[ [ [ "DC_expMatrix_DCnMono.tab.gz" ], { "name": "DC_expMatrix_DCnMono.tab", "description": "A data set of 1140 cells from human blood samples. The included cell types are dendritic cells (DCs) with mutants overexpressed for marker genes CD141+ or CD1C+, a double negative mutant CD11C+/CD141-/CD1C-, monocytes and plasmacytoid DCs. Gene expression is measured as raw count data on 26,593 genes.", "collection": "GEO", "version": "1.3", "year": 2017, "instances": 1140, "missing": 0, "variables": 26595, "source": "NCBI", "url": "https://datasets.biolab.si/DC_expMatrix_DCnMono.tab.gz", "domain": "sc", "language": "English", "target": "categorical", "location": "DC_expMatrix_DCnMono.tab.gz", "size": 20325076, "publication_status": 0, "tag": "expression", "tags": [ "expression", "human", "homo-sapiens", "blood" ], "title": "Dendritic cells and monocytes in human blood", "references": [ "Villani, A. C., Satija, ... Jardine, L. (2017). Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors. Science, 356(6335)." ], "taxid": 9606, "num_of_genes": 26593 } ], [ [ "DC_expMatrix_deeper.characterization.tab.gz" ], { "name": "DC_expMatrix_deeper.characterization.tab", "description": "A data set of 1244 cells from human blood samples. The included cell types are dendritic cells (DCs) with mutants overexpressed for marker genes CD141+, CD1C+, pathogenic cells driving blastic plasmacytoid dendritic cell neoplasm (BPDCN) from four donors, a double negative mutant CD11C+/CD141-/CD1C-, monocytes and plasmacytoid DCs, and cells FACS sorted for AXL6+/SIGLEC+ forming a new DC subplopulation.", "collection": "GEO", "version": "1.3", "year": 2017, "instances": 1244, "missing": 0, "variables": 26595, "source": "NCBI", "url": "https://datasets.biolab.si/DC_expMatrix_deeper.characterization.tab.gz", "domain": "sc", "language": "English", "target": "categorical", "location": "DC_expMatrix_deeper.characterization.tab.gz", "size": 18994431, "publication_status": 0, "tag": "expression", "tags": [ "expression", "human", "homo-sapiens", "blood" ], "title": "Dendritic cells and monocytes in human blood (deeper characterization)", "references": [ "Villani, A. C., Satija, ... Jardine, L. (2017). Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors. Science, 356(6335)." ], "taxid": 9606, "num_of_genes": 26593 } ], [ [ "aml-1k.tab.gz" ], { "name": "aml-1k.tab", "description": "Gene expressions in bone marrow mononuclear cells from a patient with acute myeloid leukemia (AML) and two healthy donors used as controls. The data includes a sample of 1000 cells and 1000 genes with the highest dispersion. This is a sample data that comes with Loupe Cell Browser, and includes cells from three separate experiments with data sets published on 10x Genomics single-cell data sets page: AML027 Pre-transplant BMMCs, Frozen BMMCs (Healthy Control 1), and Frozen BMMCs (Healthy Control 2).", "collection": "10x Genomics", "version": "1.3", "year": 2017, "instances": 1000, "missing": 0, "variables": 1004, "source": "10x Genomics", "url": "https://datasets.biolab.si/aml-1k.tab.gz", "domain": "sc", "language": "English", "target": "categorical", "location": "aml-1k.tab.gz", "size": 353229, "publication_status": 0, "tag": "aml", "tags": [ "aml", "expression", "sample" ], "title": "Bone marrow mononuclear cells with AML (sample)", "references": [ "Zheng, G. X., Terry, J. M., ... Gregory, M. T. (2017). Massively parallel digital transcriptional profiling of single cells. Nature communications, 8, 14049." ], "taxid": 9606, "num_of_genes": 1000 } ], [ [ "aml-8k.tab.gz" ], { "name": "aml-8k.tab", "description": "Gene expressions in bone marrow mononuclear cells from a patient with acute myeloid leukemia (AML) and two healthy donors used as controls. The data includes over 8000 cells and 1000 genes with the highest dispersion. This is a data that comes with Loupe Cell Browser, and includes cells from three separate experiments with data sets published on 10x Genomics single-cell data sets page: AML027 Pre-transplant BMMCs, Frozen BMMCs (Healthy Control 1), and Frozen BMMCs (Healthy Control 2).", "collection": "10x Genomics", "version": "1.3", "year": 2017, "instances": 8390, "missing": 0, "variables": 1004, "source": "10x Genomics", "url": "https://datasets.biolab.si/aml-8k.tab.gz", "domain": "sc", "language": "English", "target": "categorical", "location": "aml-8k.tab.gz", "size": 2859987, "publication_status": 0, "tag": "aml", "tags": [ "aml", "expression" ], "title": "Bone marrow mononuclear cells with AML", "references": [ "Zheng, G. X., Terry, J. M., ... Gregory, M. T. (2017). Massively parallel digital transcriptional profiling of single