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single cell rna sequencing gene expression data  (Broad Clinical Labs)


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    Broad Clinical Labs single cell rna sequencing gene expression data
    Flowchart Overview of this MR-based study. LD linkage disequilibrium, ρ-HESS Heritability Estimation from Summary Statistics, GNOVA Genetic covariance analyser, MTAG Multi-Trait Analysis of GWAS, CPASSOC Cross Phenotype Association, GWAS Genome-wide Association Study, MR Mendelian Randomization, GSMR Generalized summary-data-based Mendelian randomization, LDSC-SEG linkage disequilibrium score regression applied to specifically expressed genes, MAGMA Multi-marker Analysis of GenoMic Annotation, SMR Summary-databased Mendelian randomization, Phe-MR phenotypes, MR BMI body mass index, LUSC squamous cell lung cancer; <t>scRNA-seq</t> <t>single-cell</t> <t>RNA</t> <t>sequencing</t>
    Single Cell Rna Sequencing Gene Expression Data, supplied by Broad Clinical Labs, used in various techniques. Bioz Stars score: 96/100, based on 779 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/cell+expression+data/RNA+Sequencing/pmc13096280-240-1-12
    Average 96 stars, based on 779 article reviews
    single cell rna sequencing gene expression data - by Bioz Stars, 2026-10
    96/100 stars

    Images

    1) Product Images from "Genetic evidence supporting obesity as a risk factor for lung squamous cell carcinoma and the identification of MFAP1 as a shared genetic target"

    Article Title: Genetic evidence supporting obesity as a risk factor for lung squamous cell carcinoma and the identification of MFAP1 as a shared genetic target

    Journal: Discover Oncology

    doi: 10.1007/s12672-026-04793-9

    Flowchart Overview of this MR-based study. LD linkage disequilibrium, ρ-HESS Heritability Estimation from Summary Statistics, GNOVA Genetic covariance analyser, MTAG Multi-Trait Analysis of GWAS, CPASSOC Cross Phenotype Association, GWAS Genome-wide Association Study, MR Mendelian Randomization, GSMR Generalized summary-data-based Mendelian randomization, LDSC-SEG linkage disequilibrium score regression applied to specifically expressed genes, MAGMA Multi-marker Analysis of GenoMic Annotation, SMR Summary-databased Mendelian randomization, Phe-MR phenotypes, MR BMI body mass index, LUSC squamous cell lung cancer; scRNA-seq single-cell RNA sequencing
    Figure Legend Snippet: Flowchart Overview of this MR-based study. LD linkage disequilibrium, ρ-HESS Heritability Estimation from Summary Statistics, GNOVA Genetic covariance analyser, MTAG Multi-Trait Analysis of GWAS, CPASSOC Cross Phenotype Association, GWAS Genome-wide Association Study, MR Mendelian Randomization, GSMR Generalized summary-data-based Mendelian randomization, LDSC-SEG linkage disequilibrium score regression applied to specifically expressed genes, MAGMA Multi-marker Analysis of GenoMic Annotation, SMR Summary-databased Mendelian randomization, Phe-MR phenotypes, MR BMI body mass index, LUSC squamous cell lung cancer; scRNA-seq single-cell RNA sequencing

