,82846,,,,12,16,,No,91,0,syn23665466
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/GGO_Human_Lung-1_4/GGO_Human_Lung-1_4_S4_L004_R1_001.fastq.gz,HTA3_8004_003,HTA3_8004_2786227063,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,82846,,,,12,16,,No,91,0,syn23665454
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/GGO_Human_Lung-1_4/GGO_Human_Lung-1_4_S4_L004_R2_001.fastq.gz,HTA3_8004_003,HTA3_8004_1432652420,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,82846,,,,12,16,,No,91,0,syn23665459
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/GGO_Human_Lung-2_4/GGO_Human_Lung-2_4_S5_L001_R1_001.fastq.gz,HTA3_8004_004,HTA3_8004_4843580733,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,134636,,,,12,16,,No,91,0,syn23665456
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/GGO_Human_Lung-2_4/GGO_Human_Lung-2_4_S5_L001_R2_001.fastq.gz,HTA3_8004_004,HTA3_8004_9174607036,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,134636,,,,12,16,,No,91,0,syn23665477
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/GGO_Human_Lung-2_4/GGO_Human_Lung-2_4_S5_L002_R1_001.fastq.gz,HTA3_8004_004,HTA3_8004_4385979265,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,134636,,,,12,16,,No,91,0,syn23665450
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/GGO_Human_Lung-2_4/GGO_Human_Lung-2_4_S5_L002_R2_001.fastq.gz,HTA3_8004_004,HTA3_8004_5022491988,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,134636,,,,12,16,,No,91,0,syn23665474
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/GGO_Human_Lung-2_4/GGO_Human_Lung-2_4_S5_L003_R1_001.fastq.gz,HTA3_8004_004,HTA3_8004_7279198626,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,134636,,,,12,16,,No,91,0,syn23665449
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/GGO_Human_Lung-2_4/GGO_Human_Lung-2_4_S5_L003_R2_001.fastq.gz,HTA3_8004_004,HTA3_8004_3900964761,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,134636,,,,12,16,,No,91,0,syn23665471
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/GGO_Human_Lung-2_4/GGO_Human_Lung-2_4_S5_L004_R1_001.fastq.gz,HTA3_8004_004,HTA3_8004_3649431389,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,134636,,,,12,16,,No,91,0,syn23665457
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/GGO_Human_Lung-2_4/GGO_Human_Lung-2_4_S5_L004_R2_001.fastq.gz,HTA3_8004_004,HTA3_8004_5736174098,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,134636,,,,12,16,,No,91,0,syn23665475
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/Normal_Human_Lung_4/Normal_Human_Lung_4_S3_L001_R1_001.fastq.gz,HTA3_8004_001,HTA3_8004_6532581508,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,93391,,,,12,16,,No,91,0,syn23665452
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/Normal_Human_Lung_4/Normal_Human_Lung_4_S3_L001_R2_001.fastq.gz,HTA3_8004_001,HTA3_8004_9195966860,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,93391,,,,12,16,,No,91,0,syn23665467
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/Normal_Human_Lung_4/Normal_Human_Lung_4_S3_L002_R1_001.fastq.gz,HTA3_8004_001,HTA3_8004_9640492529,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,93391,,,,12,16,,No,91,0,syn23665451
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/Normal_Human_Lung_4/Normal_Human_Lung_4_S3_L002_R2_001.fastq.gz,HTA3_8004_001,HTA3_8004_9310415618,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,93391,,,,12,16,,No,91,0,syn23665468
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/Normal_Human_Lung_4/Normal_Human_Lung_4_S3_L003_R1_001.fastq.gz,HTA3_8004_001,HTA3_8004_7074424907,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,93391,,,,12,16,,No,91,0,syn23665448
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/Normal_Human_Lung_4/Normal_Human_Lung_4_S3_L003_R2_001.fastq.gz,HTA3_8004_001,HTA3_8004_5601203113,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,93391,,,,12,16,,No,91,0,syn23665465
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/Normal_Human_Lung_4/Normal_Human_Lung_4_S3_L004_R1_001.fastq.gz,HTA3_8004_001,HTA3_8004_4646892401,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,93391,,,,12,16,,No,91,0,syn23665460
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/Normal_Human_Lung_4/Normal_Human_Lung_4_S3_L004_R2_001.fastq.gz,HTA3_8004_001,HTA3_8004_6705364162,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,93391,,,,12,16,,No,91,0,syn23665461
