singlecell rna-seq (scrna-seq) platform Search Results


single cell rna sequencing scrna seq data  (Broad Clinical Labs)
96
Broad Clinical Labs single cell rna sequencing scrna seq data
<t>Single-Cell</t> <t>Analysis</t> of GBP2 and EIF2AK2 Expression Dynamics in Lupus Nephritis. a t-SNE plot of single-cell <t>sequencing</t> data from kidney tissues. b-c Expression patterns of GBP2 and EIF2AK2 in different cell types between the control group and LN patients. d-f Expression patterns of GBP2 in the different LN ISN/RPS pathological classifications, Interstitial Inflammation, and Tubular Interstitial Fibrosis. g-i Expression patterns of EIF2AK2 in the different LN ISN/RPS pathological classifications, Interstitial Inflammation, and Tubular Interstitial Fibrosis. j t-SNE plot of single-cell sequencing data from kidney immune cells. k-l Expression patterns of GBP2 and EIF2AK2 in different immune cell types between the control group and LN patients. CE0: Epithelial cells, CD0: Dividing cells, CM0: Inflammatory CD16 + macrophages, CM2: Tissue-resident macrophages, CM3: Conventional dendritic cells, CT5b: CD56bright CD16 − NK cells, CT0a: Effector memory CD4 + T cells, CT3b: TFH-like cells, CT0b: Central memory CD4 + T cells, CT5a: Resident memory CD8 + T cells, CB2a: Naïve B cells, CT4: GZMK + CD8 + T cells, CT1: CD56dim CD16 + NK cells, CT3a: Treg cells, CT2: Cytotoxic T Lymphocytes, CM1: Phagocytic CD16 + macrophages, CB0: Activated B cells, CB2b: Plasmacytoid dendritic cells, CM4: M2-like CD16 + macrophages, CB1: Plasma cells and plasmablasts, CT6: ISG-high CD4 + T cells, CB3: ISG-high B cells
Single Cell Rna Sequencing Scrna Seq Data, supplied by Broad Clinical Labs, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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singlecell rna sequencing scrna seq analysis  (Institut Curie)
86
Institut Curie singlecell rna sequencing scrna seq analysis
<t>Single-Cell</t> <t>Analysis</t> of GBP2 and EIF2AK2 Expression Dynamics in Lupus Nephritis. a t-SNE plot of single-cell <t>sequencing</t> data from kidney tissues. b-c Expression patterns of GBP2 and EIF2AK2 in different cell types between the control group and LN patients. d-f Expression patterns of GBP2 in the different LN ISN/RPS pathological classifications, Interstitial Inflammation, and Tubular Interstitial Fibrosis. g-i Expression patterns of EIF2AK2 in the different LN ISN/RPS pathological classifications, Interstitial Inflammation, and Tubular Interstitial Fibrosis. j t-SNE plot of single-cell sequencing data from kidney immune cells. k-l Expression patterns of GBP2 and EIF2AK2 in different immune cell types between the control group and LN patients. CE0: Epithelial cells, CD0: Dividing cells, CM0: Inflammatory CD16 + macrophages, CM2: Tissue-resident macrophages, CM3: Conventional dendritic cells, CT5b: CD56bright CD16 − NK cells, CT0a: Effector memory CD4 + T cells, CT3b: TFH-like cells, CT0b: Central memory CD4 + T cells, CT5a: Resident memory CD8 + T cells, CB2a: Naïve B cells, CT4: GZMK + CD8 + T cells, CT1: CD56dim CD16 + NK cells, CT3a: Treg cells, CT2: Cytotoxic T Lymphocytes, CM1: Phagocytic CD16 + macrophages, CB0: Activated B cells, CB2b: Plasmacytoid dendritic cells, CM4: M2-like CD16 + macrophages, CB1: Plasma cells and plasmablasts, CT6: ISG-high CD4 + T cells, CB3: ISG-high B cells
Singlecell Rna Sequencing Scrna Seq Analysis, supplied by Institut Curie, 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/singlecell+rna-seq+(scrna-seq)+platform/bulk+data+rna+seq/pm42120423-51-19-15
Average 86 stars, based on 1 article reviews
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singlecell rna sequencing scrna seq  (10X Genomics)
86
10X Genomics singlecell rna sequencing scrna seq
A–C) Split violin plots display the distribution of key <t>sequencing</t> and cell quality metrics, with red representing snRNA-seq and blue representing scRNA-seq. Each pair of samples is connected by a line. Samples are coloured by the laboratory to indicate batch origin (A, B, C, F, H, I, L). Median number of genes detected per cell for each sample (A), Library size per sample after removing MT genes (B) and Sequencing saturation (C). D–E) Scatter plots showing an example of the correlation between library size and number of genes per cell in scRNA-seq (D) and snRNA-seq (E), coloured by cell type. Scatter plots for all samples are shown in Figure S7. F) Split violin plots showing proportion of reads mapped to intronic regions per sample. G) Distribution of total UMI counts per gene length bin across 50 gene length bins across all 22 samples. H–I) Split violin plots comparing the percentage of MT gene content (H) and ambient <t>RNA</t> (I). J) Correlation between the percentage of detected doublets and the total number of cells recovered per sample. K) Boxplots showing Jaccard scores representing similarity of HVGs identified within each method, based on the variance-stabilising transformation method. L) Comparison of the average number of clusters detected in three comparable resolutions in each sample.