    Techniques Used: GWAS, Marker, Single Cell, RNA Sequencing

    Tissue- and cell type–specific enrichment of SNP heritability for BMI and LUSC. A Tissue-level SNP heritability enrichment for BMI across 53 GTEx tissues estimated using LDSC-SEG. The x-axis shows tissues grouped by organ system, and the y-axis shows the estimated enrichment coefficient (log-scaled or standardized). Tissues surpassing the significance threshold (FDR-adjusted P < 0.05) are highlighted. B Tissue-level SNP heritability enrichment for LUSC using the same LDSC-SEG framework. The x-axis indicates GTEx tissues and the y-axis indicates enrichment coefficients, as in panel ( A ). Tissues with significant enrichment (FDR-adjusted P < 0.05) are labelled, illustrating the overlap and differences in tissue-specific genetic architecture between BMI and LUSC. C – G Cell type–specific SNP heritability enrichment for BMI and LUSC across single-cell RNA sequencing datasets from brain, ileum, heart, and colon, estimated using MAGMA-based cell typing. For each tissue, the left panel shows enrichment for BMI and the right panel shows enrichment for LUSC. The y-axis lists cell types (for example, neurons, epithelial cells, eosinophils, CD8⁺ T cells), and the x-axis shows –log₁₀(P) values for the association between cell type–specific expression and SNP heritability. Cell types with P < 0.05 are indicated in red, highlighting those most strongly enriched for the genetic signal of BMI and/or LUSC. BMI body mass index, LUSC lung squamous cell carcinoma, SNP single nucleotide polymorphism, LDSC-SEG linkage disequilibrium score regression applied to specifically expressed genes, MAGMA Multi-marker Analysis of GenoMic Annotation, scRNA-seq single-cell RNA sequencing, GTEx Genotype-Tissue Expression
    Figure Legend Snippet: Tissue- and cell type–specific enrichment of SNP heritability for BMI and LUSC. A Tissue-level SNP heritability enrichment for BMI across 53 GTEx tissues estimated using LDSC-SEG. The x-axis shows tissues grouped by organ system, and the y-axis shows the estimated enrichment coefficient (log-scaled or standardized). Tissues surpassing the significance threshold (FDR-adjusted P < 0.05) are highlighted. B Tissue-level SNP heritability enrichment for LUSC using the same LDSC-SEG framework. The x-axis indicates GTEx tissues and the y-axis indicates enrichment coefficients, as in panel ( A ). Tissues with significant enrichment (FDR-adjusted P < 0.05) are labelled, illustrating the overlap and differences in tissue-specific genetic architecture between BMI and LUSC. C – G Cell type–specific SNP heritability enrichment for BMI and LUSC across single-cell RNA sequencing datasets from brain, ileum, heart, and colon, estimated using MAGMA-based cell typing. For each tissue, the left panel shows enrichment for BMI and the right panel shows enrichment for LUSC. The y-axis lists cell types (for example, neurons, epithelial cells, eosinophils, CD8⁺ T cells), and the x-axis shows –log₁₀(P) values for the association between cell type–specific expression and SNP heritability. Cell types with P < 0.05 are indicated in red, highlighting those most strongly enriched for the genetic signal of BMI and/or LUSC. BMI body mass index, LUSC lung squamous cell carcinoma, SNP single nucleotide polymorphism, LDSC-SEG linkage disequilibrium score regression applied to specifically expressed genes, MAGMA Multi-marker Analysis of GenoMic Annotation, scRNA-seq single-cell RNA sequencing, GTEx Genotype-Tissue Expression

    Techniques Used: Single Cell, RNA Sequencing, Expressing, Marker

    Related Articles

    Expressing:

    Article Title: Cross-Cancer Characterization of CAMK2A Reveals Its Favorable Prognostic Association and Neuronal Signature Enrichment in Glioma
    Article Snippet: .. CAMK2A expression at the single-cell level was examined using a publicly available single-nucleus RNA-sequencing dataset from the Broad Institute Single Cell Portal (https://singlecell.broadinstitute.org/single_cell, accessed on 11 April 2026) [73]. ..

    Article Title: TIPE2 gene knockdown in mice attenuates experimental colitis by diminishing inflammatory cell infiltration
    Article Snippet: .. The single-cell expression profile of TIPE2 in both normal and inflamed intestinal tissues was interrogated via the Single Cell Portal ( https://singlecell.broadinstitute.org/single_cell ) using single cell RNA sequencing dataset SCP259. ..

    Single Cell:

    Article Title: Cross-Cancer Characterization of CAMK2A Reveals Its Favorable Prognostic Association and Neuronal Signature Enrichment in Glioma
    Article Snippet: .. CAMK2A expression at the single-cell level was examined using a publicly available single-nucleus RNA-sequencing dataset from the Broad Institute Single Cell Portal (https://singlecell.broadinstitute.org/single_cell, accessed on 11 April 2026) [73]. ..

    Article Title: A core transcriptional regulatory circuitry controls super-enhancer-driven activation of LGR5 in colorectal cancer.
    Article Snippet: .. B t-SNE visualization ofMYC and LGR5 in normal colon (red) and CRC (blue) cells.A,B The singlecell RNA sequencing results were obtained from the Human Colon Cancer Atlas in the Single Cell Portal (https://singlecell.broadinstitute.org/single_cell, GSE17834139).C Scatter plots showing the correlation of LGR5 level with the level of core circuitry factors (MYC, ETS2, FOXP1) in primary CRCs (n = 460; TCGA cohort). ..

