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10X Genomics visium libraries
Visium Libraries, supplied by 10X Genomics, 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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10X Genomics visium libraries
Visium Libraries, supplied by 10X Genomics, 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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Illumina Inc visium full-length cdna library
A The procedure to simulate single-cell long reads sequencing as a benchmark dataset. Different number of transcripts are first simulated under the guidance of a cell isoform expression dataset. Each transcript is then amplified according to their GC ratio. Then, the sequencing errors and truncations are introduced to mimic the Nanopore sequencing data quality. B The procedure to generate the real benchmark dataset. The left plot shows the sequencing for Jurkat cells: The 10× full-length <t>cDNA</t> library was randomly split into two parts, one for Pacbio and one for Nanopore. Sequences from Pacbio was processed by their official tool isoseq, while Nanopore sequencing was processed by other methods for single-cell isoform quantification. The output from each method is then compared with the isoform quantification from Isoseq by correlation. The right plot shows the sequencing for the mouse olfactory bulb: The <t>Visium</t> full-length cDNA library was randomly split into two parts, one for Illumina and one for Nanopore. The Ilumina sequencing is used to guide the cell barcode and UMI recovery to generate a confident single-cell isoform quantification. Methods to be benchmarked are applied only to the Nanopore data. The output from each method is then compared with the confident isoform quantification by correlation. C The per cell Spearman correlation on simulated data across different data quality for 220 cells. D The per-cell Spearman correlation on the full transcriptome simulated data across different down-sampling rates for 918 cells. E The per cell Spearman correlation on the real data: the upper one is the result on the Jurkat cells (5881 cells) and the bottom one is the result on the MOB (918 cells). Boxplots are defined as in Fig. . Source data are provided in 10.5281/zenodo.15320816.
Visium Full Length Cdna Library, supplied by Illumina 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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10X Genomics visium hd spatial gene expression library, mouse kidney (ffpe)
A The procedure to simulate single-cell long reads sequencing as a benchmark dataset. Different number of transcripts are first simulated under the guidance of a cell isoform expression dataset. Each transcript is then amplified according to their GC ratio. Then, the sequencing errors and truncations are introduced to mimic the Nanopore sequencing data quality. B The procedure to generate the real benchmark dataset. The left plot shows the sequencing for Jurkat cells: The 10× full-length <t>cDNA</t> library was randomly split into two parts, one for Pacbio and one for Nanopore. Sequences from Pacbio was processed by their official tool isoseq, while Nanopore sequencing was processed by other methods for single-cell isoform quantification. The output from each method is then compared with the isoform quantification from Isoseq by correlation. The right plot shows the sequencing for the mouse olfactory bulb: The <t>Visium</t> full-length cDNA library was randomly split into two parts, one for Illumina and one for Nanopore. The Ilumina sequencing is used to guide the cell barcode and UMI recovery to generate a confident single-cell isoform quantification. Methods to be benchmarked are applied only to the Nanopore data. The output from each method is then compared with the confident isoform quantification by correlation. C The per cell Spearman correlation on simulated data across different data quality for 220 cells. D The per-cell Spearman correlation on the full transcriptome simulated data across different down-sampling rates for 918 cells. E The per cell Spearman correlation on the real data: the upper one is the result on the Jurkat cells (5881 cells) and the bottom one is the result on the MOB (918 cells). Boxplots are defined as in Fig. . Source data are provided in 10.5281/zenodo.15320816.
Visium Hd Spatial Gene Expression Library, Mouse Kidney (Ffpe), supplied by 10X Genomics, 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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Illumina Inc visium libraries
