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single cell somatic mutations  (Broad Clinical Labs)


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    Broad Clinical Labs single cell somatic mutations
    Determining the lymphoid landscape in pediatric specimens: A. Schematics of the study. 23 freshly isolated reactive and cancerous pediatric (<18 y.o.) lymph nodes, and two reactive adult lymph nodes were included. Samples were prepared for <t>single</t> <t>cell</t> RNA sequencing (scRNAseq), single cell VDJ sequencing (scVDJseq, BCR and TCR), flow cytometry and, for Hodgkin lymphoma (pHL), spatial transcriptomics. (Schematics created in https://BioRender.com ) B. Cell type annotation of integrated reactive lymph node (pediatric and adult) represented with 2D UMAP. C. (Left) Dot plot highlighting the top 2 marker genes for each identified cell type. Size of the dot indicates percentage of expression, variation in color specifies expression. (Middle) Proportion of VDJ clonotype by cell type. (Right) Proportion of each cell type distribute across all sample integrated in B. D. Transcript splicing status by cell types. E. Gene set enrichment analysis of progenitor B and T cells against progenitor B and differentiating T cell gene sets, respectively. F. (Left) UMAP distribution of adult lymph node cells (n= 21,851 cells) and randomly selected 21,851 pediatric cells. (Right) Proportion of sample source by each cell type. Arrowheads indicate progenitor clusters. G. (left) Representative inferCNV heatmap of reactive lymph node sample. Each row represents a randomly selected cell, and each column represents a gene ordered by chromosomes. Color code indicates inferred chromosome gain/loss. (Top right) CNV score distribution across reactive lymphoid landscape. (Lower right) separation of CNV reference based on chromosome 19 expression resulted in two compartments: 20% with high CNV score (2 nd CNVref) and the rest 80% (1 st CNVref).
    Single Cell Somatic Mutations, supplied by Broad Clinical Labs, used in various techniques. Bioz Stars score: 96/100, based on 834 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/single+cell+somatic+mutations/bio_rxiv__64898__2026__04__21__719850-25-21-19?v=Broad+Clinical+Labs
    Average 96 stars, based on 834 article reviews
    single cell somatic mutations - by Bioz Stars, 2026-08
    96/100 stars

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    1) Product Images from "Single cell analysis reveals molecular traits of pediatric lymphoma resistant subclones"

    Article Title: Single cell analysis reveals molecular traits of pediatric lymphoma resistant subclones

    Journal: bioRxiv

    doi: 10.64898/2026.04.21.719850

    Determining the lymphoid landscape in pediatric specimens: A. Schematics of the study. 23 freshly isolated reactive and cancerous pediatric (<18 y.o.) lymph nodes, and two reactive adult lymph nodes were included. Samples were prepared for single cell RNA sequencing (scRNAseq), single cell VDJ sequencing (scVDJseq, BCR and TCR), flow cytometry and, for Hodgkin lymphoma (pHL), spatial transcriptomics. (Schematics created in https://BioRender.com ) B. Cell type annotation of integrated reactive lymph node (pediatric and adult) represented with 2D UMAP. C. (Left) Dot plot highlighting the top 2 marker genes for each identified cell type. Size of the dot indicates percentage of expression, variation in color specifies expression. (Middle) Proportion of VDJ clonotype by cell type. (Right) Proportion of each cell type distribute across all sample integrated in B. D. Transcript splicing status by cell types. E. Gene set enrichment analysis of progenitor B and T cells against progenitor B and differentiating T cell gene sets, respectively. F. (Left) UMAP distribution of adult lymph node cells (n= 21,851 cells) and randomly selected 21,851 pediatric cells. (Right) Proportion of sample source by each cell type. Arrowheads indicate progenitor clusters. G. (left) Representative inferCNV heatmap of reactive lymph node sample. Each row represents a randomly selected cell, and each column represents a gene ordered by chromosomes. Color code indicates inferred chromosome gain/loss. (Top right) CNV score distribution across reactive lymphoid landscape. (Lower right) separation of CNV reference based on chromosome 19 expression resulted in two compartments: 20% with high CNV score (2 nd CNVref) and the rest 80% (1 st CNVref).
    Figure Legend Snippet: Determining the lymphoid landscape in pediatric specimens: A. Schematics of the study. 23 freshly isolated reactive and cancerous pediatric (<18 y.o.) lymph nodes, and two reactive adult lymph nodes were included. Samples were prepared for single cell RNA sequencing (scRNAseq), single cell VDJ sequencing (scVDJseq, BCR and TCR), flow cytometry and, for Hodgkin lymphoma (pHL), spatial transcriptomics. (Schematics created in https://BioRender.com ) B. Cell type annotation of integrated reactive lymph node (pediatric and adult) represented with 2D UMAP. C. (Left) Dot plot highlighting the top 2 marker genes for each identified cell type. Size of the dot indicates percentage of expression, variation in color specifies expression. (Middle) Proportion of VDJ clonotype by cell type. (Right) Proportion of each cell type distribute across all sample integrated in B. D. Transcript splicing status by cell types. E. Gene set enrichment analysis of progenitor B and T cells against progenitor B and differentiating T cell gene sets, respectively. F. (Left) UMAP distribution of adult lymph node cells (n= 21,851 cells) and randomly selected 21,851 pediatric cells. (Right) Proportion of sample source by each cell type. Arrowheads indicate progenitor clusters. G. (left) Representative inferCNV heatmap of reactive lymph node sample. Each row represents a randomly selected cell, and each column represents a gene ordered by chromosomes. Color code indicates inferred chromosome gain/loss. (Top right) CNV score distribution across reactive lymphoid landscape. (Lower right) separation of CNV reference based on chromosome 19 expression resulted in two compartments: 20% with high CNV score (2 nd CNVref) and the rest 80% (1 st CNVref).