Singlecell Rna Sequencing Scrna Seq, supplied by 10X Genomics, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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scrna-seq data in gbm  (Broad Institute Inc)
90
Broad Institute Inc scrna-seq data in gbm
A–C) Split violin plots display the distribution of key <t>sequencing</t> and cell quality metrics, with red representing snRNA-seq and blue representing scRNA-seq. Each pair of samples is connected by a line. Samples are coloured by the laboratory to indicate batch origin (A, B, C, F, H, I, L). Median number of genes detected per cell for each sample (A), Library size per sample after removing MT genes (B) and Sequencing saturation (C). D–E) Scatter plots showing an example of the correlation between library size and number of genes per cell in scRNA-seq (D) and snRNA-seq (E), coloured by cell type. Scatter plots for all samples are shown in Figure S7. F) Split violin plots showing proportion of reads mapped to intronic regions per sample. G) Distribution of total UMI counts per gene length bin across 50 gene length bins across all 22 samples. H–I) Split violin plots comparing the percentage of MT gene content (H) and ambient <t>RNA</t> (I). J) Correlation between the percentage of detected doublets and the total number of cells recovered per sample. K) Boxplots showing Jaccard scores representing similarity of HVGs identified within each method, based on the variance-stabilising transformation method. L) Comparison of the average number of clusters detected in three comparable resolutions in each sample.
Scrna Seq Data In Gbm, supplied by Broad Institute Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Average 90 stars, based on 1 article reviews
scrna-seq data in gbm - by Bioz Stars, 2026-10
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scrna-seq data  (Broad Institute Inc)
90
Broad Institute Inc scrna-seq data
A–C) Split violin plots display the distribution of key <t>sequencing</t> and cell quality metrics, with red representing snRNA-seq and blue representing scRNA-seq. Each pair of samples is connected by a line. Samples are coloured by the laboratory to indicate batch origin (A, B, C, F, H, I, L). Median number of genes detected per cell for each sample (A), Library size per sample after removing MT genes (B) and Sequencing saturation (C). D–E) Scatter plots showing an example of the correlation between library size and number of genes per cell in scRNA-seq (D) and snRNA-seq (E), coloured by cell type. Scatter plots for all samples are shown in Figure S7. F) Split violin plots showing proportion of reads mapped to intronic regions per sample. G) Distribution of total UMI counts per gene length bin across 50 gene length bins across all 22 samples. H–I) Split violin plots comparing the percentage of MT gene content (H) and ambient <t>RNA</t> (I). J) Correlation between the percentage of detected doublets and the total number of cells recovered per sample. K) Boxplots showing Jaccard scores representing similarity of HVGs identified within each method, based on the variance-stabilising transformation method. L) Comparison of the average number of clusters detected in three comparable resolutions in each sample.
Scrna Seq Data, supplied by Broad Institute Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/singlecell+rna-seq+(scrna-seq)+platform/scrna+seq+data/10__1158_slash_0008___5472__can___21___4141-109-3-15
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scrna seq  (10X Genomics)
86
10X Genomics scrna seq
A–C) Split violin plots display the distribution of key <t>sequencing</t> and cell quality metrics, with red representing snRNA-seq and blue representing scRNA-seq. Each pair of samples is connected by a line. Samples are coloured by the laboratory to indicate batch origin (A, B, C, F, H, I, L). Median number of genes detected per cell for each sample (A), Library size per sample after removing MT genes (B) and Sequencing saturation (C). D–E) Scatter plots showing an example of the correlation between library size and number of genes per cell in scRNA-seq (D) and snRNA-seq (E), coloured by cell type. Scatter plots for all samples are shown in Figure S7. F) Split violin plots showing proportion of reads mapped to intronic regions per sample. G) Distribution of total UMI counts per gene length bin across 50 gene length bins across all 22 samples. H–I) Split violin plots comparing the percentage of MT gene content (H) and ambient <t>RNA</t> (I). J) Correlation between the percentage of detected doublets and the total number of cells recovered per sample. K) Boxplots showing Jaccard scores representing similarity of HVGs identified within each method, based on the variance-stabilising transformation method. L) Comparison of the average number of clusters detected in three comparable resolutions in each sample.
Scrna Seq, supplied by 10X Genomics, 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/singlecell+rna-seq+(scrna-seq)+platform/scrna+seq/arxiv__2506__22228-66-8-9