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/Tumor_Human_Lung_4/Tumor_Human_Lung_4_S6_L001_R1_001.fastq.gz,HTA3_8004_002,HTA3_8004_1804369660,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,209973,,,,12,16,,No,91,0,syn23665463
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/Tumor_Human_Lung_4/Tumor_Human_Lung_4_S6_L001_R2_001.fastq.gz,HTA3_8004_002,HTA3_8004_1315860394,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,209973,,,,12,16,,No,91,0,syn23665473
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/Tumor_Human_Lung_4/Tumor_Human_Lung_4_S6_L002_R1_001.fastq.gz,HTA3_8004_002,HTA3_8004_6798604081,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,209973,,,,12,16,,No,91,0,syn23665462
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/Tumor_Human_Lung_4/Tumor_Human_Lung_4_S6_L002_R2_001.fastq.gz,HTA3_8004_002,HTA3_8004_5681119930,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,209973,,,,12,16,,No,91,0,syn23665476
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/Tumor_Human_Lung_4/Tumor_Human_Lung_4_S6_L003_R1_001.fastq.gz,HTA3_8004_002,HTA3_8004_8699561822,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,209973,,,,12,16,,No,91,0,syn23665464
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/Tumor_Human_Lung_4/Tumor_Human_Lung_4_S6_L003_R2_001.fastq.gz,HTA3_8004_002,HTA3_8004_3087664438,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,209973,,,,12,16,,No,91,0,syn23665469
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/Tumor_Human_Lung_4/Tumor_Human_Lung_4_S6_L004_R1_001.fastq.gz,HTA3_8004_002,HTA3_8004_5421153361,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,209973,,,,12,16,,No,91,0,syn23665458
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case4/Tumor_Human_Lung_4/Tumor_Human_Lung_4_S6_L004_R2_001.fastq.gz,HTA3_8004_002,HTA3_8004_0286257566,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,80,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,209973,,,,12,16,,No,91,0,syn23665472
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case5/GGO_5/GGO_5_S8_L001_R1_001.fastq.gz,HTA3_8005_003,HTA3_8005_9220809877,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,74,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,71888,,,,12,16,,No,91,0,syn23665490
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case5/GGO_5/GGO_5_S8_L001_R2_001.fastq.gz,HTA3_8005_003,HTA3_8005_9670386642,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,74,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,71888,,,,12,16,,No,91,0,syn24862342
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case5/GGO_5/GGO_5_S8_L002_R1_001.fastq.gz,HTA3_8005_003,HTA3_8005_8897248069,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,74,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,71888,,,,12,16,,No,91,0,syn23665499
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case5/GGO_5/GGO_5_S8_L002_R2_001.fastq.gz,HTA3_8005_003,HTA3_8005_7369865820,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,74,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,71888,,,,12,16,,No,91,0,syn23665502
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case5/GGO_5/GGO_5_S8_L003_R1_001.fastq.gz,HTA3_8005_003,HTA3_8005_3414047703,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,74,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,71888,,,,12,16,,No,91,0,syn23665489
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case5/GGO_5/GGO_5_S8_L003_R2_001.fastq.gz,HTA3_8005_003,HTA3_8005_1911550239,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,74,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,71888,,,,12,16,,No,91,0,syn23665500
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case5/GGO_5/GGO_5_S8_L004_R1_001.fastq.gz,HTA3_8005_003,HTA3_8005_9448027036,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,74,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,71888,,,,12,16,,No,91,0,syn23665491
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case5/GGO_5/GGO_5_S8_L004_R2_001.fastq.gz,HTA3_8005_003,HTA3_8005_3120423795,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,74,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,71888,,,,12,16,,No,91,0,syn23665496
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case5/Normal_Lung_5/Normal_Lung_5_S7_L001_R1_001.fastq.gz,HTA3_8005_001,HTA3_8005_0831662673,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,74,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,110066,,,,12,16,,No,91,0,syn23665492
