These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

181 related articles for article (PubMed ID: 36114280)

  • 1. FVC as an adaptive and accurate method for filtering variants from popular NGS analysis pipelines.
    Ren Y; Kong Y; Zhou X; Genchev GZ; Zhou C; Zhao H; Lu H
    Commun Biol; 2022 Sep; 5(1):975. PubMed ID: 36114280
    [TBL] [Abstract][Full Text] [Related]  

  • 2. VEF: a variant filtering tool based on ensemble methods.
    Zhang C; Ochoa I
    Bioinformatics; 2020 Apr; 36(8):2328-2336. PubMed ID: 31873730
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Variant callers for next-generation sequencing data: a comparison study.
    Liu X; Han S; Wang Z; Gelernter J; Yang BZ
    PLoS One; 2013; 8(9):e75619. PubMed ID: 24086590
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Comparison of GATK and DeepVariant by trio sequencing.
    Lin YL; Chang PC; Hsu C; Hung MZ; Chien YH; Hwu WL; Lai F; Lee NC
    Sci Rep; 2022 Feb; 12(1):1809. PubMed ID: 35110657
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Benchmarking variant callers in next-generation and third-generation sequencing analysis.
    Pei S; Liu T; Ren X; Li W; Chen C; Xie Z
    Brief Bioinform; 2021 May; 22(3):. PubMed ID: 32698196
    [TBL] [Abstract][Full Text] [Related]  

  • 6. VariantMetaCaller: automated fusion of variant calling pipelines for quantitative, precision-based filtering.
    Gézsi A; Bolgár B; Marx P; Sarkozy P; Szalai C; Antal P
    BMC Genomics; 2015 Oct; 16():875. PubMed ID: 26510841
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Systematic benchmark of state-of-the-art variant calling pipelines identifies major factors affecting accuracy of coding sequence variant discovery.
    Barbitoff YA; Abasov R; Tvorogova VE; Glotov AS; Predeus AV
    BMC Genomics; 2022 Feb; 23(1):155. PubMed ID: 35193511
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Detailed simulation of cancer exome sequencing data reveals differences and common limitations of variant callers.
    Hofmann AL; Behr J; Singer J; Kuipers J; Beisel C; Schraml P; Moch H; Beerenwinkel N
    BMC Bioinformatics; 2017 Jan; 18(1):8. PubMed ID: 28049408
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Validation and assessment of variant calling pipelines for next-generation sequencing.
    Pirooznia M; Kramer M; Parla J; Goes FS; Potash JB; McCombie WR; Zandi PP
    Hum Genomics; 2014 Jul; 8(1):14. PubMed ID: 25078893
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A Comparison of Variant Calling Pipelines Using Genome in a Bottle as a Reference.
    Cornish A; Guda C
    Biomed Res Int; 2015; 2015():456479. PubMed ID: 26539496
    [TBL] [Abstract][Full Text] [Related]  

  • 11. VariFAST: a variant filter by automated scoring based on tagged-signatures.
    Zhang H; Wang K; Zhou J; Chen J; Xu Y; Wang D; Li X; Sun R; Zhang M; Wang Z; Shi Y
    BMC Bioinformatics; 2019 Dec; 20(Suppl 22):713. PubMed ID: 31888441
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Performance assessment of variant calling pipelines using human whole exome sequencing and simulated data.
    Kumaran M; Subramanian U; Devarajan B
    BMC Bioinformatics; 2019 Jun; 20(1):342. PubMed ID: 31208315
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Detailed comparison of two popular variant calling packages for exome and targeted exon studies.
    Warden CD; Adamson AW; Neuhausen SL; Wu X
    PeerJ; 2014; 2():e600. PubMed ID: 25289185
    [TBL] [Abstract][Full Text] [Related]  

  • 14. An efficient and tunable parameter to improve variant calling for whole genome and exome sequencing data.
    Ahn YJ; Markkandan K; Baek IP; Mun S; Lee W; Kim HS; Han K
    Genes Genomics; 2018 Jan; 40(1):39-47. PubMed ID: 29892897
    [TBL] [Abstract][Full Text] [Related]  

  • 15. GATK hard filtering: tunable parameters to improve variant calling for next generation sequencing targeted gene panel data.
    De Summa S; Malerba G; Pinto R; Mori A; Mijatovic V; Tommasi S
    BMC Bioinformatics; 2017 Mar; 18(Suppl 5):119. PubMed ID: 28361668
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Performance evaluation of pipelines for mapping, variant calling and interval padding, for the analysis of NGS germline panels.
    Zanti M; Michailidou K; Loizidou MA; Machattou C; Pirpa P; Christodoulou K; Spyrou GM; Kyriacou K; Hadjisavvas A
    BMC Bioinformatics; 2021 Apr; 22(1):218. PubMed ID: 33910496
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Halvade somatic: Somatic variant calling with Apache Spark.
    Decap D; de Schaetzen van Brienen L; Larmuseau M; Costanza P; Herzeel C; Wuyts R; Marchal K; Fostier J
    Gigascience; 2022 Jan; 11(1):. PubMed ID: 35022699
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Impact of post-alignment processing in variant discovery from whole exome data.
    Tian S; Yan H; Kalmbach M; Slager SL
    BMC Bioinformatics; 2016 Oct; 17(1):403. PubMed ID: 27716037
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Systematic comparison of variant calling pipelines using gold standard personal exome variants.
    Hwang S; Kim E; Lee I; Marcotte EM
    Sci Rep; 2015 Dec; 5():17875. PubMed ID: 26639839
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Optimized pipeline of MuTect and GATK tools to improve the detection of somatic single nucleotide polymorphisms in whole-exome sequencing data.
    do Valle ÍF; Giampieri E; Simonetti G; Padella A; Manfrini M; Ferrari A; Papayannidis C; Zironi I; Garonzi M; Bernardi S; Delledonne M; Martinelli G; Remondini D; Castellani G
    BMC Bioinformatics; 2016 Nov; 17(Suppl 12):341. PubMed ID: 28185561
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.