BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

126 related articles for article (PubMed ID: 37963064)

  • 1. EMVC-2: an efficient single-nucleotide variant caller based on expectation maximization.
    Dufort Y Álvarez G; Xargay-Ferrer M; Pagès-Zamora A; Ochoa I
    Bioinformatics; 2024 Mar; 40(3):. PubMed ID: 37963064
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Using genotype array data to compare multi- and single-sample variant calls and improve variant call sets from deep coverage whole-genome sequencing data.
    Shringarpure SS; Mathias RA; Hernandez RD; O'Connor TD; Szpiech ZA; Torres R; De La Vega FM; Bustamante CD; Barnes KC; Taub MA;
    Bioinformatics; 2017 Apr; 33(8):1147-1153. PubMed ID: 28035032
    [TBL] [Abstract][Full Text] [Related]  

  • 3. SNVSniffer: an integrated caller for germline and somatic single-nucleotide and indel mutations.
    Liu Y; Loewer M; Aluru S; Schmidt B
    BMC Syst Biol; 2016 Aug; 10 Suppl 2(Suppl 2):47. PubMed ID: 27489955
    [TBL] [Abstract][Full Text] [Related]  

  • 4. SECEDO: SNV-based subclone detection using ultra-low coverage single-cell DNA sequencing.
    Rozhoňová H; Danciu D; Stark S; Rätsch G; Kahles A; Lehmann KV
    Bioinformatics; 2022 Sep; 38(18):4293-4300. PubMed ID: 35900151
    [TBL] [Abstract][Full Text] [Related]  

  • 5. PhredEM: a phred-score-informed genotype-calling approach for next-generation sequencing studies.
    Liao P; Satten GA; Hu YJ
    Genet Epidemiol; 2017 Jul; 41(5):375-387. PubMed ID: 28560825
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Identification of single nucleotide variants using position-specific error estimation in deep sequencing data.
    Kleftogiannis D; Punta M; Jayaram A; Sandhu S; Wong SQ; Gasi Tandefelt D; Conteduca V; Wetterskog D; Attard G; Lise S
    BMC Med Genomics; 2019 Aug; 12(1):115. PubMed ID: 31375105
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Comparing the performance of selected variant callers using synthetic data and genome segmentation.
    Bian X; Zhu B; Wang M; Hu Y; Chen Q; Nguyen C; Hicks B; Meerzaman D
    BMC Bioinformatics; 2018 Nov; 19(1):429. PubMed ID: 30453880
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Evaluating the Calling Performance of a Rare Disease NGS Panel for Single Nucleotide and Copy Number Variants.
    Cacheiro P; Ordóñez-Ugalde A; Quintáns B; Piñeiro-Hermida S; Amigo J; García-Murias M; Pascual-Pascual SI; Grandas F; Arpa J; Carracedo A; Sobrido MJ
    Mol Diagn Ther; 2017 Jun; 21(3):303-313. PubMed ID: 28290094
    [TBL] [Abstract][Full Text] [Related]  

  • 9. xAtlas: scalable small variant calling across heterogeneous next-generation sequencing experiments.
    Farek J; Hughes D; Salerno W; Zhu Y; Pisupati A; Mansfield A; Krasheninina O; English AC; Metcalf G; Boerwinkle E; Muzny DM; Gibbs R; Khan Z; Sedlazeck FJ
    Gigascience; 2022 Dec; 12():. PubMed ID: 36644891
    [TBL] [Abstract][Full Text] [Related]  

  • 10. MultiGeMS: detection of SNVs from multiple samples using model selection on high-throughput sequencing data.
    Murillo GH; You N; Su X; Cui W; Reilly MP; Li M; Ning K; Cui X
    Bioinformatics; 2016 May; 32(10):1486-92. PubMed ID: 26787661
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A hybrid computational strategy to address WGS variant analysis in >5000 samples.
    Huang Z; Rustagi N; Veeraraghavan N; Carroll A; Gibbs R; Boerwinkle E; Venkata MG; Yu F
    BMC Bioinformatics; 2016 Sep; 17(1):361. PubMed ID: 27612449
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Consensus Genotyper for Exome Sequencing (CGES): improving the quality of exome variant genotypes.
    Trubetskoy V; Rodriguez A; Dave U; Campbell N; Crawford EL; Cook EH; Sutcliffe JS; Foster I; Madduri R; Cox NJ; Davis LK
    Bioinformatics; 2015 Jan; 31(2):187-93. PubMed ID: 25270638
    [TBL] [Abstract][Full Text] [Related]  

  • 13. STIC: Predicting Single Nucleotide Variants and Tumor Purity in Cancer Genome.
    Yuan X; Ma C; Zhao H; Yang L; Wang S; Xi J
    IEEE/ACM Trans Comput Biol Bioinform; 2021; 18(6):2692-2701. PubMed ID: 32086221
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Phylovar: toward scalable phylogeny-aware inference of single-nucleotide variations from single-cell DNA sequencing data.
    Edrisi M; Valecha MV; Chowdary SBV; Robledo S; Ogilvie HA; Posada D; Zafar H; Nakhleh L
    Bioinformatics; 2022 Jun; 38(Suppl 1):i195-i202. PubMed ID: 35758771
    [TBL] [Abstract][Full Text] [Related]  

  • 15. ReliableGenome: annotation of genomic regions with high/low variant calling concordance.
    Popitsch N; ; Schuh A; Taylor JC
    Bioinformatics; 2017 Jan; 33(2):155-160. PubMed ID: 27605105
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A study on fast calling variants from next-generation sequencing data using decision tree.
    Li Z; Wang Y; Wang F
    BMC Bioinformatics; 2018 Apr; 19(1):145. PubMed ID: 29673316
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Misannotated Multi-Nucleotide Variants in Public Cancer Genomics Datasets Lead to Inaccurate Mutation Calls with Significant Implications.
    Srinivasan S; Kalinava N; Aldana R; Li Z; van Hagen S; Rodenburg SYA; Wind-Rotolo M; Qian X; Sasson AS; Tang H; Kirov S
    Cancer Res; 2021 Jan; 81(2):282-288. PubMed ID: 33115802
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Hidden Markov Models in Bioinformatics: SNV Inference from Next Generation Sequence.
    Bian J; Zhou X
    Methods Mol Biol; 2017; 1552():123-133. PubMed ID: 28224495
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Accuracy and reproducibility of somatic point mutation calling in clinical-type targeted sequencing data.
    Karimnezhad A; Palidwor GA; Thavorn K; Stewart DJ; Campbell PA; Lo B; Perkins TJ
    BMC Med Genomics; 2020 Oct; 13(1):156. PubMed ID: 33059707
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Comparing a few SNP calling algorithms using low-coverage sequencing data.
    Yu X; Sun S
    BMC Bioinformatics; 2013 Sep; 14():274. PubMed ID: 24044377
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.