A The procedure to simulate single-cell long reads sequencing as a benchmark dataset. Different number of transcripts are first simulated under the guidance of a cell isoform expression dataset. Each transcript is then amplified according to their GC ratio. Then, the sequencing errors and truncations are introduced to mimic the Nanopore sequencing data quality. B The procedure to generate the real benchmark dataset. The left plot shows the sequencing for Jurkat cells: The 10× full-length <t>cDNA</t> library was randomly split into two parts, one for Pacbio and one for Nanopore. Sequences from Pacbio was processed by their official tool isoseq, while Nanopore sequencing was processed by other methods for single-cell isoform quantification. The output from each method is then compared with the isoform quantification from Isoseq by correlation. The right plot shows the sequencing for the mouse olfactory bulb: The <t>Visium</t> full-length cDNA library was randomly split into two parts, one for Illumina and one for Nanopore. The Ilumina sequencing is used to guide the cell barcode and UMI recovery to generate a confident single-cell isoform quantification. Methods to be benchmarked are applied only to the Nanopore data. The output from each method is then compared with the confident isoform quantification by correlation. C The per cell Spearman correlation on simulated data across different data quality for 220 cells. D The per-cell Spearman correlation on the full transcriptome simulated data across different down-sampling rates for 918 cells. E The per cell Spearman correlation on the real data: the upper one is the result on the Jurkat cells (5881 cells) and the bottom one is the result on the MOB (918 cells). Boxplots are defined as in Fig. . Source data are provided in 10.5281/zenodo.15320816.
Visium Libraries, supplied by Illumina 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/result/visium libraries/product/Illumina Inc
Average 90 stars, based on 1 article reviews
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10X Genomics visium gene expression library t1t2e8
A The procedure to simulate single-cell long reads sequencing as a benchmark dataset. Different number of transcripts are first simulated under the guidance of a cell isoform expression dataset. Each transcript is then amplified according to their GC ratio. Then, the sequencing errors and truncations are introduced to mimic the Nanopore sequencing data quality. B The procedure to generate the real benchmark dataset. The left plot shows the sequencing for Jurkat cells: The 10× full-length <t>cDNA</t> library was randomly split into two parts, one for Pacbio and one for Nanopore. Sequences from Pacbio was processed by their official tool isoseq, while Nanopore sequencing was processed by other methods for single-cell isoform quantification. The output from each method is then compared with the isoform quantification from Isoseq by correlation. The right plot shows the sequencing for the mouse olfactory bulb: The <t>Visium</t> full-length cDNA library was randomly split into two parts, one for Illumina and one for Nanopore. The Ilumina sequencing is used to guide the cell barcode and UMI recovery to generate a confident single-cell isoform quantification. Methods to be benchmarked are applied only to the Nanopore data. The output from each method is then compared with the confident isoform quantification by correlation. C The per cell Spearman correlation on simulated data across different data quality for 220 cells. D The per-cell Spearman correlation on the full transcriptome simulated data across different down-sampling rates for 918 cells. E The per cell Spearman correlation on the real data: the upper one is the result on the Jurkat cells (5881 cells) and the bottom one is the result on the MOB (918 cells). Boxplots are defined as in Fig. . Source data are provided in 10.5281/zenodo.15320816.
Visium Gene Expression Library T1t2e8, supplied by 10X Genomics, 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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10X Genomics visium gene expression library t1t2-e8
A The procedure to simulate single-cell long reads sequencing as a benchmark dataset. Different number of transcripts are first simulated under the guidance of a cell isoform expression dataset. Each transcript is then amplified according to their GC ratio. Then, the sequencing errors and truncations are introduced to mimic the Nanopore sequencing data quality. B The procedure to generate the real benchmark dataset. The left plot shows the sequencing for Jurkat cells: The 10× full-length <t>cDNA</t> library was randomly split into two parts, one for Pacbio and one for Nanopore. Sequences from Pacbio was processed by their official tool isoseq, while Nanopore sequencing was processed by other methods for single-cell isoform quantification. The output from each method is then compared with the isoform quantification from Isoseq by correlation. The right plot shows the sequencing for the mouse olfactory bulb: The <t>Visium</t> full-length cDNA library was randomly split into two parts, one for Illumina and one for Nanopore. The Ilumina sequencing is used to guide the cell barcode and UMI recovery to generate a confident single-cell isoform quantification. Methods to be benchmarked are applied only to the Nanopore data. The output from each method is then compared with the confident isoform quantification by correlation. C The per cell Spearman correlation on simulated data across different data quality for 220 cells. D The per-cell Spearman correlation on the full transcriptome simulated data across different down-sampling rates for 918 cells. E The per cell Spearman correlation on the real data: the upper one is the result on the Jurkat cells (5881 cells) and the bottom one is the result on the MOB (918 cells). Boxplots are defined as in Fig. . Source data are provided in 10.5281/zenodo.15320816.
