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317
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Dataset results
317 results for “Hierarchy”
Single-cell lineage tracing uncovers unique skin adipose hierarchy and Sox9-mediated differentiation of adipocyte precursors
GEO Series GSE241627. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Dominance hierarchy arising from the evolution of a complex small RNA regulatory network
GEO Series GSE57267. Arabidopsis lyrata; Arabidopsis halleri. 12 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (scRNA-Seq of BM lineage-negative Sca1+ CD117+ CD150+CD48-cells)
GEO Series GSE141472. Mus musculus. 305 samples. Type: Expression profiling by high throughput sequencing.
A pro B cell population forms the apex of the leukemic hierarchy in Hoxa9/Meis1-dependent AML
GEO Series GSE199756. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
The cellular hierarchy of acute myeloid leukemia informs personalized treatment
GEO Series GSE272681. Homo sapiens. 108 samples. Type: Expression profiling by high throughput sequencing.
Genome editing by dual nucleases records deep lineage hierarchy with high fidelity.
GEO Series GSE236936. Mus musculus; Homo sapiens. 14 samples. Type: Expression profiling by high throughput sequencing; Other.
Gene expression analysis of tumor sorted fractions demarcating cancer stem cell hierarchy and DNA content based ploidy
GEO Series GSE74853. Homo sapiens. 15 samples. Type: Expression profiling by array.
A unified workflow to define multipotent progenitor hierarchies
GEO Series GSE266609. Mus musculus. 418 samples. Type: Other; Expression profiling by high throughput sequencing.
A unified workflow to define multipotent progenitor hierarchies (HIVE)
GEO Series GSE266523. Mus musculus. 6 samples. Type: Other.
Single-cell transcriptional atlas of hematopoiesis reveals genetic and hierarchy-based determinants of aberrant differentiation in AML
GEO Series GSE289435. Homo sapiens. 13 samples. Type: Expression profiling by high throughput sequencing.
A pro B cell population forms the apex of the leukemic hierarchy in Hoxa9/Meis1-dependent AML
GEO Series GSE204676. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
A unified workflow to define multipotent progenitor hierarchies (CITE-Seq and CellTag)
GEO Series GSE266608. Mus musculus. 63 samples. Type: Expression profiling by high throughput sequencing; Other.
Nuclear cholesterol regulates nuclear size and DNA damage responses in the tumor hierarchy
GEO Series GSE246908. Homo sapiens. 18 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Single-cell RNA sequencing of 76,535 capillary PBMCs from 3 donors across 28 samples, freshly isolated or on ice for 24h with manual 4-layer annotation hierarchy
<p><strong>Sample Procurement</strong></p> <p>Samples were collected directly from participants as part of ImYoo's "Single-cell immune profiling from self-collected capillary blood" study, approved by Advarra IRB (Protocol #Pro00057361).</p> <p><strong>Sample Processing</strong></p> <p>Whole capillary blood samples were self-collected from participants using the <a href="https://yourbiohealth.com/en-us/virtually-painless-blood-collection-devices-for-clinical-trials-and-wellness-testing">TAP II</a> device. Samples were either processed shortly after collection, or if being stored for longer than 4 hours, were kept in a styrofoam cooler with ice packs. Cells were isolated using <a href="https://www.stemcell.com/products/easysep-direct-human-pbmc-isolation-kit.html">EasySep Direct Human PBMC Isolation Kit</a> (STEMCELL Technologies Catalog #19654) and cryopreserved using <a href="https://www.stemcell.com/cryostor-cs10.html">CryoStor CS10</a> (STEMCELL Technologies Catalog #07930). Upon thawing, samples were labeled in accordance with the MULTI-seq protocol (<a href="https://www.nature.com/articles/s41592-019-0433-8">https://www.nature.com/articles/s41592-019-0433-8</a>) and then processed on a 10X Genomics Chromium, using either the Chromium Next GEM Single Cell 3' Kit v3.1 (10X Genomics Product Code 1000269) or Chromium Next GEM Single Cell 3’ HT Kit v3.1 (10X Genomics Product Code 1000370). DNA libraries were sequenced on either a NovaSeq 6000 or NextSeq 550.