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


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    Structured Review

    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 776 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/single+cell+expression+data/RNA+Sequencing/pmc13096280-240-1-12
    Average 96 stars, based on 776 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: 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: Macrophage NEDD4L restrains liver fibrosis by preventing scar-associated macrophage expansion via ubiquitination of phospho-SMAD3.
    Article Snippet: .. Macrophage NEDD4L is elevated during liver fibrosis development To understand the role of NEDD4L in liver fibrosis, we first analyzed public single-cell RNA sequencing (scRNA-seq) database (https://singlecell. broadinstitute.org). ..

    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

    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). ..

    RNA Sequencing:

    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: A severe neurodevelopmental syndrome linked to a South Asian founder variant in the UFMylation adaptor CDK5RAP3
    Article Snippet: .. Trio exome and genome sequencing (AI-1, AI-2, AII-1), and singleton skeletal muscle RNA sequencing (RNA-seq; AII-1), were performed by the Broad Institute (MIT and Harvard University, USA) as described [ ]. ..

    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: Macrophage NEDD4L restrains liver fibrosis by preventing scar-associated macrophage expansion via ubiquitination of phospho-SMAD3.
    Article Snippet: .. Macrophage NEDD4L is elevated during liver fibrosis development To understand the role of NEDD4L in liver fibrosis, we first analyzed public single-cell RNA sequencing (scRNA-seq) database (https://singlecell. broadinstitute.org). ..

    RNA sequencing:

    Article Title: PRECISE: A prognostic thyrocyte-derived gene signature for papillary thyroid carcinoma
    Article Snippet: 48 Purpose: Papillary thyroid carcinoma (PTC) exhibits heterogeneous behavior, underscoring the 49 need for effective biomarkers and improved risk stratification methods.. We developed a 50 thyrocyte–derived gene signature, Prognostic RNA Expression Cell-specific Integrated SignaturE 51 (PRECISE), using single-cell and single-nucleus RNA sequencing (RNAseq) and evaluated its 52 prognostic utility across cohorts.. 53 Patients and Methods: PRECISE was developed using a discovery cohort of PTC patients 54 (MDACC n=109, median follow-up=14 years).

    Generated:

    Article Title: PRECISE: A prognostic thyrocyte-derived gene signature for papillary thyroid carcinoma
    Article Snippet: 48 Purpose: Papillary thyroid carcinoma (PTC) exhibits heterogeneous behavior, underscoring the 49 need for effective biomarkers and improved risk stratification methods.. We developed a 50 thyrocyte–derived gene signature, Prognostic RNA Expression Cell-specific Integrated SignaturE 51 (PRECISE), using single-cell and single-nucleus RNA sequencing (RNAseq) and evaluated its 52 prognostic utility across cohorts.. 53 Patients and Methods: PRECISE was developed using a discovery cohort of PTC patients 54 (MDACC n=109, median follow-up=14 years).

    Sequencing:

    Article Title: A severe neurodevelopmental syndrome linked to a South Asian founder variant in the UFMylation adaptor CDK5RAP3
    Article Snippet: .. Trio exome and genome sequencing (AI-1, AI-2, AII-1), and singleton skeletal muscle RNA sequencing (RNA-seq; AII-1), were performed by the Broad Institute (MIT and Harvard University, USA) as described [ ]. ..

    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