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case5/Normal_Lung_5/Normal_Lung_5_S7_L001_R2_001.fastq.gz,HTA3_8005_001,HTA3_8005_0757911127,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,74,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,110066,,,,12,16,,No,91,0,syn23665503
-ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case5/Normal_Lung_5/Normal_Lung_5_S7_L002_R1_001.fastq.gz,HTA3_8005_001,HTA3_8005_6079881122,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,74,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,110066,,,,12,16,,No,91,0,syn23665493
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+ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case6/Normal_Lung_6/Normal_Lung_6_S9_L001_R1_001.fastq.gz,HTA3_8006_001,HTA3_8006_7959435347,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,73,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,116540,,,,12,16,,No,91,0,syn23665520
+ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case6/Normal_Lung_6/Normal_Lung_6_S9_L001_R2_001.fastq.gz,HTA3_8006_001,HTA3_8006_8212174046,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,73,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,116540,,,,12,16,,No,91,0,syn23665530
+ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case6/Normal_Lung_6/Normal_Lung_6_S9_L002_R1_001.fastq.gz,HTA3_8006_001,HTA3_8006_7147976860,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,73,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,116540,,,,12,16,,No,91,0,syn23665522
+ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case6/Normal_Lung_6/Normal_Lung_6_S9_L002_R2_001.fastq.gz,HTA3_8006_001,HTA3_8006_3417628202,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,73,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,116540,,,,12,16,,No,91,0,syn23665528
+ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case6/Normal_Lung_6/Normal_Lung_6_S9_L003_R1_001.fastq.gz,HTA3_8006_001,HTA3_8006_3729148015,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,73,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,116540,,,,12,16,,No,91,0,syn23665519
+ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case6/Normal_Lung_6/Normal_Lung_6_S9_L003_R2_001.fastq.gz,HTA3_8006_001,HTA3_8006_4491877044,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,73,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,116540,,,,12,16,,No,91,0,syn23665525
+ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case6/Normal_Lung_6/Normal_Lung_6_S9_L004_R1_001.fastq.gz,HTA3_8006_001,HTA3_8006_0194609009,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R1,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,73,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,116540,,,,12,16,,No,91,0,syn23665515
+ScRNA-seqLevel1,sc_rna_seq_level_1/Linh_UCLA/Case6/Normal_Lung_6/Normal_Lung_6_S9_L004_R2_001.fastq.gz,HTA3_8006_001,HTA3_8006_7895825324,fastq,Single Cell,No,10x,Enzymatic Digestion,10xV3,R2,Cell Barcode and UMI,cDNA,3 Prime,Oligo-dT,No Spike In,Illumina NovaSeq 6000,16000,16000,0,0,73,0,https://doi.org/10.1002/cyto.b.21481,,,16,0,,GRCh38,116540,,,,12,16,,No,91,0,syn23665526
\ No newline at end of file
diff --git a/tests/test_completeness_summary.py b/tests/test_completeness_summary.py
new file mode 100644
index 0000000..d2dcf8e
--- /dev/null
+++ b/tests/test_completeness_summary.py
@@ -0,0 +1,20 @@
+"""Test CompletenessSummary"""
+from hdash.graph.graph_flattener import GraphFlattener
+from hdash.stats.completeness_summary import CompletenessSummary
+from hdash.graph.graph_creator import GraphCreator
+from hdash.validator.categories import Categories
+
+
+def test_completeness_summary(sample_meta_map):
+ meta_map = sample_meta_map
+ graph_creator = GraphCreator("HTA1", meta_map)
+ graph_flat = GraphFlattener(graph_creator.htan_graph)
+
+ stats = CompletenessSummary("HTA1", meta_map, graph_flat)
+ categories = Categories()
+ assert stats.has_data("HTA3_8001", categories.DEMOGRAPHICS)
+ assert stats.has_data("HTA3_8004", categories.DEMOGRAPHICS)
+ assert stats.has_data("HTA3_8001_001", categories.SC_RNA_SEQ_LEVEL_1)
+ assert stats.has_data("HTA3_8001_001", categories.SC_RNA_SEQ_LEVEL_2)
+ assert stats.has_data("HTA3_8001_001", categories.SC_RNA_SEQ_LEVEL_3)
+ assert stats.has_data("HTA3_8001_001", categories.SC_RNA_SEQ_LEVEL_4)
diff --git a/tests/test_graph_creator.py b/tests/test_graph_creator.py
new file mode 100644
index 0000000..d335ec2
--- /dev/null
+++ b/tests/test_graph_creator.py
@@ -0,0 +1,40 @@
+"""Test Graph Creator."""