    Techniques Used: Isolation, Single Cell, RNA Sequencing, Sequencing, Flow Cytometry, Spatial Transcriptomics, Marker, Expressing

    A single-cell atlas uncovers lymphoma origin-specific characteristics. A. Integrated scRNAseq UMAP over all pReLy and lymphoma (in grey) samples. B. (top) scRNAseq UMAP plotted by pathological origin. C-D. Proportion of top 3 BCR and TCR clones per sample. Hyperexpanded BCR clones; pBL_01: IGHV1−46.NA.IGHJ4.IGHM_IGLV2−11.IGLJ2.IGLC2, pBL_02: IGHV3−74.NA.IGHJ6.IGHM_IGLV2−18.IGLJ3.IGLC3, pBL_03: IGHV3−30.NA.IGHJ4.IGHM_IGKV2−24.IGKJ2.IGKC and hyperexpanded TCR clones; pTLL_02: TRAV25.TRAJ45.TRAC_TRBV29−1.NA.TRBJ2−1.TRBC2; pTLL_03: NA_TRBV7−9.NA.TRBJ1−1.TRBC1, pTLL_04: NA_TRBV20−1.TRBD1.TRBJ1−2.TRBC1). (Bottom) Contour plots of hyperexpanded (Proportion > 0.1) immune receptor distribution. Color code matches that of the bar plot. E. Proportions of predicted cell types of single cells from lymphoma samples.
    Figure Legend Snippet: A single-cell atlas uncovers lymphoma origin-specific characteristics. A. Integrated scRNAseq UMAP over all pReLy and lymphoma (in grey) samples. B. (top) scRNAseq UMAP plotted by pathological origin. C-D. Proportion of top 3 BCR and TCR clones per sample. Hyperexpanded BCR clones; pBL_01: IGHV1−46.NA.IGHJ4.IGHM_IGLV2−11.IGLJ2.IGLC2, pBL_02: IGHV3−74.NA.IGHJ6.IGHM_IGLV2−18.IGLJ3.IGLC3, pBL_03: IGHV3−30.NA.IGHJ4.IGHM_IGKV2−24.IGKJ2.IGKC and hyperexpanded TCR clones; pTLL_02: TRAV25.TRAJ45.TRAC_TRBV29−1.NA.TRBJ2−1.TRBC2; pTLL_03: NA_TRBV7−9.NA.TRBJ1−1.TRBC1, pTLL_04: NA_TRBV20−1.TRBD1.TRBJ1−2.TRBC1). (Bottom) Contour plots of hyperexpanded (Proportion > 0.1) immune receptor distribution. Color code matches that of the bar plot. E. Proportions of predicted cell types of single cells from lymphoma samples.