cells. Nature communications, 8, 14049." ], "taxid": 9606, "num_of_genes": 1000 } ], [ [ "baron2016_pancreas_human.pkl.gz" ], { "name": "baron2016_pancreas_human.pkl", "description": "Single-cell RNA sequencing of pancreatic islets from 4 human donors", "collection": "GEO", "version": "3.0", "year": 2016, "instances": 8569, "missing": 0, "variables": 20130, "source": "GEO", "url": "https://datasets.biolab.si/baron2016_pancreas_human.pkl.gz", "domain": "sc", "language": "English", "target": "categorical", "location": "baron2016_pancreas_human.pkl.gz", "size": 22304736, "publication_status": 0, "tag": "human", "tags": [ "human", "expression", "pancreas" ], "title": "Pancreas cells in human", "references": [ "Baron, M., Veres, A., Wolock, S. L., Faust, A. L., Gaujoux, R., Vetere, A., ... & Melton, D. A. (2016). A single-cell transcriptomic map of the human and mouse pancreas reveals inter-and intra-cell population structure. Cell systems, 3(4), 346-360." ], "taxid": 9606, "num_of_genes": 8569 } ], [ [ "baron2016_pancreas_human_sample.tab.gz" ], { "name": "baron2016_pancreas_human_sample.tab", "description": "A sample of transcriptomes of major pancreatic cell types from one human donor.", "collection": "GEO", "version": "3.0", "year": 2016, "instances": 1631, "missing": 0, "variables": 5015, "source": "GEO", "url": "https://datasets.biolab.si/baron2016_pancreas_human_sample.tab.gz", "domain": "sc", "language": "English", "target": "categorical", "location": "baron2016_pancreas_human_sample.tab.gz", "size": 1376129, "publication_status": 0, "tag": "human", "tags": [ "human", "expression", "pancreas" ], "title": "Pancreas cells in human (sample)", "references": [ "Baron, M., Veres, A., Wolock, S. L., Faust, A. L., Gaujoux, R., Vetere, A., ... & Melton, D. A. (2016). A single-cell transcriptomic map of the human and mouse pancreas reveals inter-and intra-cell population structure. Cell systems, 3(4), 346-360." ], "taxid": 9606, "num_of_genes": 5010 } ], [ [ "ccp_data_Tcells_normCounts.counts.all_genes.tab.gz" ], { "name": "ccp_data_Tcells_normCounts.counts.all_genes.tab", "description": "Na\u00efve CD4+ cells from spleens of IL-13eGFP Balb/c mice were negatively selected and differentiated toward TH2 in anti-CD3/CD28 coated plates. Gene expression was normalized with respect to ERCC spike-ins. Cell cycle stage of the cells is not known, but relevant marker genes can be used. The complete dataset contains expression of 38,293 genes.", "collection": "EBI", "version": "1.3", "year": 2014, "instances": 81, "missing": 0, "variables": 38293, "source": "ArrayExpress", "url": "https://datasets.biolab.si/ccp_data_Tcells_normCounts.counts.all_genes.tab.gz", "domain": "sc", "language": "English", "target": "none", "location": "ccp_data_Tcells_normCounts.counts.all_genes.tab.gz", "size": 4650642, "publication_status": 0, "tag": "mouse", "tags": [ "mouse", "expression", "tcell", "mus-musculus" ], "title": "Cell cycle in T-cells", "references": [ "Mahata, B., Zhang, X., ... Arlt, W. (2014). Single-cell RNA sequencing reveals T helper cells synthesizing steroids de novo to contribute to immune homeostasis. Cell reports, 7(4), 1130-1142.", "Buettner, F., Natarajan, K. N., ... Stegle, O. (2015). Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells. Nature biotechnology, 33(2), 155-160." ], "taxid": 10090, "num_of_genes": 38293 } ], [ [ "ccp_data_Tcells_normCounts.counts.cycle_genes.tab.gz" ], { "name": "ccp_data_Tcells_normCounts.counts.cycle_genes.tab", "description": "Na\u00efve CD4+ cells from spleens of IL-13eGFP Balb/c mice were negatively selected and differentiated toward TH2 in anti-CD3/CD28 coated plates. Gene expression was normalized with respect to ERCC spike-ins. Cell cycle stage of the cells is not known, but relevant marker genes can be used. The reduced data set contains expression of 553 genes related to cell cycle based on Gene Ontology (GO) terms.", "collection": "EBI", "version": "1.3", "year": 2014, "instances": 81, "missing": 0, "variables": 553, "source": "ArrayExpress", "url": "https://datasets.biolab.si/ccp_data_Tcells_normCounts.counts.cycle_genes.tab.gz", "domain": "sc", "language": "English", "target": "none", "location": "ccp_data_Tcells_normCounts.counts.cycle_genes.tab.gz", "size": 230943, "publication_status": 0, "tag": "mouse", "tags": [ "mouse", "expression", "tcell", "mus-musculus" ], "title": "Cell cycle in T-cells (cell cycle genes)", "references": [ "Mahata, B., Zhang, X., ... Arlt, W. (2014). Single-cell RNA sequencing reveals T helper cells synthesizing steroids de novo to contribute to immune homeostasis. Cell reports, 7(4), 1130-1142.", "Buettner, F., Natarajan, K. N., ... Stegle, O. (2015). Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells. Nature biotechnology, 33(2), 155-160." ], "taxid": 10090, "num_of_genes": 553 } ], [ [ "ccp_data_liver.counts.all_genes.tab.gz" ], { "name": "ccp_data_liver.counts.all_genes.tab", "description": "Five liver cells, sequenced using the Smart-seq protocol. Since most liver cells do not proliferate, they are expected to be in G1 cycle phase. The instances in the data set are therefore not labelled (with cell cycle information). The complete dataset contains expression of 20,683 genes.", "collection": "GEO", "version": "1.3", "year": 2014, "instances": 5, "missing": 0, "variables": 20683, "source": "NCBI", "url": "https://datasets.biolab.si/ccp_data_liver.counts.all_genes.tab.gz", "domain": "sc", "language": "English", "target": "none", "location": "ccp_data_liver.counts.all_genes.tab.gz", "size": 197362, "publication_status": 0, "tag": "mouse", "tags": [ "mouse", "expression", "liver", "mus-musculus" ], "title": "Cell cycle in mouse liver", "references": [ "Deng, Q., Ramsk\u00f6ld, D., Reinius, B., Sandberg, R. (2014). Single-cell RNA-seq reveals dynamic, random monoallelic gene expression in mammalian cells. Science, 343(6167), 193-196.", "Scialdone, A., Natarajan, K. N., Saraiva, L. R., ... Buettner, F. (2015). Computational assignment of cell-cycle stage from single-cell transcriptome data. Methods, 85, 54-61." ], "taxid": 10090, "num_of_genes": 20683 } ], [ [ "ccp_data_liver.counts.cycle_genes.tab.gz" ], { "name": "ccp_data_liver.counts.cycle_genes.tab", "description": "Five liver cells, sequenced using the Smart-seq protocol. Since most liver cells do not proliferate, they are expected to be in G1 cycle phase. The instances in the data set are therefore not labelled (with cell cycle information). The reduced data set contains expression of 537 genes related to cell cycle based on Gene Ontology (GO) terms.", "collection": "GEO", "version": "1.3", "year": 2014, "instances": 5, "missing": 0, "variables": 537, "source": "NCBI", "url": "https://datasets.biolab.si/ccp_data_liver.counts.cycle_genes.tab.gz", "domain": "sc", "language": "English", "target": "none", "location": "ccp_data_liver.counts.cycle_genes.tab.gz", "size": 5841, "publication_status": 0, "tag": "mouse", "tags": [ "mouse", "expression", "liver", "mus-musculus" ], "title": "Cell cycle in mouse liver (cell cycle genes)", "references": [ "Deng, Q., Ramsk\u00f6ld, D., Reinius, B., Sandberg, R. (2014). Single-cell RNA-seq reveals dynamic, random monoallelic gene expression in mammalian cells. Science, 343(6167), 193-196.", "Scialdone, A., Natarajan, K. N., Saraiva, L. R., ... Buettner, F. (2015). Computational assignment of cell-cycle stage from single-cell transcriptome data. Methods, 85, 54-61." ], "taxid": 10090, "num_of_genes": 537 } ], [ [ "ccp_data_mESCbulk.counts.all_genes.tab.gz" ], { "name": "ccp_data_mESCbulk.counts.all_genes.tab", "description": "Mouse embryonic stem cells (mESCs) were FACS sorted for cell cycle stages (G1, S and G2M). Approximately 150,000\u2013300,000 cells from an asynchronous population and from each cell cycle fractions (G1, S and G2M) were used for bulk mRNA sequencing, with libraries being generated using the Illumina TruSeq Stranded RNA Sample preparation kit. All libraries were prepared and sequenced using the Wellcome Trust Sanger Institute sample preparation pipeline. Sequencing quality control and data quality checks were performed by the Sanger Sequencing facility. The complete dataset contains expression of 38,293 genes.", "collection": "EBI", "version": "1.3", "year": 2015, "instances": 4, "missing": 0, "variables": 38294, "source": "ArrayExpress", "url": "https://datasets.biolab.si/ccp_data_mESCbulk.counts.all_genes.tab.gz", "domain": "sc", "language": "English", "target": "categorical", "location": "ccp_data_mESCbulk.counts.all_genes.tab.gz", "size": 383715, "publication_status": 0, "tag": "mouse", "tags": [ "mouse", "expression", "mesc", "mus-musculus", "rna-seq" ], "title": "Cell cycle in mESC (bulk RNA-seq)", "references": [ "Scialdone, A., Natarajan, K. N., Saraiva, L. R., ... Buettner, F. (2015). Computational assignment of cell-cycle stage from single-cell transcriptome data. Methods, 85, 54-61." ], "taxid": 10090, "num_of_genes": 38293 } ], [ [ "ccp_data_mESCbulk.counts.cycle_genes.tab.gz" ], { "name": "ccp_data_mESCbulk.counts.cycle_genes.tab", "description": "Mouse embryonic stem cells (mESCs) were FACS sorted for cell cycle stages (G1, S and G2M). Approximately 150,000\u2013300,000 cells from an asynchronous population and from each cell cycle fractions (G1, S and G2M) were used for