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exome sequencing wes data  (Broad Clinical Labs)


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    Structured Review

    Broad Clinical Labs exome sequencing wes data
    Study design for patient cohorts and genomic analyses (A) Initial study criteria with study design based on sample availability and treatment timing. After <t>whole-exome</t> <t>sequencing,</t> PhylogicNDT and SignatureAnalyzer were used to identify clones and compare mutational signatures, respectively. Functional mutations were characterized based on existing evidence previously published or annotated in genomic databases, such as COSMIC, ClinVar, and OncoKB. (B) Signaling pathway landscape for paired-cohort participants ( n = 26) organized by time on tyrosine kinase treatment (days by sampled TKI) and acquired ( n = 8) or intrinsic ( n = 18) resistance. Known mechanisms in ERBB2 and PIK3CA are highlighted. Signaling pathways are depicted in decreasing frequency per number of mutations for the entire cohort of paired participants. Arrows indicate the subclonal trajectory as either growing, stable, or shrinking. The TP53 and ESR1+ regulator pathways were significantly mutated ( q < 0.05; MutSig, Fisher’s method). Stacked bar charts indicate relative contributions of mutational signatures identified by SignatureAnalyzer to the mutational spectrum of each participant. (C) Pathway-level comparison of mutation frequency between four cohorts: intrinsic ( n = 18), acquired ( n = 8), pre-TKI ( n = 55), and post-TKI ( n = 30). Pathways were included if they possessed at least one mutation. There were no significant differences in pathway-level mutation frequency between cohorts (Fisher’s exact test).
    Exome Sequencing Wes Data, supplied by Broad Clinical Labs, used in various techniques. Bioz Stars score: 95/100, based on 311 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/exome+sequence+data/Whole+Exome+Sequencing/pmc12802574-231-9-16
    Average 95 stars, based on 311 article reviews
    exome sequencing wes data - by Bioz Stars, 2026-11
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    Images

    1) Product Images from "Detection of heterogeneous resistance mechanisms to tyrosine kinase inhibitors from cell-free DNA"

    Article Title: Detection of heterogeneous resistance mechanisms to tyrosine kinase inhibitors from cell-free DNA

    Journal: Cell Genomics

    doi: 10.1016/j.xgen.2025.100987

    Study design for patient cohorts and genomic analyses (A) Initial study criteria with study design based on sample availability and treatment timing. After whole-exome sequencing, PhylogicNDT and SignatureAnalyzer were used to identify clones and compare mutational signatures, respectively. Functional mutations were characterized based on existing evidence previously published or annotated in genomic databases, such as COSMIC, ClinVar, and OncoKB. (B) Signaling pathway landscape for paired-cohort participants ( n = 26) organized by time on tyrosine kinase treatment (days by sampled TKI) and acquired ( n = 8) or intrinsic ( n = 18) resistance. Known mechanisms in ERBB2 and PIK3CA are highlighted. Signaling pathways are depicted in decreasing frequency per number of mutations for the entire cohort of paired participants. Arrows indicate the subclonal trajectory as either growing, stable, or shrinking. The TP53 and ESR1+ regulator pathways were significantly mutated ( q < 0.05; MutSig, Fisher’s method). Stacked bar charts indicate relative contributions of mutational signatures identified by SignatureAnalyzer to the mutational spectrum of each participant. (C) Pathway-level comparison of mutation frequency between four cohorts: intrinsic ( n = 18), acquired ( n = 8), pre-TKI ( n = 55), and post-TKI ( n = 30). Pathways were included if they possessed at least one mutation. There were no significant differences in pathway-level mutation frequency between cohorts (Fisher’s exact test).
    Figure Legend Snippet: Study design for patient cohorts and genomic analyses (A) Initial study criteria with study design based on sample availability and treatment timing. After whole-exome sequencing, PhylogicNDT and SignatureAnalyzer were used to identify clones and compare mutational signatures, respectively. Functional mutations were characterized based on existing evidence previously published or annotated in genomic databases, such as COSMIC, ClinVar, and OncoKB. (B) Signaling pathway landscape for paired-cohort participants ( n = 26) organized by time on tyrosine kinase treatment (days by sampled TKI) and acquired ( n = 8) or intrinsic ( n = 18) resistance. Known mechanisms in ERBB2 and PIK3CA are highlighted. Signaling pathways are depicted in decreasing frequency per number of mutations for the entire cohort of paired participants. Arrows indicate the subclonal trajectory as either growing, stable, or shrinking. The TP53 and ESR1+ regulator pathways were significantly mutated ( q < 0.05; MutSig, Fisher’s method). Stacked bar charts indicate relative contributions of mutational signatures identified by SignatureAnalyzer to the mutational spectrum of each participant. (C) Pathway-level comparison of mutation frequency between four cohorts: intrinsic ( n = 18), acquired ( n = 8), pre-TKI ( n = 55), and post-TKI ( n = 30). Pathways were included if they possessed at least one mutation. There were no significant differences in pathway-level mutation frequency between cohorts (Fisher’s exact test).