Average 86 stars, based on 1 article reviews
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droplet  (10X Genomics)
86
10X Genomics droplet
A–C) Split violin plots display the distribution of key <t>sequencing</t> and cell quality metrics, with red representing snRNA-seq and blue representing scRNA-seq. Each pair of samples is connected by a line. Samples are coloured by the laboratory to indicate batch origin (A, B, C, F, H, I, L). Median number of genes detected per cell for each sample (A), Library size per sample after removing MT genes (B) and Sequencing saturation (C). D–E) Scatter plots showing an example of the correlation between library size and number of genes per cell in scRNA-seq (D) and snRNA-seq (E), coloured by cell type. Scatter plots for all samples are shown in Figure S7. F) Split violin plots showing proportion of reads mapped to intronic regions per sample. G) Distribution of total UMI counts per gene length bin across 50 gene length bins across all 22 samples. H–I) Split violin plots comparing the percentage of MT gene content (H) and ambient <t>RNA</t> (I). J) Correlation between the percentage of detected doublets and the total number of cells recovered per sample. K) Boxplots showing Jaccard scores representing similarity of HVGs identified within each method, based on the variance-stabilising transformation method. L) Comparison of the average number of clusters detected in three comparable resolutions in each sample.
Droplet, supplied by 10X Genomics, 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/singlecell+rna-seq+(scrna-seq)+platform/based+droplet/pm38563819-121-21-25
Average 86 stars, based on 1 article reviews
droplet - by Bioz Stars, 2026-10
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single cell portal  (Broad Clinical Labs)
96
Broad Clinical Labs single cell portal
A–C) Split violin plots display the distribution of key <t>sequencing</t> and cell quality metrics, with red representing snRNA-seq and blue representing scRNA-seq. Each pair of samples is connected by a line. Samples are coloured by the laboratory to indicate batch origin (A, B, C, F, H, I, L). Median number of genes detected per cell for each sample (A), Library size per sample after removing MT genes (B) and Sequencing saturation (C). D–E) Scatter plots showing an example of the correlation between library size and number of genes per cell in scRNA-seq (D) and snRNA-seq (E), coloured by cell type. Scatter plots for all samples are shown in Figure S7. F) Split violin plots showing proportion of reads mapped to intronic regions per sample. G) Distribution of total UMI counts per gene length bin across 50 gene length bins across all 22 samples. H–I) Split violin plots comparing the percentage of MT gene content (H) and ambient <t>RNA</t> (I). J) Correlation between the percentage of detected doublets and the total number of cells recovered per sample. K) Boxplots showing Jaccard scores representing similarity of HVGs identified within each method, based on the variance-stabilising transformation method. L) Comparison of the average number of clusters detected in three comparable resolutions in each sample.
Single Cell Portal, supplied by Broad Clinical Labs, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/singlecell+rna-seq+(scrna-seq)+platform/Single+Cell+Sequencing/pm38758649-300-6-11
Average 96 stars, based on 1 article reviews
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smart-seq2 scrna-seq dataset  (Broad Institute Inc)
90
Broad Institute Inc smart-seq2 scrna-seq dataset
A–C) Split violin plots display the distribution of key <t>sequencing</t> and cell quality metrics, with red representing snRNA-seq and blue representing scRNA-seq. Each pair of samples is connected by a line. Samples are coloured by the laboratory to indicate batch origin (A, B, C, F, H, I, L). Median number of genes detected per cell for each sample (A), Library size per sample after removing MT genes (B) and Sequencing saturation (C). D–E) Scatter plots showing an example of the correlation between library size and number of genes per cell in scRNA-seq (D) and snRNA-seq (E), coloured by cell type. Scatter plots for all samples are shown in Figure S7. F) Split violin plots showing proportion of reads mapped to intronic regions per sample. G) Distribution of total UMI counts per gene length bin across 50 gene length bins across all 22 samples. H–I) Split violin plots comparing the percentage of MT gene content (H) and ambient <t>RNA</t> (I). J) Correlation between the percentage of detected doublets and the total number of cells recovered per sample. K) Boxplots showing Jaccard scores representing similarity of HVGs identified within each method, based on the variance-stabilising transformation method. L) Comparison of the average number of clusters detected in three comparable resolutions in each sample.
Smart Seq2 Scrna Seq Dataset, supplied by Broad Institute Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/singlecell+rna-seq+(scrna-seq)+platform/smart+seq2+rna+seq/pmc10795478-575-2-36