+from hdash.graph.graph_creator import GraphCreator
+from hdash.synapse.meta_map import MetaMap
+from hdash.synapse.meta_file import MetaFile
+from hdash.synapse.table_util import TableUtil
+from hdash.graph.htan_graph import HtanGraph
+
+
+def test_graph_creator(sample_meta_map):
+ """Test Graph Creator."""
+ meta_map = sample_meta_map
+ graph_creator = GraphCreator("HTA1", meta_map)
+
+ # We should have 213 nodes and 271 edges
+ htan_graph = graph_creator.htan_graph
+ directed_graph = htan_graph.directed_graph
+ assert len(directed_graph.nodes) == 213
+ assert len(directed_graph.edges) == 271
+
+ # Verify a few nodes are in the graph
+ patient_node = directed_graph.nodes["HTA3_8001"]
+ assert patient_node[HtanGraph.DATA_KEY].meta_file.id == "synapse_1"
+ assert patient_node[HtanGraph.DATA_KEY].meta_file.category == "Demographics"
+
+ biospecimen_node = directed_graph.nodes["HTA3_8001_001"]
+ assert biospecimen_node[HtanGraph.DATA_KEY].meta_file.id == "synapse_2"
+ assert biospecimen_node[HtanGraph.DATA_KEY].meta_file.category == "Biospecimen"
+
+ assay_node = directed_graph.nodes["HTA3_8001_4651918348"]
+ assert assay_node[HtanGraph.DATA_KEY].meta_file.id == "synapse_3"
+ assert assay_node[HtanGraph.DATA_KEY].meta_file.category == "ScRNA-seqLevel1"
+
+ # Check for Specific Edges
+ assert directed_graph.edges["HTA3_8001_002", "HTA3_8001_4651918348"] != None
+ assert directed_graph.edges["HTA3_8001_002", "HTA3_8001_7837535366"] != None
+ assert directed_graph.edges["HTA3_8001_001", "HTA3_8001_7837535366"] != None
+
+ # Verify Adjacent Edges
+ adjacent_list = htan_graph.adjacent_list
+ assert len(adjacent_list) == 26
diff --git a/tests/test_graph_flattener.py b/tests/test_graph_flattener.py
new file mode 100644
index 0000000..de4f4d0
--- /dev/null
+++ b/tests/test_graph_flattener.py
@@ -0,0 +1,83 @@
+"""Test Graph Util class."""
+from hdash.graph.htan_graph import HtanGraph
+from hdash.graph.node_data import NodeData
+from hdash.graph.graph_flattener import GraphFlattener
+from hdash.validator.categories import Categories
+from hdash.synapse.meta_file import MetaFile
+
+
+def test_graph_flattener():
+ """"Test Graph Flattener."""