Visium Gene Expression Library T1t2 E8, supplied by 10X Genomics, 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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10X Genomics visium spatial gene expression library preparation slide
A The procedure to simulate single-cell long reads sequencing as a benchmark dataset. Different number of transcripts are first simulated under the guidance of a cell isoform expression dataset. Each transcript is then amplified according to their GC ratio. Then, the sequencing errors and truncations are introduced to mimic the Nanopore sequencing data quality. B The procedure to generate the real benchmark dataset. The left plot shows the sequencing for Jurkat cells: The 10× full-length <t>cDNA</t> library was randomly split into two parts, one for Pacbio and one for Nanopore. Sequences from Pacbio was processed by their official tool isoseq, while Nanopore sequencing was processed by other methods for single-cell isoform quantification. The output from each method is then compared with the isoform quantification from Isoseq by correlation. The right plot shows the sequencing for the mouse olfactory bulb: The <t>Visium</t> full-length cDNA library was randomly split into two parts, one for Illumina and one for Nanopore. The Ilumina sequencing is used to guide the cell barcode and UMI recovery to generate a confident single-cell isoform quantification. Methods to be benchmarked are applied only to the Nanopore data. The output from each method is then compared with the confident isoform quantification by correlation. C The per cell Spearman correlation on simulated data across different data quality for 220 cells. D The per-cell Spearman correlation on the full transcriptome simulated data across different down-sampling rates for 918 cells. E The per cell Spearman correlation on the real data: the upper one is the result on the Jurkat cells (5881 cells) and the bottom one is the result on the MOB (918 cells). Boxplots are defined as in Fig. . Source data are provided in 10.5281/zenodo.15320816.
Visium Spatial Gene Expression Library Preparation Slide, supplied by 10X Genomics, 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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Illumina Inc 10x visium spatial transcriptome library
A The procedure to simulate single-cell long reads sequencing as a benchmark dataset. Different number of transcripts are first simulated under the guidance of a cell isoform expression dataset. Each transcript is then amplified according to their GC ratio. Then, the sequencing errors and truncations are introduced to mimic the Nanopore sequencing data quality. B The procedure to generate the real benchmark dataset. The left plot shows the sequencing for Jurkat cells: The 10× full-length <t>cDNA</t> library was randomly split into two parts, one for Pacbio and one for Nanopore. Sequences from Pacbio was processed by their official tool isoseq, while Nanopore sequencing was processed by other methods for single-cell isoform quantification. The output from each method is then compared with the isoform quantification from Isoseq by correlation. The right plot shows the sequencing for the mouse olfactory bulb: The <t>Visium</t> full-length cDNA library was randomly split into two parts, one for Illumina and one for Nanopore. The Ilumina sequencing is used to guide the cell barcode and UMI recovery to generate a confident single-cell isoform quantification. Methods to be benchmarked are applied only to the Nanopore data. The output from each method is then compared with the confident isoform quantification by correlation. C The per cell Spearman correlation on simulated data across different data quality for 220 cells. D The per-cell Spearman correlation on the full transcriptome simulated data across different down-sampling rates for 918 cells. E The per cell Spearman correlation on the real data: the upper one is the result on the Jurkat cells (5881 cells) and the bottom one is the result on the MOB (918 cells). Boxplots are defined as in Fig. . Source data are provided in 10.5281/zenodo.15320816.
10x Visium Spatial Transcriptome Library, supplied by Illumina 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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10X Genomics visium sequencing libraries preparation