bulk mRNA sequencing, with libraries being generated using the Illumina TruSeq Stranded RNA Sample preparation kit. All libraries were prepared and sequenced using the Wellcome Trust Sanger Institute sample preparation pipeline. Sequencing quality control and data quality checks were performed by the Sanger Sequencing facility. The reduced data set contains expression of 553 genes related to cell cycle based on Gene Ontology (GO) terms.", "collection": "EBI", "version": "1.3", "year": 2015, "instances": 4, "missing": 0, "variables": 554, "source": "ArrayExpress", "url": "https://datasets.biolab.si/ccp_data_mESCbulk.counts.cycle_genes.tab.gz", "domain": "sc", "language": "English", "target": "categorical", "location": "ccp_data_mESCbulk.counts.cycle_genes.tab.gz", "size": 9879, "publication_status": 0, "tag": "mouse", "tags": [ "mouse", "expression", "mesc", "mus-musculus", "rna-seq" ], "title": "Cell cycle in mESC (bulk RNA-seq, cell cycle genes)", "references": [ "Scialdone, A., Natarajan, K. N., Saraiva, L. R., ... Buettner, F. (2015). Computational assignment of cell-cycle stage from single-cell transcriptome data. Methods, 85, 54-61." ], "taxid": 10090, "num_of_genes": 553 } ], [ [ "ccp_normCountsBuettnerEtAl.counts.all_genes.tab.gz" ], { "name": "ccp_normCountsBuettnerEtAl.counts.all_genes.tab", "description": "A single-cell RNA-seq dataset comprised of 182 mouse embryonic stem cells (mESCs) with known cell-cycle phase. Cells were sorted using FACS for three different cell-cycle phases. This resulted in a filtered set of 59 cells in G1 phase, 58 cells in S phase and 65 cells in G2M phase. Next, single-cell RNA-seq was performed using the C1 Single Cell Auto Prep System (Fluidigm). The raw read counts were normalised using two different size factors derived from endogenous genes and ERCC spike-ins. The complete dataset contains expression of 38,293 genes.", "collection": "EBI", "version": "1.3", "year": 2015, "instances": 182, "missing": 0, "variables": 38294, "source": "ArrayExpress", "url": "https://datasets.biolab.si/ccp_normCountsBuettnerEtAl.counts.all_genes.tab.gz", "domain": "sc", "language": "English", "target": "categorical", "location": "ccp_normCountsBuettnerEtAl.counts.all_genes.tab.gz", "size": 4110383, "publication_status": 0, "tag": "mouse", "tags": [ "mouse", "expression", "mesc", "mus-musculus" ], "title": "Cell cycle in mESC (Fluidigm)", "references": [ "Buettner, F., Natarajan, K. N., ... Stegle, O. (2015). Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells. Nature biotechnology, 33(2), 155-160.", "Scialdone, A., Natarajan, K. N., Saraiva, L. R., ... Buettner, F. (2015). Computational assignment of cell-cycle stage from single-cell transcriptome data. Methods, 85, 54-61." ], "taxid": 10090, "num_of_genes": 38293 } ], [ [ "ccp_normCountsBuettnerEtAl.counts.cycle_genes.tab.gz" ], { "name": "ccp_normCountsBuettnerEtAl.counts.cycle_genes.tab", "description": "A single-cell RNA-seq dataset comprised of 182 mouse embryonic stem cells (mESCs) with known cell-cycle phase. Cells were sorted using FACS for three different cell-cycle phases. This resulted in a filtered set of 59 cells in G1 phase, 58 cells in S phase and 65 cells in G2M phase. Next, single-cell RNA-seq was performed using the C1 Single Cell Auto Prep System (Fluidigm). The raw read counts were normalised using two different size factors derived from endogenous genes and ERCC spike-ins. The reduced data set contains expression of 563 genes related to cell cycle based on Gene Ontology (GO) terms.", "collection": "EBI", "version": "1.3", "year": 2015, "instances": 182, "missing": 0, "variables": 564, "source": "ArrayExpress", "url": "https://datasets.biolab.si/ccp_normCountsBuettnerEtAl.counts.cycle_genes.tab.gz", "domain": "sc", "language": "English", "target": "categorical", "location": "ccp_normCountsBuettnerEtAl.counts.cycle_genes.tab.gz", "size": 150014, "publication_status": 0, "tag": "mouse", "tags": [ "mouse", "expression", "mesc", "mus-musculus" ], "title": "Cell cycle in mESC (Fluidigm, cell cycle genes)", "references": [ "Buettner, F., Natarajan, K. N., ... Stegle, O. (2015). Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells. Nature biotechnology, 33(2), 155-160.", "Scialdone, A., Natarajan, K. N., Saraiva, L. R., ... Buettner, F. (2015). Computational assignment of cell-cycle stage from single-cell transcriptome data. Methods, 85, 54-61." ], "taxid": 10090, "num_of_genes": 563 } ], [ [ "ccp_normCounts_mESCquartz.counts.all_genes.tab.gz" ], { "name": "ccp_normCounts_mESCquartz.counts.all_genes.tab", "description": "The mouse embryonic stem cells (mESCs) were FACS sorted into G1, S and G2M phases. A total of 35 cells (seven S, eight G2M and 20 G1 cells) were sequenced using the Quartz-seq protocol and gene expression was normalised to FPKM values. The amount of technical noise expected for genes with variable levels of expression was estimated using a log-linear fit between the expression mean and the squared coefficient of variation between cells. The complete dataset contains expression of 36,807 genes.", "collection": "GEO", "version": "1.3", "year": 2013, "instances": 35, "missing": 0, "variables": 36808, "source": "NCBI", "url": "https://datasets.biolab.si/ccp_normCounts_mESCquartz.counts.all_genes.tab.gz", "domain": "sc", "language": "English", "target": "categorical", "location": "ccp_normCounts_mESCquartz.counts.all_genes.tab.gz", "size": 774815, "publication_status": 0, "tag": "mouse", "tags": [ "mouse", "expression", "mesc", "mus-musculus" ], "title": "Cell cycle in mESC (QuartzSeq)", "references": [ "Sasagawa, Y., Nikaido, I., ..., Ueda, H. R. (2013). Quartz-Seq: a highly reproducible and sensitive single-cell RNA sequencing method, reveals non-genetic gene-expression heterogeneity. Genome biology, 14(4), 3097.", "Scialdone, A., Natarajan, K. N., Saraiva, L. R., ... Buettner, F. (2015). Computational assignment of cell-cycle stage from single-cell transcriptome data. Methods, 85, 54-61." ], "taxid": 10090, "num_of_genes": 36807 } ], [ [ "ccp_normCounts_mESCquartz.counts.cycle_genes.tab.gz" ], { "name": "ccp_normCounts_mESCquartz.counts.cycle_genes.tab", "description": "The mESCs were FACS sorted into G1, S and G2M phases. A total of 35 cells (seven S, eight G2M and 20 G1 cells) were sequenced using the Quartz-seq protocol and gene expression was normalised to FPKM values. The amount of technical noise expected for genes with variable levels of expression was estimated using a log-linear fit between the expression mean and the squared coefficient of variation between cells. The reduced data set contains expression of 561 genes related to cell cycle based on Gene Ontology (GO) terms.", "collection": "GEO", "version": "1.3", "year": 2013, "instances": 35, "missing": 0, "variables": 562, "source": "NCBI", "url": "https://datasets.biolab.si/ccp_normCounts_mESCquartz.counts.cycle_genes.tab.gz", "domain": "sc", "language": "English", "target": "categorical", "location": "ccp_normCounts_mESCquartz.counts.cycle_genes.tab.gz", "size": 24516, "publication_status": 0, "tag": "mouse", "tags": [ "mouse", "expression", "mesc", "mus-musculus" ], "title": "Cell cycle in mESC (QuartzSeq, cell cycle genes)", "references": [ "Sasagawa, Y., Nikaido, I., ..., Ueda, H. R. (2013). Quartz-Seq: a highly reproducible and sensitive single-cell RNA sequencing method, reveals non-genetic gene-expression heterogeneity. Genome biology, 14(4), 3097.", "Scialdone, A., Natarajan, K. N., Saraiva, L. R., ... Buettner, F. (2015). Computational assignment of cell-cycle stage from single-cell transcriptome data. Methods, 85, 54-61." ], "taxid": 10090, "num_of_genes": 561 } ], [ [ "cdp_expression_macosko.tab.gz" ], { "name": "cdp_expression_macosko.tab", "description": "DropSeq analysis of more than 6,000 mouse retinal cells with expression levels of more than 6,800 genes expressed in at least 5% of the cells. The cells are labelled with corresponding bipolar cell (BC) cluster identified by the original study.", "collection": "GEO", "version": "2.3", "year": 2015, "instances": 6243, "missing": 1, "variables": 6862, "source": "NCBI", "url": "https://datasets.biolab.si/cdp_expression_macosko.tab.gz", "domain": "sc", "language": "English", "target": "categorical", "location": "cdp_expression_macosko.tab.gz", "size": 7786356, "publication_status": 0, "tag": "expression", "tags": [ "expression", "mouse", "mus-musculus", "neuron", "drop-seq" ], "title": "Mouse retinal bipolar neurons (DropSeq)", "references": [ "Macosko, E. Z., Basu, A., Satija, R., ... Trombetta, J. J. (2015). Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell, 161(5), 1202-1214." ], "taxid": 10090, "num_of_genes": 6860 } ], [ [ "cdp_expression_shekhar.tab.gz" ], { "name": "cdp_expression_shekhar.tab", "description": "The dataset contains a heterogeneous class of neurons, mouse retinal bipolar cells (BCs). Gene expression was measured with the DropSeq protocol. More than 4,900 genes expressed in at least 5% of the cells are included. The 12,606 cells are classified into 13 subtypes based on morphology and position.", "collection": "GEO", "version": "1.3", "year": 2016, "instances": 12606, "missing": 0, "variables": 4982, "source": "NCBI", "url": "https://datasets.biolab.si/cdp_expression_shekhar.tab.gz", "domain": "sc", "language": "English", "target": "categorical", "location": "cdp_expression_shekhar.tab.gz", "size": 