    Article Title: GATA3 and YBX1 are associated with ER-specific metabolic programs and vulnerabilities in breast cancer
    Article Snippet: .. Single-cell RNA-sequencing data were obtained from the Single Cell Portal hosted by the Broad Institute (https://singlecell. ..

    Article Title: TIPE2 gene knockdown in mice attenuates experimental colitis by diminishing inflammatory cell infiltration
    Article Snippet: .. The single-cell expression profile of TIPE2 in both normal and inflamed intestinal tissues was interrogated via the Single Cell Portal ( https://singlecell.broadinstitute.org/single_cell ) using single cell RNA sequencing dataset SCP259. ..

    Article Title: Gpnmb defines a phagocytic state of microglia linked to cell death in prion disease mouse model.
    Article Snippet: .. The single-cell RNA-seq dataset reanalyzed in this study (26) is available from the Broad Institute Single Cell Portal under study SCP1962. ..

    Article Title: Effect of chemoradiation treatment on methylated BCAT1 and IKZF1 in rectal cancer.
    Article Snippet: Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia South Australian Immunogenomics Cancer Institute, The University of Adelaide, Adelaide, South Australia, Australia Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia Department of Medical Oncology, Flinders Medical Centre, Southern Adelaide Local Health Network, Adelaide, South Australia, Australia Department of Gastroenterology, Flinders Medical Centre, Southern Adelaide Local Health Network, Adelaide, South Australia, Australia

    RNA Sequencing:

    Article Title: A core transcriptional regulatory circuitry controls super-enhancer-driven activation of LGR5 in colorectal cancer.
    Article Snippet: .. B t-SNE visualization ofMYC and LGR5 in normal colon (red) and CRC (blue) cells.A,B The singlecell RNA sequencing results were obtained from the Human Colon Cancer Atlas in the Single Cell Portal (https://singlecell.broadinstitute.org/single_cell, GSE17834139).C Scatter plots showing the correlation of LGR5 level with the level of core circuitry factors (MYC, ETS2, FOXP1) in primary CRCs (n = 460; TCGA cohort). ..

    Article Title: IFN-γ signaling drives multiple immunosuppressive pathways and poor clinical outcome in glioblastoma
    Article Snippet: .. In silico data analysis RNA sequencing data from patients with GBM were obtained from The Cancer Genome Atlas (TCGA) Firehose Legacy dataset, published by the Broad Institute (54-57). ..

    Article Title: TIPE2 gene knockdown in mice attenuates experimental colitis by diminishing inflammatory cell infiltration
    Article Snippet: .. The single-cell expression profile of TIPE2 in both normal and inflamed intestinal tissues was interrogated via the Single Cell Portal ( https://singlecell.broadinstitute.org/single_cell ) using single cell RNA sequencing dataset SCP259. ..

    Article Title: Gpnmb defines a phagocytic state of microglia linked to cell death in prion disease mouse model.
    Article Snippet: .. The single-cell RNA-seq dataset reanalyzed in this study (26) is available from the Broad Institute Single Cell Portal under study SCP1962. ..

    In Silico:

    Article Title: IFN-γ signaling drives multiple immunosuppressive pathways and poor clinical outcome in glioblastoma
    Article Snippet: .. In silico data analysis RNA sequencing data from patients with GBM were obtained from The Cancer Genome Atlas (TCGA) Firehose Legacy dataset, published by the Broad Institute (54-57). ..

    Analysis:

    Article Title: IFN-γ signaling drives multiple immunosuppressive pathways and poor clinical outcome in glioblastoma
    Article Snippet: .. In silico data analysis RNA sequencing data from patients with GBM were obtained from The Cancer Genome Atlas (TCGA) Firehose Legacy dataset, published by the Broad Institute (54-57). ..

    other:

    Article Title: Multi-omic re-analysis increases diagnostic yield in individuals with Cornelia de Lange syndrome
    Article Snippet: RNA sequencing was performed at the BROAD institute at a minimum depth of 100M reads per sample and DRAGEN v3.9 RNA-seq workflow was used to align the raw reads to the human transcriptome and estimate the abundance of transcripts defined in GENCODE V39.