A The procedure to simulate single-cell long reads sequencing as a benchmark dataset. Different number of transcripts are first simulated under the guidance of a cell isoform expression dataset. Each transcript is then amplified according to their GC ratio. Then, the sequencing errors and truncations are introduced to mimic the Nanopore sequencing data quality. B The procedure to generate the real benchmark dataset. The left plot shows the sequencing for Jurkat cells: The 10× full-length <t>cDNA</t> library was randomly split into two parts, one for Pacbio and one for Nanopore. Sequences from Pacbio was processed by their official tool isoseq, while Nanopore sequencing was processed by other methods for single-cell isoform quantification. The output from each method is then compared with the isoform quantification from Isoseq by correlation. The right plot shows the sequencing for the mouse olfactory bulb: The <t>Visium</t> full-length cDNA library was randomly split into two parts, one for Illumina and one for Nanopore. The Ilumina sequencing is used to guide the cell barcode and UMI recovery to generate a confident single-cell isoform quantification. Methods to be benchmarked are applied only to the Nanopore data. The output from each method is then compared with the confident isoform quantification by correlation. C The per cell Spearman correlation on simulated data across different data quality for 220 cells. D The per-cell Spearman correlation on the full transcriptome simulated data across different down-sampling rates for 918 cells. E The per cell Spearman correlation on the real data: the upper one is the result on the Jurkat cells (5881 cells) and the bottom one is the result on the MOB (918 cells). Boxplots are defined as in Fig. . Source data are provided in 10.5281/zenodo.15320816.
Visium Sequencing Libraries Preparation, supplied by 10X Genomics, 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
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10X Genomics visium spatial gene expression 30 library construction v1 kit
A The procedure to simulate single-cell long reads sequencing as a benchmark dataset. Different number of transcripts are first simulated under the guidance of a cell isoform expression dataset. Each transcript is then amplified according to their GC ratio. Then, the sequencing errors and truncations are introduced to mimic the Nanopore sequencing data quality. B The procedure to generate the real benchmark dataset. The left plot shows the sequencing for Jurkat cells: The 10× full-length <t>cDNA</t> library was randomly split into two parts, one for Pacbio and one for Nanopore. Sequences from Pacbio was processed by their official tool isoseq, while Nanopore sequencing was processed by other methods for single-cell isoform quantification. The output from each method is then compared with the isoform quantification from Isoseq by correlation. The right plot shows the sequencing for the mouse olfactory bulb: The <t>Visium</t> full-length cDNA library was randomly split into two parts, one for Illumina and one for Nanopore. The Ilumina sequencing is used to guide the cell barcode and UMI recovery to generate a confident single-cell isoform quantification. Methods to be benchmarked are applied only to the Nanopore data. The output from each method is then compared with the confident isoform quantification by correlation. C The per cell Spearman correlation on simulated data across different data quality for 220 cells. D The per-cell Spearman correlation on the full transcriptome simulated data across different down-sampling rates for 918 cells. E The per cell Spearman correlation on the real data: the upper one is the result on the Jurkat cells (5881 cells) and the bottom one is the result on the MOB (918 cells). Boxplots are defined as in Fig. . Source data are provided in 10.5281/zenodo.15320816.
Visium Spatial Gene Expression 30 Library Construction V1 Kit, supplied by 10X Genomics, 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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A The procedure to simulate single-cell long reads sequencing as a benchmark dataset. Different number of transcripts are first simulated under the guidance of a cell isoform expression dataset. Each transcript is then amplified according to their GC ratio. Then, the sequencing errors and truncations are introduced to mimic the Nanopore sequencing data quality. B The procedure to generate the real benchmark dataset. The left plot shows the sequencing for Jurkat cells: The 10× full-length cDNA library was randomly split into two parts, one for Pacbio and one for Nanopore. Sequences from Pacbio was processed by their official tool isoseq, while Nanopore sequencing was processed by other methods for single-cell isoform quantification. The output from each method is then compared with the isoform quantification from Isoseq by correlation. The right plot shows the sequencing for the mouse olfactory bulb: The Visium full-length cDNA library was randomly split into two parts, one for Illumina and one for Nanopore. The Ilumina sequencing is used to guide the cell barcode and UMI recovery to generate a confident single-cell isoform quantification. Methods to be benchmarked are applied only to the Nanopore data. The output from each method is then compared with the confident isoform quantification by correlation. C The per cell Spearman correlation on simulated data across different data quality for 220 cells. D The per-cell Spearman correlation on the full transcriptome simulated data across different down-sampling rates for 918 cells. E The per cell Spearman correlation on the real data: the upper one is the result on the Jurkat cells (5881 cells) and the bottom one is the result on the MOB (918 cells). Boxplots are defined as in Fig. . Source data are provided in 10.5281/zenodo.15320816.