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porter database  (Broad Institute Inc)
90
Broad Institute Inc porter database
A–C) Split violin plots display the distribution of key <t>sequencing</t> and cell quality metrics, with red representing snRNA-seq and blue representing scRNA-seq. Each pair of samples is connected by a line. Samples are coloured by the laboratory to indicate batch origin (A, B, C, F, H, I, L). Median number of genes detected per cell for each sample (A), Library size per sample after removing MT genes (B) and Sequencing saturation (C). D–E) Scatter plots showing an example of the correlation between library size and number of genes per cell in scRNA-seq (D) and snRNA-seq (E), coloured by cell type. Scatter plots for all samples are shown in Figure S7. F) Split violin plots showing proportion of reads mapped to intronic regions per sample. G) Distribution of total UMI counts per gene length bin across 50 gene length bins across all 22 samples. H–I) Split violin plots comparing the percentage of MT gene content (H) and ambient <t>RNA</t> (I). J) Correlation between the percentage of detected doublets and the total number of cells recovered per sample. K) Boxplots showing Jaccard scores representing similarity of HVGs identified within each method, based on the variance-stabilising transformation method. L) Comparison of the average number of clusters detected in three comparable resolutions in each sample.
Porter Database, supplied by Broad Institute Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/singlecell+rna-seq+(scrna-seq)+platform/porter+database/pmc09909353-258-0-9
Average 90 stars, based on 1 article reviews
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single cell rna-seq (scrna-seq) porter database  (Broad Institute Inc)
90
Broad Institute Inc single cell rna-seq (scrna-seq) porter database
A–C) Split violin plots display the distribution of key <t>sequencing</t> and cell quality metrics, with red representing snRNA-seq and blue representing scRNA-seq. Each pair of samples is connected by a line. Samples are coloured by the laboratory to indicate batch origin (A, B, C, F, H, I, L). Median number of genes detected per cell for each sample (A), Library size per sample after removing MT genes (B) and Sequencing saturation (C). D–E) Scatter plots showing an example of the correlation between library size and number of genes per cell in scRNA-seq (D) and snRNA-seq (E), coloured by cell type. Scatter plots for all samples are shown in Figure S7. F) Split violin plots showing proportion of reads mapped to intronic regions per sample. G) Distribution of total UMI counts per gene length bin across 50 gene length bins across all 22 samples. H–I) Split violin plots comparing the percentage of MT gene content (H) and ambient <t>RNA</t> (I). J) Correlation between the percentage of detected doublets and the total number of cells recovered per sample. K) Boxplots showing Jaccard scores representing similarity of HVGs identified within each method, based on the variance-stabilising transformation method. L) Comparison of the average number of clusters detected in three comparable resolutions in each sample.
Single Cell Rna Seq (Scrna Seq) Porter Database, supplied by Broad Institute Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/singlecell+rna-seq+(scrna-seq)+platform/single+cell+rna+seq+data/pm36776889-339-0-9
Average 90 stars, based on 1 article reviews
single cell rna-seq (scrna-seq) porter database - by Bioz Stars, 2026-10
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gel bead kit v3 1  (10X Genomics)
86
10X Genomics gel bead kit v3 1
A–C) Split violin plots display the distribution of key <t>sequencing</t> and cell quality metrics, with red representing snRNA-seq and blue representing scRNA-seq. Each pair of samples is connected by a line. Samples are coloured by the laboratory to indicate batch origin (A, B, C, F, H, I, L). Median number of genes detected per cell for each sample (A), Library size per sample after removing MT genes (B) and Sequencing saturation (C). D–E) Scatter plots showing an example of the correlation between library size and number of genes per cell in scRNA-seq (D) and snRNA-seq (E), coloured by cell type. Scatter plots for all samples are shown in Figure S7. F) Split violin plots showing proportion of reads mapped to intronic regions per sample. G) Distribution of total UMI counts per gene length bin across 50 gene length bins across all 22 samples. H–I) Split violin plots comparing the percentage of MT gene content (H) and ambient <t>RNA</t> (I). J) Correlation between the percentage of detected doublets and the total number of cells recovered per sample. K) Boxplots showing Jaccard scores representing similarity of HVGs identified within each method, based on the variance-stabilising transformation method. L) Comparison of the average number of clusters detected in three comparable resolutions in each sample.
Gel Bead Kit V3 1, supplied by 10X Genomics, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