    Tissue:

    Article Title: Effect of chemoradiation treatment on methylated BCAT1 and IKZF1 in rectal cancer.
    Article Snippet: Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia South Australian Immunogenomics Cancer Institute, The University of Adelaide, Adelaide, South Australia, Australia Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia Department of Medical Oncology, Flinders Medical Centre, Southern Adelaide Local Health Network, Adelaide, South Australia, Australia Department of Gastroenterology, Flinders Medical Centre, Southern Adelaide Local Health Network, Adelaide, South Australia, Australia

    Gene Expression:

    Article Title: Effect of chemoradiation treatment on methylated BCAT1 and IKZF1 in rectal cancer.
    Article Snippet: Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia South Australian Immunogenomics Cancer Institute, The University of Adelaide, Adelaide, South Australia, Australia Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia Department of Medical Oncology, Flinders Medical Centre, Southern Adelaide Local Health Network, Adelaide, South Australia, Australia Department of Gastroenterology, Flinders Medical Centre, Southern Adelaide Local Health Network, Adelaide, South Australia, Australia



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    Image Search Results


    Flowchart Overview of this MR-based study. LD linkage disequilibrium, ρ-HESS Heritability Estimation from Summary Statistics, GNOVA Genetic covariance analyser, MTAG Multi-Trait Analysis of GWAS, CPASSOC Cross Phenotype Association, GWAS Genome-wide Association Study, MR Mendelian Randomization, GSMR Generalized summary-data-based Mendelian randomization, LDSC-SEG linkage disequilibrium score regression applied to specifically expressed genes, MAGMA Multi-marker Analysis of GenoMic Annotation, SMR Summary-databased Mendelian randomization, Phe-MR phenotypes, MR BMI body mass index, LUSC squamous cell lung cancer; scRNA-seq single-cell RNA sequencing

    Journal: Discover Oncology

    Article Title: Genetic evidence supporting obesity as a risk factor for lung squamous cell carcinoma and the identification of MFAP1 as a shared genetic target

    doi: 10.1007/s12672-026-04793-9

    Figure Lengend Snippet: Flowchart Overview of this MR-based study. LD linkage disequilibrium, ρ-HESS Heritability Estimation from Summary Statistics, GNOVA Genetic covariance analyser, MTAG Multi-Trait Analysis of GWAS, CPASSOC Cross Phenotype Association, GWAS Genome-wide Association Study, MR Mendelian Randomization, GSMR Generalized summary-data-based Mendelian randomization, LDSC-SEG linkage disequilibrium score regression applied to specifically expressed genes, MAGMA Multi-marker Analysis of GenoMic Annotation, SMR Summary-databased Mendelian randomization, Phe-MR phenotypes, MR BMI body mass index, LUSC squamous cell lung cancer; scRNA-seq single-cell RNA sequencing

    Article Snippet: The Single-cell RNA sequencing gene expression data were available from https://www.ncbi.nlm.nih.gov/geo/ and [https://singlecell.broadinstitute.org/single_cell](https:/www.singlecell.broadinstitute.org/single_cell) .

    Techniques: GWAS, Marker, Single Cell, RNA Sequencing

    Tissue- and cell type–specific enrichment of SNP heritability for BMI and LUSC. A Tissue-level SNP heritability enrichment for BMI across 53 GTEx tissues estimated using LDSC-SEG. The x-axis shows tissues grouped by organ system, and the y-axis shows the estimated enrichment coefficient (log-scaled or standardized). Tissues surpassing the significance threshold (FDR-adjusted P < 0.05) are highlighted. B Tissue-level SNP heritability enrichment for LUSC using the same LDSC-SEG framework. The x-axis indicates GTEx tissues and the y-axis indicates enrichment coefficients, as in panel ( A ). Tissues with significant enrichment (FDR-adjusted P < 0.05) are labelled, illustrating the overlap and differences in tissue-specific genetic architecture between BMI and LUSC. C – G Cell type–specific SNP heritability enrichment for BMI and LUSC across single-cell RNA sequencing datasets from brain, ileum, heart, and colon, estimated using MAGMA-based cell typing. For each tissue, the left panel shows enrichment for BMI and the right panel shows enrichment for LUSC. The y-axis lists cell types (for example, neurons, epithelial cells, eosinophils, CD8⁺ T cells), and the x-axis shows –log₁₀(P) values for the association between cell type–specific expression and SNP heritability. Cell types with P < 0.05 are indicated in red, highlighting those most strongly enriched for the genetic signal of BMI and/or LUSC. BMI body mass index, LUSC lung squamous cell carcinoma, SNP single nucleotide polymorphism, LDSC-SEG linkage disequilibrium score regression applied to specifically expressed genes, MAGMA Multi-marker Analysis of GenoMic Annotation, scRNA-seq single-cell RNA sequencing, GTEx Genotype-Tissue Expression