</p> <p><strong>Data Processing</strong></p> <p>Transcriptomic sequencing data was processed using Cell Ranger v7.0.1 with default parameters. Multiplexing oligo sequencing data was processed through a custom python script that counts the number of occurrences of each sample barcode sequence and assigns it to the corresponding cell barcode. Samples were demultiplexed using a custom algorithm that estimates the background sample barcode counts, and assigns each cell a probability of belonging to each sample. Cell typing was done as part of a larger dataset and consisted of iterative manual assignments of clusters to cell types. For each cell subtype detected, a new model was trained on just the cells of that type, and the process was repeated.</p> <p><strong>Metadata Fields</strong></p> <ul> <li><strong>barcode:</strong> Original chromium cell barcode</li> <li><strong>Sample IDs:</strong> Unique ID for the experimental sample that was processed with 10x Chromium, could have come from the same biological sample (identified by <strong>original_sample_id</strong>)</li> <li><strong>Participant IDs:</strong> Unique ID for participant (here there are three participants: 2, 3 and 51)</li> <li><strong>Cell Barcoding Runs:</strong> Unique ID for the 10x Chromium cell barcoding run in which that sample was processed. Multiple samples can be processed in a cell barcoding run.</li> <li><strong>Lane:</strong> ID of which Chromium chip lane the cell came from</li> <li><strong>extraction_protocol:</strong> How the PBMCs were isolated from whole blood. In this dataset all samples were processed with the TAP device.</li> <li><strong>sample_processing_delay_seconds:</strong> The amount of time (in seconds) between when the blood was extracted from the participant and when PBMC isolation + cryopreservation was performed</li> <li><strong>cell_barcoding_delay_days:</strong> How long PBMC samples were stored in liquid nitrogen prior to being thawed and processed on 10x</li> <li><strong>cell_barcoding_protocol</strong>: Which single cell RNA sequencing experimental protocol was used. Here all samples were processed with 10x v3.1 chemistry.</li> <li><strong>run_lane_batch:</strong> Concatenation of columns <strong>Cell Barcoding Runs</strong> and <strong>Lane</strong> to provide a unique ID for experimental processing batch (i.e. the DNA library)</li> <li><strong>cell_type_level_1:</strong> Level 1 of a 4-tier PBMC ontology that does not provide a label for low quality cells - those were left as NaNs.</li> <li><strong>cell_type_level_2:</strong> Level 2 of a 4-tier PBMC ontology that does not provide a label for low quality cells - those were left as NaNs.</li> <li><strong>cell_type_level_3:</strong> Level 3 of a 4-tier PBMC ontology that does not provide a label for low quality cells - those were left as NaNs.</li> <li><strong>cell_type_level_4:</strong> Level 4 of a 4-tier PBMC ontology that does not provide a label for low quality cells - those were left as NaNs.</li> <li><strong>c1:</strong> Level 1 of a 4-tier PBMC ontology that also provides label for low quality cells, such as Debris, Doublets, experimental artifacts and others. These additional labels can be used for creating a junk detector.</li> <li><strong>c2:</strong> Level 1 of a 4-tier PBMC ontology that also provides label for low quality cells, such as Debris, Doublets, experimental artifacts and others. These additional labels can be used for creating a junk detector.</li> <li><strong>c3:</strong> Level 1 of a 4-tier PBMC ontology that also provides label for low quality cells, such as Debris, Doublets, experimental artifacts and others. These additional labels can be used for creating a junk detector.</li> <li><strong>c4:</strong> Level 1 of a 4-tier PBMC ontology that also provides label for low quality cells, such as Debris, Doublets, experimental artifacts and others. These additional labels can be used for creating a junk detector.</li> <li><strong>original_sample_id:</strong> Some samples were derived from the same originating whole blood sample. This field specifies the source of the whole blood sample.</li> </ul>
Overexpression of miR-155 alters the hierarchy of gene master regulators in the adenocarcinomic human alveolar basal epithelial cell line A549
GEO Series GSE116575. Homo sapiens. 4 samples. Type: Expression profiling by array.
A unified workflow to define multipotent progenitor hierarchies [Fluidigm]
GEO Series GSE266522. Mus musculus. 337 samples. Type: Other.
Mapping the human hematopoietic stem and progenitor cell hierarchy through integrated single-cell proteomics and transcriptomics
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.