    Techniques Used: Sequencing, Clone Assay, Functional Assay, Protein-Protein interactions, Comparison, Mutagenesis

    Related Articles

    Sequencing:

    Article Title: Eosinophilic Biliary Cystic Neoplasm of the Liver: A Case Report of an Unrecognized Subtype of Intrahepatic Biliary Neoplasm
    Article Snippet: .. To characterize genomic alterations, whole‐exome sequencing (WES) and RNA sequencing were performed: somatic variants were identified using MuTect2 (GATK, Broad Institute) and annotated with ANNOVAR (Data ). ..

    Article Title: A Homozygous Nonsense Variant in the Oligosaccharyltransferase Complex Gene, RPN1, Causes a Congenital Disorder of Glycosylation.
    Article Snippet: .. Whole exome sequencing was performed at the Broad Institute using an Agilent Sure-Select Human All Exon v2.0 capture kit and sequenced on an Illumina HiSeq2000 sequencer. ..

    RNA Sequencing:

    Article Title: Eosinophilic Biliary Cystic Neoplasm of the Liver: A Case Report of an Unrecognized Subtype of Intrahepatic Biliary Neoplasm
    Article Snippet: .. To characterize genomic alterations, whole‐exome sequencing (WES) and RNA sequencing were performed: somatic variants were identified using MuTect2 (GATK, Broad Institute) and annotated with ANNOVAR (Data ). ..

    other:

    Article Title: Early differential impact of MeCP2 mutations on functional networks in Rett syndrome patient-derived human cortical organoids.
    Article Snippet: Another Rett syndrome patient-derived hiPS cell line, which carries the heterozygous MECP2[R306C] mutation (female, 8Y, missense; 4–7% of RTT patients), and its isogenic control was obtained from the Coriell Institute (WIC05i-127-325(MT) and WIC04i-12733(WT)).

    Article Title: Immunoregulatory gene GIMAP6 suppresses lethal atherosclerotic vasculopathy and ischemic heart failure.
    Article Snippet: REAGENT or RESOURCE SOURCE IDENTIFIER Poly-L-lysine solution Sigma-Aldrich Cat# P8920 FORANE (isoflurane, USP) Baxter Cat# 1001936060 High-fat diet, 40% kcal fat, 1.25% cholesterol Research Diets Cat# D12108C Critical commercial assays Mouse Cardiac Troponin-I ELISA Kit MyBioSource Cat# MBS766175 Masson’s Trichrome Stain Kit VitroView Cat# VB-3016 RNeasy Plus Mini Kit Qiagen Cat# 74136 SG Cell Line 4D-Nucleofector X Kit L Lonza Cat# V4XC-3012 P3 Primary Cell 4D-Nucleofector X Kit S Lonza Cat# V4XP-3032 Cholesterol E CHOD-DAOS Method Kit FUJIFILM Wako Cat# 999-02601 L-Type Triglyceride M GPO-HMMPS Method Kit FUJIFILM Wako Cat# 994-02891 In Vitro Vascular Permeability Assay, 96-well Millipore/Merck Cat# ECM642 GeniePlex Mouse Inflammation 5-Plex Panel 1 Assay Genie Cat# MOAMPM016 Seahorse XF Cell Mito Stress Test Kit Agilent Cat# 103015-100 Deposited data International Mouse Phenotyping Consortium IMPC MP:0000274 CZ CELLxGENE Discover Chan Zuckerberg Initiative https://cellxgene.cziscience.com/gene- expression scRNA-seq dataset of human thoracic aorta Pirruccello et al.76 SCP1265 scRNA-seq dataset of mouse aorta Kalluri et al.77 SCP289 scRNA-seq dataset of mouse heart Hu et al.78 SCP283 scRNA-seq dataset of carotid plaques SICOF portal Mocci et al.43; https://sicof.medh.ki.se/ athero/carotid/index.html Multi-tissue transcriptomic, eQTL, and GRN dataset from CAD patients STARNET portal Koplev et al.41; http://starnet.mssm.edu/ RNA-seq dataset of Gimap6-deficient BMDMs This paper GEO: GSE307778 RNA-seq dataset of Gimap6-deficient Aortae This paper GEO: GSE335627 CAD-stage-specific monocyte RNA-seq dataset Wang et al.42 GEO: GSE166780 Mouse AEC sex-comparison RNA-seq dataset Shin et al.49 GEO: GSE247364 GTEx Analysis Release v10 GTEx Portal dbGaP: phs000424.v10.p2 Pt 1 and Pt 1’s family Whole-exome sequencing (WES) Yao et al.15 dbGaP: phs002816.v1.p1 ImmGen expression dataset Immunological Genome Project https://www.immgen.org/ CADD v1.7 Schubach et al.79 https://cadd.gs.washington.edu/ gnomAD v4.1.0 Broad Institute https://gnomad.broadinstitute.org/ GIMAP6 ASCVD All of Us analysis code This paper https://github.com/xiangchennih-25/ GIMAP6_CVD_Analysis-; Zenodo: 10.5281/ zenodo.17100995 All of Us Controlled Tier Dataset v8 All of Us Research Program Researcher Workbench All of Us Controlled Tier Dataset C2024Q3R5 All of Us Research Program Researcher Workbench (Continued on next page) Cell 189, 6792–6809.e1–e21, October 15, 2026 e4