    Techniques Used: Single Cell, Clone Assay



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    single cell somatic mutations  (Broad Clinical Labs)
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    Broad Clinical Labs single cell somatic mutations
    Determining the lymphoid landscape in pediatric specimens: A. Schematics of the study. 23 freshly isolated reactive and cancerous pediatric (<18 y.o.) lymph nodes, and two reactive adult lymph nodes were included. Samples were prepared for <t>single</t> <t>cell</t> RNA sequencing (scRNAseq), single cell VDJ sequencing (scVDJseq, BCR and TCR), flow cytometry and, for Hodgkin lymphoma (pHL), spatial transcriptomics. (Schematics created in https://BioRender.com ) B. Cell type annotation of integrated reactive lymph node (pediatric and adult) represented with 2D UMAP. C. (Left) Dot plot highlighting the top 2 marker genes for each identified cell type. Size of the dot indicates percentage of expression, variation in color specifies expression. (Middle) Proportion of VDJ clonotype by cell type. (Right) Proportion of each cell type distribute across all sample integrated in B. D. Transcript splicing status by cell types. E. Gene set enrichment analysis of progenitor B and T cells against progenitor B and differentiating T cell gene sets, respectively. F. (Left) UMAP distribution of adult lymph node cells (n= 21,851 cells) and randomly selected 21,851 pediatric cells. (Right) Proportion of sample source by each cell type. Arrowheads indicate progenitor clusters. G. (left) Representative inferCNV heatmap of reactive lymph node sample. Each row represents a randomly selected cell, and each column represents a gene ordered by chromosomes. Color code indicates inferred chromosome gain/loss. (Top right) CNV score distribution across reactive lymphoid landscape. (Lower right) separation of CNV reference based on chromosome 19 expression resulted in two compartments: 20% with high CNV score (2 nd CNVref) and the rest 80% (1 st CNVref).
    Single Cell Somatic Mutations, 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/single+cell+somatic+mutations/bio_rxiv__64898__2026__04__21__719850-25-21-19?v=Broad+Clinical+Labs
    Average 96 stars, based on 1 article reviews
    single cell somatic mutations - by Bioz Stars, 2026-08
    96/100 stars
    		  Buy from Supplier

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    Determining the lymphoid landscape in pediatric specimens: A. Schematics of the study. 23 freshly isolated reactive and cancerous pediatric (<18 y.o.) lymph nodes, and two reactive adult lymph nodes were included. Samples were prepared for single cell RNA sequencing (scRNAseq), single cell VDJ sequencing (scVDJseq, BCR and TCR), flow cytometry and, for Hodgkin lymphoma (pHL), spatial transcriptomics. (Schematics created in https://BioRender.com ) B. Cell type annotation of integrated reactive lymph node (pediatric and adult) represented with 2D UMAP. C. (Left) Dot plot highlighting the top 2 marker genes for each identified cell type. Size of the dot indicates percentage of expression, variation in color specifies expression. (Middle) Proportion of VDJ clonotype by cell type. (Right) Proportion of each cell type distribute across all sample integrated in B. D. Transcript splicing status by cell types. E. Gene set enrichment analysis of progenitor B and T cells against progenitor B and differentiating T cell gene sets, respectively. F. (Left) UMAP distribution of adult lymph node cells (n= 21,851 cells) and randomly selected 21,851 pediatric cells. (Right) Proportion of sample source by each cell type. Arrowheads indicate progenitor clusters. G. (left) Representative inferCNV heatmap of reactive lymph node sample. Each row represents a randomly selected cell, and each column represents a gene ordered by chromosomes. Color code indicates inferred chromosome gain/loss. (Top right) CNV score distribution across reactive lymphoid landscape. (Lower right) separation of CNV reference based on chromosome 19 expression resulted in two compartments: 20% with high CNV score (2 nd CNVref) and the rest 80% (1 st CNVref).

    Journal: bioRxiv

    Article Title: Single cell analysis reveals molecular traits of pediatric lymphoma resistant subclones