Single-Cell Analysis of GBP2 and EIF2AK2 Expression Dynamics in Lupus Nephritis. a t-SNE plot of single-cell sequencing data from kidney tissues. b-c Expression patterns of GBP2 and EIF2AK2 in different cell types between the control group and LN patients. d-f Expression patterns of GBP2 in the different LN ISN/RPS pathological classifications, Interstitial Inflammation, and Tubular Interstitial Fibrosis. g-i Expression patterns of EIF2AK2 in the different LN ISN/RPS pathological classifications, Interstitial Inflammation, and Tubular Interstitial Fibrosis. j t-SNE plot of single-cell sequencing data from kidney immune cells. k-l Expression patterns of GBP2 and EIF2AK2 in different immune cell types between the control group and LN patients. CE0: Epithelial cells, CD0: Dividing cells, CM0: Inflammatory CD16 + macrophages, CM2: Tissue-resident macrophages, CM3: Conventional dendritic cells, CT5b: CD56bright CD16 − NK cells, CT0a: Effector memory CD4 + T cells, CT3b: TFH-like cells, CT0b: Central memory CD4 + T cells, CT5a: Resident memory CD8 + T cells, CB2a: Naïve B cells, CT4: GZMK + CD8 + T cells, CT1: CD56dim CD16 + NK cells, CT3a: Treg cells, CT2: Cytotoxic T Lymphocytes, CM1: Phagocytic CD16 + macrophages, CB0: Activated B cells, CB2b: Plasmacytoid dendritic cells, CM4: M2-like CD16 + macrophages, CB1: Plasma cells and plasmablasts, CT6: ISG-high CD4 + T cells, CB3: ISG-high B cells