+
+ # Create Mock Graph
+ htan_graph = HtanGraph()
+
+ p1_meta_file = __create_mock_meta_file("synapse1", Categories.DEMOGRAPHICS)
+ p1 = NodeData("p1", p1_meta_file)
+ htan_graph.add_node(p1)
+
+ b1_meta_file = __create_mock_meta_file("synapse2", Categories.BIOSPECIMEN)
+ b1 = NodeData("b1", b1_meta_file)
+ htan_graph.add_node(b1)
+
+ b2_meta_file = __create_mock_meta_file("synapse3", Categories.BIOSPECIMEN)
+ b2 = NodeData("b2", b2_meta_file)
+ htan_graph.add_node(b2)
+
+ b3_meta_file = __create_mock_meta_file("synapse4", Categories.BIOSPECIMEN)
+ b3 = NodeData("b3", b3_meta_file)
+ htan_graph.add_node(b3)
+
+ s1_meta = __create_mock_meta_file("synapse5", Categories.SC_RNA_SEQ_LEVEL_1)
+ s1 = NodeData("s1", s1_meta)
+ htan_graph.add_node(s1)
+
+ s2_meta = __create_mock_meta_file("synapse6", Categories.SC_RNA_SEQ_LEVEL_2)
+ s2 = NodeData("s2", s2_meta)
+ htan_graph.add_node(s2)
+
+ s3_meta = __create_mock_meta_file("synapse7", Categories.SC_RNA_SEQ_LEVEL_3)
+ s3 = NodeData("s3", s3_meta)
+ htan_graph.add_node(s3)
+
+ htan_graph.add_edge("p1", "b1")
+ htan_graph.add_edge("p1", "b3")
+ htan_graph.add_edge("b1", "b2")
+ htan_graph.add_edge("b2", "s1")
+ htan_graph.add_edge("s1", "s2")
+ htan_graph.add_edge("s2", "s3")
+ htan_graph.add_edge("b3", "s3")
+
+ # Now Flatten
+ graph_flat = GraphFlattener(htan_graph)
+
+ # We should have 1 patient and 3 biospecimens
+ assert len(graph_flat.participant_id_set) == 1
+ assert len(graph_flat.biospecimen_id_set) == 3
+
+ # p1 should point to b1, b2, b3
+ biospecimen_list = graph_flat.participant_2_biopsecimens["p1"]
+ assert len(biospecimen_list) == 3
+ assert "b1" in biospecimen_list
+ assert "b2" in biospecimen_list
+ assert "b3" in biospecimen_list
+
+ # b1 should point to s1, s2 and s3
+ assay_list = graph_flat.biospecimen_2_assays["b1"]
+ assert len(assay_list) == 3
+ assert "s1" in assay_list
+ assert "s2" in assay_list
+ assert "s3" in assay_list
+
+ # b1 should have SCRNA-Seq Levels 1-3
+ categories = Categories()
+ assert graph_flat.biospecimen_has_assay("b1", categories.SC_RNA_SEQ_LEVEL_1)
+ assert graph_flat.biospecimen_has_assay("b1", categories.SC_RNA_SEQ_LEVEL_2)
+ assert graph_flat.biospecimen_has_assay("b1", categories.SC_RNA_SEQ_LEVEL_3)
+
+
+def __create_mock_meta_file(id, category):
+ meta_file = MetaFile()
+ meta_file.id = id
+ meta_file.category = category
+ return meta_file
diff --git a/tests/test_graph_util.py b/tests/test_graph_util.py
deleted file mode 100644
index 5c7119f..0000000
--- a/tests/test_graph_util.py
+++ /dev/null
@@ -1,77 +0,0 @@
-"""Test Graph Util class."""
-import networkx as nx
-import matplotlib.pyplot as plt
-from hdash.validator import htan_validator
-from hdash.graph.graph_util import GraphUtil
-from hdash.graph.graph import Node, Edge
-from hdash.validator.categories import Categories
-from hdash.synapse.table_util import TableUtil
-from hdash.synapse.meta_file import MetaFile
-
-
-def test_graph_util():
- """Test core Graph Utility Features."""
- node1 = Node()
- node1.id = "A111"
- node1.label = "A111 Node"
- node1.category = "Biospecimen"
-
- node2 = Node()
- node2.id = "A112"
- node2.label = "A112 Node"
- node2.category = "Biospecimen"
-
- edge = Edge()
- edge.source_id = node1.id
- edge.target_id = node2.id
-
- node_map = {node1.id: node1, node2.id: node2}
- edge_list = [edge]
-
- graph_util = GraphUtil(node_map, edge_list)
- data_list = graph_util.data_list
- assert len(data_list) == 3
-
-
-def test_real_graph():
- """Test Real Graph."""