Journal: Nature Communications

Article Title: Single cell and spatial alternative splicing analysis with Nanopore long read sequencing

doi: 10.1038/s41467-025-60902-2

Figure Lengend Snippet: A The procedure to simulate single-cell long reads sequencing as a benchmark dataset. Different number of transcripts are first simulated under the guidance of a cell isoform expression dataset. Each transcript is then amplified according to their GC ratio. Then, the sequencing errors and truncations are introduced to mimic the Nanopore sequencing data quality. B The procedure to generate the real benchmark dataset. The left plot shows the sequencing for Jurkat cells: The 10× full-length cDNA library was randomly split into two parts, one for Pacbio and one for Nanopore. Sequences from Pacbio was processed by their official tool isoseq, while Nanopore sequencing was processed by other methods for single-cell isoform quantification. The output from each method is then compared with the isoform quantification from Isoseq by correlation. The right plot shows the sequencing for the mouse olfactory bulb: The Visium full-length cDNA library was randomly split into two parts, one for Illumina and one for Nanopore. The Ilumina sequencing is used to guide the cell barcode and UMI recovery to generate a confident single-cell isoform quantification. Methods to be benchmarked are applied only to the Nanopore data. The output from each method is then compared with the confident isoform quantification by correlation. C The per cell Spearman correlation on simulated data across different data quality for 220 cells. D The per-cell Spearman correlation on the full transcriptome simulated data across different down-sampling rates for 918 cells. E The per cell Spearman correlation on the real data: the upper one is the result on the Jurkat cells (5881 cells) and the bottom one is the result on the MOB (918 cells). Boxplots are defined as in Fig. . Source data are provided in 10.5281/zenodo.15320816.

Article Snippet: The right plot shows the sequencing for the mouse olfactory bulb: The Visium full-length cDNA library was randomly split into two parts, one for Illumina and one for Nanopore.

Techniques: Sequencing, Expressing, Amplification, Nanopore Sequencing, cDNA Library Assay, Sampling

A The UMAP of the colorectal cancer metastasis to the liver (CRCLM) single cell data, each point is a cell colored by its cell type definition. B The paired VISIUM sequencing for the same CRCLM sample. The left plot shows the histology, indicating the tumor region. The right plot shows the dominant cell type in each spot. C The relationship between \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{\psi }$$\end{document} ψ ¯ and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\phi$$\end{document} ϕ , \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{\psi }$$\end{document} ψ ¯ means the mean of percent-spliced-in for an exon across the cell population, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\phi$$\end{document} ϕ means the inter-cell heterogeneity of this exon. The histograms of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document} ψ are colored by their \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{\psi }$$\end{document} ψ ¯ . The dots above each histogram show the alternative splicing across the cell population. The dot filled in red means the target exon is preserved in the isoforms in this cell, while the dot filled in white means the target exon is spliced out. The circle filled in red gradient means the cell expresses both isoforms. D ϕ vs . \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{\psi }$$\end{document} ψ ¯ distribution for alternative spliced exons in CRCLM single cell data, the color indicates the confidence interval of ϕ estimation. E The \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document} ψ distribution for exon 6 of MYL6 , which has a very high ϕ , indicating high intercell heterogeneity. In this histogram, x -axis shows the exon \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document} ψ and y -axis shows the cell frequency whose \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document} ψ value falls in this bin. As \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document} ψ estimation is influenced by the gene expression, the average gene expression for is bin is shown in color gradient. F The left plot shows the ψ distribution for exon 6 of MYL6 across cells, epithelial show the highest inclusion-level of this exon. The expression of two dominant isoforms across different cells are shown in the right heatmap, epithelial has higher expression of MYL6-218 compared to other cell types. G The sashimi plot shows the comparison of bulk expression of MYL6-207 and MYL6-218 between epithelial cells and other immune cells. H The spatial view of the expression for MYL6-218 (top) and MYL6-207 (bottom). The regions for myeloid cells are marked by black circles. Source data are provided in 10.5281/zenodo.15320816.

Journal: Nature Communications

Article Title: Single cell and spatial alternative splicing analysis with Nanopore long read sequencing