11191059, "publication_status": 0, "tag": "expression", "tags": [ "expression", "mouse", "mus-musculus", "neuron", "drop-seq" ], "title": "Mouse retinal bipolar neurons (DropSeq, large)", "references": [ "Shekhar, K., Lapan, S. W., ... McCarroll, S. A. (2016). Comprehensive classification of retinal bipolar neurons by single-cell transcriptomics. Cell, 166(5), 1308-1323." ], "taxid": 10090, "num_of_genes": 4980 } ], [ [ "dm_proj_neurons_li2017.pkl.gz" ], { "name": "dm_proj_neurons_li2017.pkl", "description": "The data set contains 1842 projection neurons from Drosophila Melanogaster. The brains with mCD8GFP-labeled cells using specific GAL4 drivers were manually dissected, and two optical lobes were removed.", "collection": "EBI", "version": "1.0", "year": 2017, "instances": 1842, "missing": 0, "variables": 13920, "source": "EBI", "url": "https://datasets.biolab.si/dm_proj_neurons_li2017.pkl.gz", "domain": "sc", "language": "English", "target": "none", "location": "dm_proj_neurons_li2017.pkl.gz", "size": 24587348, "publication_status": 0, "tag": "drosophila-melanogaster", "tags": [ "drosophila-melanogaster", "expression", "differentiation" ], "title": "Drosophila Olfactory Projection Neuron Subtypes", "references": [ "Li, Hongjie, et al. Classifying Drosophila olfactory projection neuron subtypes by single-cell RNA sequencing. Cell 171.5 (2017): 1206-1220." ], "taxid": 7227, "num_of_genes": 13898 } ], [ [ "galen2019_AML_bone_marrow_day0.pkl.gz" ], { "name": "galen2019_AML_bone_marrow_day0.pkl", "description": "Bone marrow aspirate from AML patient before chemotherapy", "collection": "GEO", "version": "1.0", "year": 2018, "instances": 2328, "missing": 0, "variables": 27701, "source": "GEO", "url": "https://datasets.biolab.si/galen2019_AML_bone_marrow_day0.pkl.gz", "domain": "sc", "language": "English", "target": "none", "location": "galen2019_AML_bone_marrow_day0.pkl.gz", "size": 6275273, "publication_status": 0, "tag": "human", "tags": [ "human", "expression", "AML", "bone marrow" ], "title": "AML patient bone marrow day 0", "references": [ "van Galen, P., Hovestadt, V., Wadsworth II, M. H., Hughes, T. K., Griffin, G. K., Battaglia, S., ... & Pinkus, G. S. (2019). Single-Cell RNA-Seq Reveals AML Hierarchies Relevant to Disease Progression and Immunity. Cell, 176(6), 1265-1281." ], "taxid": 9606, "num_of_genes": 27899 } ], [ [ "galen2019_AML_bone_marrow_day15.pkl.gz" ], { "name": "galen2019_AML_bone_marrow_day15.pkl", "description": "Bone marrow aspirate from AML patient 15 days after first undergoing chemotherapy...", "collection": "GEO", "version": "1.2", "year": 2018, "instances": 1203, "missing": 0, "variables": 27701, "source": "GEO", "url": "https://datasets.biolab.si/galen2019_AML_bone_marrow_day15.pkl.gz", "domain": "sc", "language": "English", "target": "none", "location": "galen2019_AML_bone_marrow_day15.pkl.gz", "size": 3863633, "publication_status": 0, "tag": "human", "tags": [ "human", "expression", "AML", "bone marrow" ], "title": "AML patient bone marrow day 15", "references": [ "van Galen, P., Hovestadt, V., Wadsworth II, M. H., Hughes, T. K., Griffin, G. K., Battaglia, S., ... & Pinkus, G. S. (2019). Single-Cell RNA-Seq Reveals AML Hierarchies Relevant to Disease Progression and Immunity. Cell, 176(6), 1265-1281." ], "taxid": 9606, "num_of_genes": 27899 } ], [ [ "galen2019_AML_bone_marrow_day31.pkl.gz" ], { "name": "galen2019_AML_bone_marrow_day31.pkl", "description": "Bone marrow aspirate from AML patient 31 days after first undergoing chemotherapy", "collection": "GEO", "version": "1.2", "year": 2018, "instances": 1203, "missing": 0, "variables": 27701, "source": "GEO", "url": "https://datasets.biolab.si/galen2019_AML_bone_marrow_day31.pkl.gz", "domain": "sc", "language": "English", "target": "none", "location": "galen2019_AML_bone_marrow_day31.pkl.gz", "size": 3863633, "publication_status": 0, "tag": "AML", "tags": [ "AML", "bone marrow", "expression", "human" ], "title": "AML patient bone marrow day 31", "references": [ "van Galen, P., Hovestadt, V., Wadsworth II, M. H., Hughes, T. K., Griffin, G. K., Battaglia, S., ... & Pinkus, G. S. (2019). Single-Cell RNA-Seq Reveals AML Hierarchies Relevant to Disease Progression and Immunity. Cell, 176(6), 1265-1281." ], "taxid": 9606, "num_of_genes": 27899 } ], [ [ "galen2019_healthy_bone_marrow.pkl.gz" ], { "name": "galen2019_healthy_bone_marrow.pkl", "description": "Single cell profile of a bone marrow aspirate from a healthy donor containing 3739 cells", "collection": "GEO", "version": "1.0", "year": 2018, "instances": 