-
- path_list = [
- "tests/data/demographics.csv",
- "tests/data/biospecimens.csv",
- "tests/data/single_cell_level1.csv",
- "tests/data/single_cell_level2.csv",
- "tests/data/single_cell_level3.csv",
- "tests/data/single_cell_level4.csv",
- ]
- meta_file_list = []
- tableUtil = TableUtil()
- for path in path_list:
- meta_file = MetaFile()
- meta_file.path = path
- tableUtil.annotate_meta_file(meta_file)
- meta_file_list.append(meta_file)
-
- validator = htan_validator.HtanValidator("HTA3", meta_file_list)
- graph_util = GraphUtil(validator.get_node_map(), validator.get_edge_list())
- data_list = graph_util.data_list
- assert len(data_list) == 483
-
- sif_list = graph_util.sif_list
- assert sif_list[0][0] == "D_HTA3_8001"
- assert sif_list[0][1] == "B_HTA3_8001_001"
-
- # Verify Participant Set
- participant_ids = graph_util.participant_id_set
- assert len(participant_ids) == 6
-
- # Verify Biospecimen Set
- biospecimen_ids = graph_util.participant_2_biopsecimens["HTA3_8001"]
- assert len(biospecimen_ids) == 2
- assert biospecimen_ids[0] == "HTA3_8001_001"
- assert biospecimen_ids[1] == "HTA3_8001_002"
-
- # Verify Downstream Assays are Linked to Parent Biospecimens
- biospecimens_2_assays = graph_util.assays_2_biospecimens
- assert biospecimens_2_assays["HTA3_8001_4651918348"] == "HTA3_8001_002"
- assert biospecimens_2_assays["HTA3_8001_3257504874"] == "HTA3_8001_002"
diff --git a/tests/test_heatmap_util.py b/tests/test_heatmap_util.py
index b98ac78..e93553a 100644
--- a/tests/test_heatmap_util.py
+++ b/tests/test_heatmap_util.py
@@ -1,69 +1,42 @@
"""Test HTAN Validator class."""
-from hdash.graph.graph_util import GraphUtil
-from hdash.synapse.htan_project import HTANProject
-from hdash.util.heatmap_util import HeatMapUtil
-from hdash.validator import htan_validator
-from hdash.stats import stats_summary
+from hdash.graph.graph_flattener import GraphFlattener
+from hdash.stats.completeness_summary import CompletenessSummary
+from hdash.graph.graph_creator import GraphCreator
+from hdash.synapse.meta_map import MetaMap
from hdash.synapse.meta_file import MetaFile
from hdash.synapse.table_util import TableUtil
-import pytest
+from hdash.util.heatmap_util import HeatMapUtil
-def test_heatmap_util():
+def test_heatmap_util(sample_meta_map):
"""Test HeatMap Util."""
- path_list = [
- "tests/data/demographics.csv",
- "tests/data/biospecimens.csv",
- "tests/data/single_cell_level1.csv",
- "tests/data/single_cell_level2.csv",
- "tests/data/single_cell_level3.csv",
- "tests/data/single_cell_level4.csv",
- ]
- meta_file_list = []
- tableUtil = TableUtil()
- for path in path_list:
- meta_file = MetaFile()
- meta_file.path = path
- tableUtil.annotate_meta_file(meta_file)
- meta_file_list.append(meta_file)
-
- # Run Validator to Extract the Graph
- validator = htan_validator.HtanValidator("HTA3", meta_file_list)
- meta_map = validator.meta_map
- graph_util = GraphUtil(validator.get_node_map(), validator.get_edge_list())
- assays_2_biospecimens = graph_util.assays_2_biospecimens
+ meta_map = sample_meta_map
+ graph_creator = GraphCreator("HTA1", meta_map)
+ graph_flat = GraphFlattener(graph_creator.htan_graph)
- # Run the Summary Stats
- stats = stats_summary.StatsSummary("HTA3", meta_map, assays_2_biospecimens)
+ stats = CompletenessSummary("HTA1", meta_map, graph_flat)
# Run HeatMap Util
- project = HTANProject()
- project.atlas_id = "HTA3"
- project.participant_id_set = stats.participant_id_set
- project.df_stats_map = stats.df_stats_map
- project.assays_2_biospecimens = assays_2_biospecimens
- project.participant_2_biopsecimens = graph_util.participant_2_biopsecimens
- heatmap_util = HeatMapUtil(project)
+ heatmap_util = HeatMapUtil("HTA1", stats)
+
heatmaps = heatmap_util.heatmaps
assert len(heatmaps) == 6
data0 = heatmaps[0].data
data1 = heatmaps[1].data
data2 = heatmaps[2].data
- # Test Clinical Tiers 1,2
+ # Validate Clinical Tiers 1,2
assert data0[0][0] == "HTA3_8001"
- assert data0[0][1] == 0.4375
+ assert data0[0][1] == 1
- # Test Clinical Tier 3
+ # Validate Clinical Tier 3
assert data1[0][0] == "HTA3_8001"
- assert data1[0][1] == 0.0
+ assert data1[0][1] == 0
- # Test Single Cell Assay, Levels 1
+ # Validate Single Cell Data
assert data2[0][0] == "HTA3_8001"
assert data2[0][1] == "HTA3_8001_001"
-
- # Completeness of Biospecimen Data
- assert data2[0][2] == pytest.approx(0.51, 0.01)
-
- # Completeness of Single Cell Level 1 Data
- assert data2[0][3] == pytest.approx(0.82, 0.01)
+ assert data2[0][2] == 1
+ assert data2[0][3] == 1
+ assert data2[0][4] == 1
+ assert data2[0][5] == 1
diff --git a/tests/test_meta_summary.py b/tests/test_meta_summary.py
new file mode 100644
index 0000000..6a9df8d
--- /dev/null
+++ b/tests/test_meta_summary.py
@@ -0,0 +1,13 @@
+"""Test HTAN Validator class."""