doi: 10.1038/s41467-025-60902-2

Figure Lengend Snippet: A The UMAP of the colorectal cancer metastasis to the liver (CRCLM) single cell data, each point is a cell colored by its cell type definition. B The paired VISIUM sequencing for the same CRCLM sample. The left plot shows the histology, indicating the tumor region. The right plot shows the dominant cell type in each spot. C The relationship between \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{\psi }$$\end{document} ψ ¯ and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\phi$$\end{document} ϕ , \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{\psi }$$\end{document} ψ ¯ means the mean of percent-spliced-in for an exon across the cell population, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\phi$$\end{document} ϕ means the inter-cell heterogeneity of this exon. The histograms of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document} ψ are colored by their \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{\psi }$$\end{document} ψ ¯ . The dots above each histogram show the alternative splicing across the cell population. The dot filled in red means the target exon is preserved in the isoforms in this cell, while the dot filled in white means the target exon is spliced out. The circle filled in red gradient means the cell expresses both isoforms. D ϕ vs . \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{\psi }$$\end{document} ψ ¯ distribution for alternative spliced exons in CRCLM single cell data, the color indicates the confidence interval of ϕ estimation. E The \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document} ψ distribution for exon 6 of MYL6 , which has a very high ϕ , indicating high intercell heterogeneity. In this histogram, x -axis shows the exon \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document} ψ and y -axis shows the cell frequency whose \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document} ψ value falls in this bin. As \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document} ψ estimation is influenced by the gene expression, the average gene expression for is bin is shown in color gradient. F The left plot shows the ψ distribution for exon 6 of MYL6 across cells, epithelial show the highest inclusion-level of this exon. The expression of two dominant isoforms across different cells are shown in the right heatmap, epithelial has higher expression of MYL6-218 compared to other cell types. G The sashimi plot shows the comparison of bulk expression of MYL6-207 and MYL6-218 between epithelial cells and other immune cells. H The spatial view of the expression for MYL6-218 (top) and MYL6-207 (bottom). The regions for myeloid cells are marked by black circles. Source data are provided in 10.5281/zenodo.15320816.

Article Snippet: The right plot shows the sequencing for the mouse olfactory bulb: The Visium full-length cDNA library was randomly split into two parts, one for Illumina and one for Nanopore.

Techniques: Sequencing, Alternative Splicing, Gene Expression, Expressing, Comparison

A The spatial plot for the VISIUM slice, each spot is colored by the layer identification. B ϕ vs . \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{\psi }$$\end{document} ψ ¯ distribution for alternative spliced exons, color indicates the confidence interval of ϕ . C The mean change vs. variance change of ψ for all significant meta-sites which are alternatively spliced across different layers. The point size indicates the significance after FDR control, while the color indicates in which layer this meta-site is alternatively spliced. D The ψ distribution for exon 3 of Plp1 , which has the highest ϕ and shows a bimodal distribution, indicating a low inter-cell heterogeneity. E Spatial plot of spots in the slice of mouse olfactory bulb. The spots are colored by ψ for exon 3 of Plp1 . Cells which have low expression (<3) of this gene and could not give a confident ψ estimation are the smallest points colored in gray. The gene expression for each spot is shown by the point size, while the ψ estimation is shown by the color gradient. F , G The alternative splicing for Plp1 in different layers. H The ψ distribution for exon 4 of Mapre3 , which has a relatively high ϕ and show a bimodal distribution, indicating a high inter-cell heterogeneity. I Spatial plot of spots in the slice of mouse olfactory bulb. The spots are colored by ψ for exon 4 of Mapre3 . J , K The alternative splicing for Mapre3 in different layers. Source data are provided in 10.5281/zenodo.15320816.

Journal: Nature Communications

Article Title: Single cell and spatial alternative splicing analysis with Nanopore long read sequencing

doi: 10.1038/s41467-025-60902-2

Figure Lengend Snippet: A The spatial plot for the VISIUM slice, each spot is colored by the layer identification. B ϕ vs . \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{\psi }$$\end{document} ψ ¯ distribution for alternative spliced exons, color indicates the confidence interval of ϕ . C The mean change vs. variance change of ψ for all significant meta-sites which are alternatively spliced across different layers. The point size indicates the significance after FDR control, while the color indicates in which layer this meta-site is alternatively spliced. D The ψ distribution for exon 3 of Plp1 , which has the highest ϕ and shows a bimodal distribution, indicating a low inter-cell heterogeneity. E Spatial plot of spots in the slice of mouse olfactory bulb. The spots are colored by ψ for exon 3 of Plp1 . Cells which have low expression (<3) of this gene and could not give a confident ψ estimation are the smallest points colored in gray. The gene expression for each spot is shown by the point size, while the ψ estimation is shown by the color gradient. F , G The alternative splicing for Plp1 in different layers. H The ψ distribution for exon 4 of Mapre3 , which has a relatively high ϕ and show a bimodal distribution, indicating a high inter-cell heterogeneity. I Spatial plot of spots in the slice of mouse olfactory bulb. The spots are colored by ψ for exon 4 of Mapre3 . J , K The alternative splicing for Mapre3 in different layers. Source data are provided in 10.5281/zenodo.15320816.

Article Snippet: The right plot shows the sequencing for the mouse olfactory bulb: The Visium full-length cDNA library was randomly split into two parts, one for Illumina and one for Nanopore.

Techniques: Control, Expressing, Gene Expression, Alternative Splicing