    Whole-Exome Sequencing:

    Article Title: A homozygous nonsense variant in the oligosaccharyltransferase complex gene, RPN1 , causes a congenital disorder of glycosylation
    Article Snippet: .. Whole-exome sequencing (WES) was performed at the Broad Institute using an Agilent Sure-Select Human All Exon v.2.0 capture kit and sequenced on an Illumina HiSeq2000 sequencer. ..



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    Image Search Results


    Study design for patient cohorts and genomic analyses (A) Initial study criteria with study design based on sample availability and treatment timing. After whole-exome sequencing, PhylogicNDT and SignatureAnalyzer were used to identify clones and compare mutational signatures, respectively. Functional mutations were characterized based on existing evidence previously published or annotated in genomic databases, such as COSMIC, ClinVar, and OncoKB. (B) Signaling pathway landscape for paired-cohort participants ( n = 26) organized by time on tyrosine kinase treatment (days by sampled TKI) and acquired ( n = 8) or intrinsic ( n = 18) resistance. Known mechanisms in ERBB2 and PIK3CA are highlighted. Signaling pathways are depicted in decreasing frequency per number of mutations for the entire cohort of paired participants. Arrows indicate the subclonal trajectory as either growing, stable, or shrinking. The TP53 and ESR1+ regulator pathways were significantly mutated ( q < 0.05; MutSig, Fisher’s method). Stacked bar charts indicate relative contributions of mutational signatures identified by SignatureAnalyzer to the mutational spectrum of each participant. (C) Pathway-level comparison of mutation frequency between four cohorts: intrinsic ( n = 18), acquired ( n = 8), pre-TKI ( n = 55), and post-TKI ( n = 30). Pathways were included if they possessed at least one mutation. There were no significant differences in pathway-level mutation frequency between cohorts (Fisher’s exact test).

    Journal: Cell Genomics

    Article Title: Detection of heterogeneous resistance mechanisms to tyrosine kinase inhibitors from cell-free DNA

    doi: 10.1016/j.xgen.2025.100987

    Figure Lengend Snippet: Study design for patient cohorts and genomic analyses (A) Initial study criteria with study design based on sample availability and treatment timing. After whole-exome sequencing, PhylogicNDT and SignatureAnalyzer were used to identify clones and compare mutational signatures, respectively. Functional mutations were characterized based on existing evidence previously published or annotated in genomic databases, such as COSMIC, ClinVar, and OncoKB. (B) Signaling pathway landscape for paired-cohort participants ( n = 26) organized by time on tyrosine kinase treatment (days by sampled TKI) and acquired ( n = 8) or intrinsic ( n = 18) resistance. Known mechanisms in ERBB2 and PIK3CA are highlighted. Signaling pathways are depicted in decreasing frequency per number of mutations for the entire cohort of paired participants. Arrows indicate the subclonal trajectory as either growing, stable, or shrinking. The TP53 and ESR1+ regulator pathways were significantly mutated ( q < 0.05; MutSig, Fisher’s method). Stacked bar charts indicate relative contributions of mutational signatures identified by SignatureAnalyzer to the mutational spectrum of each participant. (C) Pathway-level comparison of mutation frequency between four cohorts: intrinsic ( n = 18), acquired ( n = 8), pre-TKI ( n = 55), and post-TKI ( n = 30). Pathways were included if they possessed at least one mutation. There were no significant differences in pathway-level mutation frequency between cohorts (Fisher’s exact test).

    Article Snippet: The remainder of our genomic analysis relied on whole exome sequencing (WES) data generated by the Broad Institute Genomics Platform.

    Techniques: Sequencing, Clone Assay, Functional Assay, Protein-Protein interactions, Comparison, Mutagenesis