+from hdash.stats.meta_summary import MetaDataSummary
+from hdash.synapse.meta_map import MetaMap
+import pytest
+
+
+def test_meta_summary(sample_meta_map: MetaMap):
+ """Test Meta Summary."""
+ meta_map = sample_meta_map
+ meta_list = meta_map.meta_list_sorted
+ MetaDataSummary(meta_list)
+ assert meta_list[0].percent_meta_data_complete == pytest.approx(0.427, 0.01)
+ assert meta_list[2].percent_meta_data_complete == pytest.approx(0.82, 0.01)
diff --git a/tests/test_sif_writer.py b/tests/test_sif_writer.py
new file mode 100644
index 0000000..270808b
--- /dev/null
+++ b/tests/test_sif_writer.py
@@ -0,0 +1,16 @@
+"""Test Graph Creator."""
+from hdash.graph.graph_creator import GraphCreator
+from hdash.graph.sif_writer import SifWriter
+
+
+def test_sif_writer(sample_meta_map):
+ """Test SIF Writer."""
+ meta_map = sample_meta_map
+ graph_creator = GraphCreator("HTA1", meta_map)
+ directed_graph = graph_creator.htan_graph.directed_graph
+ sif_writer = SifWriter(directed_graph)
+
+ # Check for Specific Edges
+ sif = sif_writer.sif
+ assert "B_HTA3_8001_002\tconnect\tSC1_HTA3_8001_4651918348" in sif
+ assert "B_HTA3_8001_001 connect SC1_HTA3_8001_7837535366" in sif
diff --git a/tests/test_stats_summary.py b/tests/test_stats_summary.py
deleted file mode 100644
index 981d669..0000000
--- a/tests/test_stats_summary.py
+++ /dev/null
@@ -1,58 +0,0 @@
-"""Test HTAN Validator class."""
-from hdash.graph.graph_util import GraphUtil
-from hdash.validator import htan_validator
-from hdash.stats import stats_summary
-from hdash.synapse.table_util import TableUtil
-from hdash.synapse.meta_file import MetaFile
-import pytest
-
-
-def test_stats_summary():
- """Test Summary Stats."""