3737, "missing": 0, "variables": 27701, "source": "GEO", "url": "https://datasets.biolab.si/galen2019_healthy_bone_marrow.pkl.gz", "domain": "sc", "language": "English", "target": "none", "location": "galen2019_healthy_bone_marrow.pkl.gz", "size": 10082836, "publication_status": 0, "tag": "human", "tags": [ "human", "expression", "bone marrow" ], "title": "Healthy human bone marrow", "references": [ "van Galen, P., Hovestadt, V., Wadsworth II, M. H., Hughes, T. K., Griffin, G. K., Battaglia, S., ... & Pinkus, G. S. (2019). Single-Cell RNA-Seq Reveals AML Hierarchies Relevant to Disease Progression and Immunity. Cell, 176(6), 1265-1281." ], "taxid": 9606, "num_of_genes": 27699 } ], [ [ "miller2019_chronically_infected_CD8.pkl.gz" ], { "name": "miller2019_chronically_infected_CD8.pkl", "description": "Expression profile obtained by high throughput sequencing of distinct populations of progenitor exhausted and terminally exhausted CD8+ T-cells that occur in chronic LCMV Clone 13 infection in mouse", "collection": "GEO", "version": "1.0", "year": 2018, "instances": 9197, "missing": 0, "variables": 22193, "source": "GEO", "url": "https://datasets.biolab.si/nestorawa_forcellcycle.pkl.gz", "domain": "sc", "language": "English", "target": "none", "location": "nestorawa_forcellcycle.pkl.gz", "size": 17564953, "publication_status": 0, "tag": "mus-musculus", "tags": [ "mus-musculus", "expression", "HPSC", "cell-cycle", "differentiation" ], "title": "Mouse haematopoietic stem and progenitor cell differentiation", "references": [ "Nestorowa, S., Hamey, F. K., Sala, B. P., Diamanti, E., Shepherd, M., Laurenti, E., ... & G\\u00f6ttgens, B. (2016). A single cell resolution map of mouse haematopoietic stem and progenitor cell differentiation. Blood, blood-2016." ], "taxid": 10090, "num_of_genes": 23929 } ], [ [ "pbmc_kang2018_raw_control.pkl.gz" ], { "name": "pbmc_kang2018_raw_control.pkl", "description": "Multiplexed dscRNA-seq was used to characterize the cell-type specificity and inter-individual variability of response to IFN-\u03b2, a potent cytokine that induces genome-scale changes in the transcriptional profiles of immune cells. From each of eight lupus patients, PBMCs were activated with recombinant IFN-\u03b2 or left untreated for 6 h, a time point previously found to maximize the expression of interferon-sensitive genes in dendritic cells and T cells16,17. Two pools, IFN-\u03b2-treated and control, were prepared with the same number of cells from each individual and loaded onto the 10\u00d7 Chromium instrument.", "collection": "GEO", "version": "2.0", "year": 2018, "instances": 13019, "missing": 0, "variables": 35637, "source": "GEO", "url": "https://datasets.biolab.si/pbmc_kang2018_raw_control.pkl.gz", "domain": "sc", "language": "English", "target": "categorical", "location": "pbmc_kang2018_raw_control.pkl.gz", "size": 19504172, "publication_status": 0, "tag": "human", "tags": [ "human", "expression", "pbmc", "immune-system" ], "title": "Stimulated and resting immune cells (control)", "references": [ "Kang, H. M., Subramaniam, M., Targ, S., Nguyen, M., Maliskova, L., McCarthy, E., ... & Gate, R. E. (2018). Multiplexed droplet single-cell RNA-sequencing using natural genetic variation. Nature biotechnology, 36(1), 89.", "Butler, A., Hoffman, P., Smibert, P., Papalexi, E., & Satija, R. (2018). Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nature biotechnology, 36(5), 411." ], "taxid": 9606, "num_of_genes": 35635 } ], [ [ "pbmc_kang2018_raw_stimulated.pkl.gz" ], { "name": "pbmc_kang2018_raw_stimulated.pkl", "description": "Multiplexed dscRNA-seq was used to characterize the cell-type specificity and inter-individual variability of response to IFN-\u03b2, a potent cytokine that induces genome-scale changes in the transcriptional profiles of immune cells. From each of eight lupus patients, PBMCs were activated with recombinant IFN-\u03b2 or left untreated for 6 h, a time point previously found to maximize the expression of interferon-sensitive genes in dendritic cells and T cells16,17. Two pools, IFN-\u03b2-treated and control, were prepared with the same number of cells from each individual and loaded onto the 10\u00d7 Chromium instrument.", "collection": "GEO", "version": "2.0", "year": 2018, "instances": 12875, "missing": 0, "variables": 35637, "source": "GEO", "url": "https://datasets.biolab.si/pbmc_kang2018_raw_stimulated.pkl.gz", "domain": "sc", "language": "English", "target": "categorical", "location": "pbmc_kang2018_raw_stimulated.pkl.gz", "size": 19932029, "publication_status": 0, "tag": "human", "tags": [ "human", "expression", "pbmc", "immune-system" ], "title": "Stimulated and resting immune cells (stimulated)", "references": [ "Kang, H. M., Subramaniam, M., Targ, S., Nguyen, M., Maliskova, L., McCarthy, E., ... & Gate, R. E. (2018). Multiplexed droplet single-cell RNA-sequencing using natural genetic variation. Nature biotechnology, 36(1), 89.", "Butler, A., Hoffman, P., Smibert, P., Papalexi, E., & Satija, R. (2018). Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nature biotechnology, 36(5), 411." ], "taxid": 9606, "num_of_genes": 35635 } ], [ [ "pbmc_kang2018_sample.tab.gz" ], { "name": "pbmc_kang2018_sample.tab", "description": "A preprocessed sample of Kang et al. (2018) data containing 1,000 controls and stimulated cells and 1,500 highly variable genes. Expression was CPM-normalized, log-transformed, and z-standardized. In the original study, the multiplexed dscRNA-seq was used to characterize the cell-type specificity and inter-individual variability of response to IFN-\u03b2, a potent cytokine that induces genome-scale changes in the transcriptional profiles of immune cells. From each of eight lupus patients, PBMCs were activated with recombinant IFN-\u03b2 or left untreated for 6 h, a time point previously found to maximize the expression of interferon-sensitive genes in dendritic cells and T cells16,17. Two pools, IFN-\u03b2-treated and control, were prepared with the same number of cells from each individual and loaded onto the 10\u00d7 Chromium instrument.", "collection": "GEO", "version": "1.0", "year": 2018, "instances": 1000, "missing": 0, "variables": 1502, "source": "GEO", "url": "https://datasets.biolab.si/pbmc_kang2018_sample.tab.gz", "domain": "sc", "language": "English", "target": "categorical", "location": "pbmc_kang2018_sample.tab.gz", "size": 4000592, "publication_status": 0, "tag": "human", "tags": [ "human", "expression", "pbmc", "immune-system" ], "title": "Stimulated and resting immune cells (1000 cells)", "references": [ "Kang, H. M., Subramaniam, M., Targ, S., Nguyen, M., Maliskova, L., McCarthy, E., ... & Gate, R. E. (2018). Multiplexed droplet single-cell RNA-sequencing using natural genetic variation. Nature biotechnology, 36(1), 89.", "Butler, A., Hoffman, P., Smibert, P., Papalexi, E., & Satija, R. (2018). Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nature biotechnology, 36(5), 411." ], "taxid": 9606, "num_of_genes": 1500 } ], [ [ "xin2016_pancreas_human.tab.gz" ], { "name": "xin2016_pancreas_human.tab", "description": "Data gathered using single-cell RNA sequencing to determine the transcriptomes of 1,492 human pancreatic \u03b1-, \u03b2-, \u03b4- and PP cells from non-diabetic and type 2 diabetes organ donors. 245 genes with disturbed expression in type 2 diabetes can be idenfitied from it.", "collection": "GEO", "version": "1.0", "year": 2016, "instances": 1492, "missing": 0, "variables": 35900, "source": "GEO", "url": "https://datasets.biolab.si/xin2016_pancreas_human.tab.gz", "domain": "sc", "language": "English", "target": "categorical", "location": "xin2016_pancreas_human.tab.gz", "size": 74519264, "publication_status": 0, "tag": "human", "tags": [ "human", "expression", "pancreas", "diabetes" ], "title": "Pancreas cells in human (type 2 diabetis)", "references": [ "Xin, Y, Kim, J., Okamoto, H., Ni, M., Wei, Y., Adler, C., J. Murphy, A., D. Yancopoulos, Lin, C., Gromada, J. (2016). RNA Sequencing of Single Human Islet Cells Reveals Type 2 Diabetes Genes. Cell Metabolism, 24 (4), 608-615." ], "taxid": 9606, "num_of_genes": 35899 } ], [ [ "xin2016_pancreas_human_sample.tab.gz" ], { "name": "xin2016_pancreas_human_sample.tab", "description": "A sample of 500 single cells gathered using single-cell RNA sequencing to determine the transcriptomes of human pancreatic \u03b1-, \u03b2-, \u03b4- and PP cells from non-diabetic and type 2 diabetes organ donors. 245 genes with disturbed expression in type 2 diabetes can be idenfitied from it.", "collection": "GEO", "version": "3.0", "year": 2016, "instances": 500, "missing": 0, "variables": 4648, "source": "GEO", "url": "https://datasets.biolab.si/xin2016_pancreas_human_sample.tab.gz", "domain": "sc", "language": "English", "target": "categorical", "location": "xin2016_pancreas_human_sample.tab.gz", "size": 6046346, "publication_status": 0, "tag": "human", "tags": [ "human", "expression", "pancreas", "diabetes" ], "title": "Pancreas cells in human (type 2 diabetes) (sample)", "references": [ "Xin, Y, Kim, J., Okamoto, H., Ni, M., Wei, Y., Adler, C., J. Murphy, A., D. Yancopoulos, Lin, C., Gromada, J. (2016). RNA Sequencing of Single Human Islet Cells Reveals Type 2 Diabetes Genes. Cell Metabolism, 24 (4), 608-615." ], "taxid": 9606, "num_of_genes": 4647 } ] ]