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amniotic fluid clinical whole exome sequencing data qi guo  (Chongqing Key)

 
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    Chongqing Key amniotic fluid clinical whole exome sequencing data qi guo
    Amniotic Fluid Clinical Whole Exome Sequencing Data Qi Guo, supplied by Chongqing Key, 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/exome+sequence+data/amniotic+clinical+data+exome+fluid+guo+qi+sequencing+whole/pm41519313-12-11-75
    Average 86 stars, based on 1 article reviews
    amniotic fluid clinical whole exome sequencing data qi guo - by Bioz Stars, 2026-11
    86/100 stars

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    Biomarker Discovery:

    Article Title: Evaluation of CNV detection tools for prenatal diagnosis using amniotic fluid clinical whole-exome sequencing data.
    Article Snippet: .. Research Paper Evaluation of CNV detection tools for prenatal diagnosis using amniotic fluid clinical whole-exome sequencing data Qi Guo a,b,1, Yue Zhang a,b,1, Xin Gui a,b, Lijuan Zhong a,b, Rong Zhong a,b, Yan Jiang a,b,*, Hongbo Qi c,** a Department of Prenatal Diagnosis Center, Women and Children's Hospital of Chongqing Medical University, China b Department of Prenatal Diagnosis Center, Chongqing Health Center for Women and Children, Chongqing 401147, China c Department of Obstetrics and Gynecology, Chongqing Key Laboratory of Maternal and Fetal Medicine/Joint International Research Laboratory of Reproduction & Development, Ministry of Education/The Innovation and Talent Recruitment Base of Maternal-Fetal Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China A R T I C L E I N F O Keywords: Amniotic fluid Bioinformatics tools Copy number variation Prenatal diagnosis Clinical whole exome sequencing A B S T R A C T Background: Copy number variations (CNVs) are significant contributors to genetic disorders, making their accurate detection crucial for prenatal diagnosis. ..

    Sequencing:

    Article Title: Evaluation of CNV detection tools for prenatal diagnosis using amniotic fluid clinical whole-exome sequencing data.
    Article Snippet: .. Research Paper Evaluation of CNV detection tools for prenatal diagnosis using amniotic fluid clinical whole-exome sequencing data Qi Guo a,b,1, Yue Zhang a,b,1, Xin Gui a,b, Lijuan Zhong a,b, Rong Zhong a,b, Yan Jiang a,b,*, Hongbo Qi c,** a Department of Prenatal Diagnosis Center, Women and Children's Hospital of Chongqing Medical University, China b Department of Prenatal Diagnosis Center, Chongqing Health Center for Women and Children, Chongqing 401147, China c Department of Obstetrics and Gynecology, Chongqing Key Laboratory of Maternal and Fetal Medicine/Joint International Research Laboratory of Reproduction & Development, Ministry of Education/The Innovation and Talent Recruitment Base of Maternal-Fetal Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China A R T I C L E I N F O Keywords: Amniotic fluid Bioinformatics tools Copy number variation Prenatal diagnosis Clinical whole exome sequencing A B S T R A C T Background: Copy number variations (CNVs) are significant contributors to genetic disorders, making their accurate detection crucial for prenatal diagnosis. ..



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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