Journal: Inflammation

Article Title: Identifying Crucial Genes Associated with Pyroptosis in Lupus Nephritis

doi: 10.1007/s10753-025-02402-5

Figure Lengend Snippet: Single-Cell Analysis of GBP2 and EIF2AK2 Expression Dynamics in Lupus Nephritis. a t-SNE plot of single-cell sequencing data from kidney tissues. b-c Expression patterns of GBP2 and EIF2AK2 in different cell types between the control group and LN patients. d-f Expression patterns of GBP2 in the different LN ISN/RPS pathological classifications, Interstitial Inflammation, and Tubular Interstitial Fibrosis. g-i Expression patterns of EIF2AK2 in the different LN ISN/RPS pathological classifications, Interstitial Inflammation, and Tubular Interstitial Fibrosis. j t-SNE plot of single-cell sequencing data from kidney immune cells. k-l Expression patterns of GBP2 and EIF2AK2 in different immune cell types between the control group and LN patients. CE0: Epithelial cells, CD0: Dividing cells, CM0: Inflammatory CD16 + macrophages, CM2: Tissue-resident macrophages, CM3: Conventional dendritic cells, CT5b: CD56bright CD16 − NK cells, CT0a: Effector memory CD4 + T cells, CT3b: TFH-like cells, CT0b: Central memory CD4 + T cells, CT5a: Resident memory CD8 + T cells, CB2a: Naïve B cells, CT4: GZMK + CD8 + T cells, CT1: CD56dim CD16 + NK cells, CT3a: Treg cells, CT2: Cytotoxic T Lymphocytes, CM1: Phagocytic CD16 + macrophages, CB0: Activated B cells, CB2b: Plasmacytoid dendritic cells, CM4: M2-like CD16 + macrophages, CB1: Plasma cells and plasmablasts, CT6: ISG-high CD4 + T cells, CB3: ISG-high B cells

Article Snippet: Additionally, the distribution and expression characteristics of these hub genes within the kidney were examined using single-cell RNA sequencing (scRNA-seq) data ( https://singlecell.broadinstitute.org/single_cell/study/SCP279/amp-phase-1 ).

Techniques: Single-cell Analysis, Expressing, Single Cell, Sequencing, Control, Clinical Proteomics

A–C) Split violin plots display the distribution of key sequencing and cell quality metrics, with red representing snRNA-seq and blue representing scRNA-seq. Each pair of samples is connected by a line. Samples are coloured by the laboratory to indicate batch origin (A, B, C, F, H, I, L). Median number of genes detected per cell for each sample (A), Library size per sample after removing MT genes (B) and Sequencing saturation (C). D–E) Scatter plots showing an example of the correlation between library size and number of genes per cell in scRNA-seq (D) and snRNA-seq (E), coloured by cell type. Scatter plots for all samples are shown in Figure S7. F) Split violin plots showing proportion of reads mapped to intronic regions per sample. G) Distribution of total UMI counts per gene length bin across 50 gene length bins across all 22 samples. H–I) Split violin plots comparing the percentage of MT gene content (H) and ambient RNA (I). J) Correlation between the percentage of detected doublets and the total number of cells recovered per sample. K) Boxplots showing Jaccard scores representing similarity of HVGs identified within each method, based on the variance-stabilising transformation method. L) Comparison of the average number of clusters detected in three comparable resolutions in each sample.

Journal: bioRxiv

Article Title: Comparative Analysis of Single-Nucleus and Single-Cell RNA Sequencing in Human Bone Marrow Mononuclear Cells: Methodological Insights and Trade-offs

doi: 10.1101/2025.09.08.675012

Figure Lengend Snippet: A–C) Split violin plots display the distribution of key sequencing and cell quality metrics, with red representing snRNA-seq and blue representing scRNA-seq. Each pair of samples is connected by a line. Samples are coloured by the laboratory to indicate batch origin (A, B, C, F, H, I, L). Median number of genes detected per cell for each sample (A), Library size per sample after removing MT genes (B) and Sequencing saturation (C). D–E) Scatter plots showing an example of the correlation between library size and number of genes per cell in scRNA-seq (D) and snRNA-seq (E), coloured by cell type. Scatter plots for all samples are shown in Figure S7. F) Split violin plots showing proportion of reads mapped to intronic regions per sample. G) Distribution of total UMI counts per gene length bin across 50 gene length bins across all 22 samples. H–I) Split violin plots comparing the percentage of MT gene content (H) and ambient RNA (I). J) Correlation between the percentage of detected doublets and the total number of cells recovered per sample. K) Boxplots showing Jaccard scores representing similarity of HVGs identified within each method, based on the variance-stabilising transformation method. L) Comparison of the average number of clusters detected in three comparable resolutions in each sample.

Article Snippet: Among the most widely adopted of these are singlecell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq), commercialised by 10x Genomics ( ).

Techniques: Sequencing, Transformation Assay, Comparison