    Journal: Discover Oncology

    Article Title: Genetic evidence supporting obesity as a risk factor for lung squamous cell carcinoma and the identification of MFAP1 as a shared genetic target

    doi: 10.1007/s12672-026-04793-9

    Figure Lengend Snippet: Tissue- and cell type–specific enrichment of SNP heritability for BMI and LUSC. A Tissue-level SNP heritability enrichment for BMI across 53 GTEx tissues estimated using LDSC-SEG. The x-axis shows tissues grouped by organ system, and the y-axis shows the estimated enrichment coefficient (log-scaled or standardized). Tissues surpassing the significance threshold (FDR-adjusted P < 0.05) are highlighted. B Tissue-level SNP heritability enrichment for LUSC using the same LDSC-SEG framework. The x-axis indicates GTEx tissues and the y-axis indicates enrichment coefficients, as in panel ( A ). Tissues with significant enrichment (FDR-adjusted P < 0.05) are labelled, illustrating the overlap and differences in tissue-specific genetic architecture between BMI and LUSC. C – G Cell type–specific SNP heritability enrichment for BMI and LUSC across single-cell RNA sequencing datasets from brain, ileum, heart, and colon, estimated using MAGMA-based cell typing. For each tissue, the left panel shows enrichment for BMI and the right panel shows enrichment for LUSC. The y-axis lists cell types (for example, neurons, epithelial cells, eosinophils, CD8⁺ T cells), and the x-axis shows –log₁₀(P) values for the association between cell type–specific expression and SNP heritability. Cell types with P < 0.05 are indicated in red, highlighting those most strongly enriched for the genetic signal of BMI and/or LUSC. BMI body mass index, LUSC lung squamous cell carcinoma, SNP single nucleotide polymorphism, LDSC-SEG linkage disequilibrium score regression applied to specifically expressed genes, MAGMA Multi-marker Analysis of GenoMic Annotation, scRNA-seq single-cell RNA sequencing, GTEx Genotype-Tissue Expression

    Article Snippet: The Single-cell RNA sequencing gene expression data were available from https://www.ncbi.nlm.nih.gov/geo/ and [https://singlecell.broadinstitute.org/single_cell](https:/www.singlecell.broadinstitute.org/single_cell) .

    Techniques: Single Cell, RNA Sequencing, Expressing, Marker

    a Gene expression levels (Transcripts Per Million, TPM) of major autoantibody targets identified in paraneoplastic pemphigus, showing a marked enrichment in the skin and other squamous epithelia (data from the GTEx database, v6p.v1.1.8). Each bar comprises stacked boxes, with the width of each box representing the interquartile range of gene expression in the corresponding tissue. b – d Heatmaps showing normalized single-cell transcript expression levels (nTPM), summarized per gene and cell type cluster for selected tissues, highlighting SERPINB3 expression in bronchiolar cells. Single-cell expression data were obtained from the Human Protein Atlas.

    Journal: Communications Medicine

    Article Title: Autoantibody repertoire analysis in paraneoplastic pemphigus reveals novel targets linked to mucocutaneous blistering and bronchiolitis obliterans

    doi: 10.1038/s43856-025-01335-2

    Figure Lengend Snippet: a Gene expression levels (Transcripts Per Million, TPM) of major autoantibody targets identified in paraneoplastic pemphigus, showing a marked enrichment in the skin and other squamous epithelia (data from the GTEx database, v6p.v1.1.8). Each bar comprises stacked boxes, with the width of each box representing the interquartile range of gene expression in the corresponding tissue. b – d Heatmaps showing normalized single-cell transcript expression levels (nTPM), summarized per gene and cell type cluster for selected tissues, highlighting SERPINB3 expression in bronchiolar cells. Single-cell expression data were obtained from the Human Protein Atlas.

    Article Snippet: Single-cell expression data were obtained from the Human Protein Atlas.

    Techniques: Gene Expression, Expressing