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single cell rna expression data  (Human Protein Atlas)

 
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    Human Protein Atlas single cell rna expression data
    Single Cell Rna Expression Data, supplied by Human Protein Atlas, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/cell+rna+expression+data/pmc12882627-172-8-15?v=Human+Protein+Atlas
    Average 86 stars, based on 1 article reviews
    single cell rna expression data - by Bioz Stars, 2026-06
    86/100 stars

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    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