- path_list = [
- "tests/data/demographics.csv",
- "tests/data/biospecimens.csv",
- "tests/data/single_cell_level1.csv",
- "tests/data/single_cell_level2.csv",
- "tests/data/single_cell_level3.csv",
- "tests/data/single_cell_level4.csv",
- ]
- meta_file_list = []
- tableUtil = TableUtil()
- for path in path_list:
- meta_file = MetaFile()
- meta_file.path = path
- tableUtil.annotate_meta_file(meta_file)
- meta_file_list.append(meta_file)
-
- # Run Validator to Extract the Graph
- validator = htan_validator.HtanValidator("HTA3", meta_file_list)
- meta_map = validator.meta_map
- graph_util = GraphUtil(validator.get_node_map(), validator.get_edge_list())
- assays_2_biospecimens = graph_util.assays_2_biospecimens
-
- # Run the Summary Stats
- stats = stats_summary.StatsSummary("HTA3", meta_map, assays_2_biospecimens)
- participant_id_set = stats.participant_id_set
- stats_map = stats.df_stats_map
-
- # Verify Participant ID Set
- assert "HTA3_8001" in participant_id_set
- assert "HTA3_8004" in participant_id_set
-
- # Verify Completeness of HTA3_8001:Demographics
- # 44% is based on manual inspection of HTA3_8001
- assert stats_map.get("HTA3_8001:Demographics") == 0.4375
-
- # Verify Completeness of HTA3_8004:Demographics
- # 38% is based on manual inspection of HTA3_8004
- assert stats_map.get("HTA3_8004:Demographics") == 0.375
-
- # Verify Completeness of HTA3_8001_001:Biospecimen
- assert stats_map.get("HTA3_8001_001:Biospecimen") == pytest.approx(0.51, 0.01)
-
- # Verify Completeness of Downstream Assays
- assert stats_map.get("HTA3_8001_001:ScRNA-seqLevel1") == pytest.approx(0.82, 0.01)
- assert stats_map.get("HTA3_8001_001:ScRNA-seqLevel2") == pytest.approx(0.67, 0.01)
- assert stats_map.get("HTA3_8001_001:ScRNA-seqLevel3") == pytest.approx(0.79, 0.01)
- assert stats_map.get("HTA3_8001_001:ScRNA-seqLevel4") == pytest.approx(0.80, 0.01)
diff --git a/tests/test_validator.py b/tests/test_validator.py
index 271d2c3..aedfe78 100644
--- a/tests/test_validator.py
+++ b/tests/test_validator.py
@@ -1,13 +1,25 @@
"""Test HTAN Validator class."""
from hdash.validator import htan_validator
-from hdash.synapse.table_util import TableUtil
-from hdash.synapse.meta_file import MetaFile
+from hdash.graph.graph_creator import GraphCreator
+from hdash.synapse.meta_map import MetaMap
+from conftest import _create_meta_file_list
+
def test_validator():
"""Test core HTAN Validator."""
path_list = ["tests/data/demographics.csv", "tests/data/biospecimens.csv"]
meta_file_list = _create_meta_file_list(path_list)
- validator = htan_validator.HtanValidator("HTA3", meta_file_list)
+
+ # Create the MetaMap
+ meta_map = MetaMap()
+ for meta_file in meta_file_list:
+ meta_map.add_meta_file(meta_file)
+
+ # Create the Graph
+ graph_creator = GraphCreator("HTA3", meta_map)
+ htan_graph = graph_creator.htan_graph
+
+ validator = htan_validator.HtanValidator("HTA3", meta_map, htan_graph)
validation_list = validator.get_validation_list()
assert len(validation_list) == 7
@@ -18,35 +30,7 @@ def test_validator():
assert validation_list[4].validation_passed()
assert not validation_list[5].validation_passed()
error_list = validation_list[5].error_list
- assert error_list[0].startswith("Biospecimen references adjacent ID: ")
+ assert error_list[0].startswith(
+ "HTA3_8001_001 references adjacent ID=HTA3_8001_1002"
+ )
assert validation_list[6].validation_passed()
-
-
-def test_graph():
- """Test Links and Graph Creation."""
- path_list = [
- "tests/data/demographics.csv",
- "tests/data/biospecimens.csv",
- "tests/data/single_cell_level1.csv",
- "tests/data/single_cell_level2.csv",
- "tests/data/single_cell_level3.csv",
- "tests/data/single_cell_level4.csv",
- ]
- meta_file_list = _create_meta_file_list(path_list)
-
- validator = htan_validator.HtanValidator("HTA3", meta_file_list)
- node_map = validator.get_node_map()
- edge_list = validator.get_edge_list()
- assert len(node_map) == 213
- assert len(edge_list) == 270
-
-
-def _create_meta_file_list(path_list: list[str]):
- meta_file_list = []
- tableUtil = TableUtil()
- for path in path_list:
- meta_file = MetaFile()
- meta_file.path = path
- tableUtil.annotate_meta_file(meta_file)
- meta_file_list.append(meta_file)
- return meta_file_list
\ No newline at end of file