379 related articles for article (PubMed ID: 26539496)
1. 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]
2. 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]
3. 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]
4. 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]
5. 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]
6. Optimized detection of insertions/deletions (INDELs) in whole-exome sequencing data.
Kim BY; Park JH; Jo HY; Koo SK; Park MH
PLoS One; 2017; 12(8):e0182272. PubMed ID: 28792971
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. 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]
9. Challenges in exome analysis by LifeScope and its alternative computational pipelines.
Pranckevičiene E; Rančelis T; Pranculis A; Kučinskas V
BMC Res Notes; 2015 Sep; 8():421. PubMed ID: 26346699
[TBL] [Abstract][Full Text] [Related]
10. From Wet-Lab to Variations: Concordance and Speed of Bioinformatics Pipelines for Whole Genome and Whole Exome Sequencing.
Laurie S; Fernandez-Callejo M; Marco-Sola S; Trotta JR; Camps J; Chacón A; Espinosa A; Gut M; Gut I; Heath S; Beltran S
Hum Mutat; 2016 Dec; 37(12):1263-1271. PubMed ID: 27604516
[TBL] [Abstract][Full Text] [Related]
11. An analytical workflow for accurate variant discovery in highly divergent regions.
Tian S; Yan H; Neuhauser C; Slager SL
BMC Genomics; 2016 Sep; 17(1):703. PubMed ID: 27590916
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. 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]
14. 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]
15. 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]
16. A reference data set of 5.4 million phased human variants validated by genetic inheritance from sequencing a three-generation 17-member pedigree.
Eberle MA; Fritzilas E; Krusche P; Källberg M; Moore BL; Bekritsky MA; Iqbal Z; Chuang HY; Humphray SJ; Halpern AL; Kruglyak S; Margulies EH; McVean G; Bentley DR
Genome Res; 2017 Jan; 27(1):157-164. PubMed ID: 27903644
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Comparison of calling pipelines for whole genome sequencing: an empirical study demonstrating the importance of mapping and alignment.
Betschart RO; Thiéry A; Aguilera-Garcia D; Zoche M; Moch H; Twerenbold R; Zeller T; Blankenberg S; Ziegler A
Sci Rep; 2022 Dec; 12(1):21502. PubMed ID: 36513709
[TBL] [Abstract][Full Text] [Related]
19. Benchmarking workflows to assess performance and suitability of germline variant calling pipelines in clinical diagnostic assays.
Krishnan V; Utiramerur S; Ng Z; Datta S; Snyder MP; Ashley EA
BMC Bioinformatics; 2021 Feb; 22(1):85. PubMed ID: 33627090
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]