    doi: 10.64898/2026.04.21.719850

    Figure Lengend Snippet: Determining the lymphoid landscape in pediatric specimens: A. Schematics of the study. 23 freshly isolated reactive and cancerous pediatric (<18 y.o.) lymph nodes, and two reactive adult lymph nodes were included. Samples were prepared for single cell RNA sequencing (scRNAseq), single cell VDJ sequencing (scVDJseq, BCR and TCR), flow cytometry and, for Hodgkin lymphoma (pHL), spatial transcriptomics. (Schematics created in https://BioRender.com ) B. Cell type annotation of integrated reactive lymph node (pediatric and adult) represented with 2D UMAP. C. (Left) Dot plot highlighting the top 2 marker genes for each identified cell type. Size of the dot indicates percentage of expression, variation in color specifies expression. (Middle) Proportion of VDJ clonotype by cell type. (Right) Proportion of each cell type distribute across all sample integrated in B. D. Transcript splicing status by cell types. E. Gene set enrichment analysis of progenitor B and T cells against progenitor B and differentiating T cell gene sets, respectively. F. (Left) UMAP distribution of adult lymph node cells (n= 21,851 cells) and randomly selected 21,851 pediatric cells. (Right) Proportion of sample source by each cell type. Arrowheads indicate progenitor clusters. G. (left) Representative inferCNV heatmap of reactive lymph node sample. Each row represents a randomly selected cell, and each column represents a gene ordered by chromosomes. Color code indicates inferred chromosome gain/loss. (Top right) CNV score distribution across reactive lymphoid landscape. (Lower right) separation of CNV reference based on chromosome 19 expression resulted in two compartments: 20% with high CNV score (2 nd CNVref) and the rest 80% (1 st CNVref).

    Article Snippet: In pursuit of a R/R related lymphoma subclone, we here combined scRNA-seq with scVDJ-seq, inferred copy number variation (inferCNV, https://github.com/broadinstitute/inferCNV ), single-cell somatic mutations , and marker gene expression to reconstruct a phylogenetic tree for each lymphoma sample.

    Techniques: Isolation, Single Cell, RNA Sequencing, Sequencing, Flow Cytometry, Spatial Transcriptomics, Marker, Expressing

    A single-cell atlas uncovers lymphoma origin-specific characteristics. A. Integrated scRNAseq UMAP over all pReLy and lymphoma (in grey) samples. B. (top) scRNAseq UMAP plotted by pathological origin. C-D. Proportion of top 3 BCR and TCR clones per sample. Hyperexpanded BCR clones; pBL_01: IGHV1−46.NA.IGHJ4.IGHM_IGLV2−11.IGLJ2.IGLC2, pBL_02: IGHV3−74.NA.IGHJ6.IGHM_IGLV2−18.IGLJ3.IGLC3, pBL_03: IGHV3−30.NA.IGHJ4.IGHM_IGKV2−24.IGKJ2.IGKC and hyperexpanded TCR clones; pTLL_02: TRAV25.TRAJ45.TRAC_TRBV29−1.NA.TRBJ2−1.TRBC2; pTLL_03: NA_TRBV7−9.NA.TRBJ1−1.TRBC1, pTLL_04: NA_TRBV20−1.TRBD1.TRBJ1−2.TRBC1). (Bottom) Contour plots of hyperexpanded (Proportion > 0.1) immune receptor distribution. Color code matches that of the bar plot. E. Proportions of predicted cell types of single cells from lymphoma samples.

    Journal: bioRxiv

    Article Title: Single cell analysis reveals molecular traits of pediatric lymphoma resistant subclones

    doi: 10.64898/2026.04.21.719850

    Figure Lengend Snippet: A single-cell atlas uncovers lymphoma origin-specific characteristics. A. Integrated scRNAseq UMAP over all pReLy and lymphoma (in grey) samples. B. (top) scRNAseq UMAP plotted by pathological origin. C-D. Proportion of top 3 BCR and TCR clones per sample. Hyperexpanded BCR clones; pBL_01: IGHV1−46.NA.IGHJ4.IGHM_IGLV2−11.IGLJ2.IGLC2, pBL_02: IGHV3−74.NA.IGHJ6.IGHM_IGLV2−18.IGLJ3.IGLC3, pBL_03: IGHV3−30.NA.IGHJ4.IGHM_IGKV2−24.IGKJ2.IGKC and hyperexpanded TCR clones; pTLL_02: TRAV25.TRAJ45.TRAC_TRBV29−1.NA.TRBJ2−1.TRBC2; pTLL_03: NA_TRBV7−9.NA.TRBJ1−1.TRBC1, pTLL_04: NA_TRBV20−1.TRBD1.TRBJ1−2.TRBC1). (Bottom) Contour plots of hyperexpanded (Proportion > 0.1) immune receptor distribution. Color code matches that of the bar plot. E. Proportions of predicted cell types of single cells from lymphoma samples.

    Article Snippet: In pursuit of a R/R related lymphoma subclone, we here combined scRNA-seq with scVDJ-seq, inferred copy number variation (inferCNV, https://github.com/broadinstitute/inferCNV ), single-cell somatic mutations , and marker gene expression to reconstruct a phylogenetic tree for each lymphoma sample.

    Techniques: Single Cell, Clone Assay