329 related articles for article (PubMed ID: 22084253)
1. Feature-based classifiers for somatic mutation detection in tumour-normal paired sequencing data.
Ding J; Bashashati A; Roth A; Oloumi A; Tse K; Zeng T; Haffari G; Hirst M; Marra MA; Condon A; Aparicio S; Shah SP
Bioinformatics; 2012 Jan; 28(2):167-75. PubMed ID: 22084253
[TBL] [Abstract][Full Text] [Related]
2. JointSNVMix: a probabilistic model for accurate detection of somatic mutations in normal/tumour paired next-generation sequencing data.
Roth A; Ding J; Morin R; Crisan A; Ha G; Giuliany R; Bashashati A; Hirst M; Turashvili G; Oloumi A; Marra MA; Aparicio S; Shah SP
Bioinformatics; 2012 Apr; 28(7):907-13. PubMed ID: 22285562
[TBL] [Abstract][Full Text] [Related]
3. Machine learning random forest for predicting oncosomatic variant NGS analysis.
Pellegrino E; Jacques C; Beaufils N; Nanni I; Carlioz A; Metellus P; Ouafik L
Sci Rep; 2021 Nov; 11(1):21820. PubMed ID: 34750410
[TBL] [Abstract][Full Text] [Related]
4. SNooPer: a machine learning-based method for somatic variant identification from low-pass next-generation sequencing.
Spinella JF; Mehanna P; Vidal R; Saillour V; Cassart P; Richer C; Ouimet M; Healy J; Sinnett D
BMC Genomics; 2016 Nov; 17(1):912. PubMed ID: 27842494
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. SNVMix: predicting single nucleotide variants from next-generation sequencing of tumors.
Goya R; Sun MG; Morin RD; Leung G; Ha G; Wiegand KC; Senz J; Crisan A; Marra MA; Hirst M; Huntsman D; Murphy KP; Aparicio S; Shah SP
Bioinformatics; 2010 Mar; 26(6):730-6. PubMed ID: 20130035
[TBL] [Abstract][Full Text] [Related]
7. A comparative analysis of algorithms for somatic SNV detection in cancer.
Roberts ND; Kortschak RD; Parker WT; Schreiber AW; Branford S; Scott HS; Glonek G; Adelson DL
Bioinformatics; 2013 Sep; 29(18):2223-30. PubMed ID: 23842810
[TBL] [Abstract][Full Text] [Related]
8. Germline contamination and leakage in whole genome somatic single nucleotide variant detection.
Sendorek DH; Caloian C; Ellrott K; Bare JC; Yamaguchi TN; Ewing AD; Houlahan KE; Norman TC; Margolin AA; Stuart JM; Boutros PC
BMC Bioinformatics; 2018 Jan; 19(1):28. PubMed ID: 29385983
[TBL] [Abstract][Full Text] [Related]
9. A novel machine learning approach (svmSomatic) to distinguish somatic and germline mutations using next-generation sequencing data.
Mao YF; Yuan XG; Cun YP
Zool Res; 2021 Mar; 42(2):246-249. PubMed ID: 33709636
[TBL] [Abstract][Full Text] [Related]
10. MosaicHunter: accurate detection of postzygotic single-nucleotide mosaicism through next-generation sequencing of unpaired, trio, and paired samples.
Huang AY; Zhang Z; Ye AY; Dou Y; Yan L; Yang X; Zhang Y; Wei L
Nucleic Acids Res; 2017 Jun; 45(10):e76. PubMed ID: 28132024
[TBL] [Abstract][Full Text] [Related]
11. A gradient-boosting approach for filtering de novo mutations in parent-offspring trios.
Liu Y; Li B; Tan R; Zhu X; Wang Y
Bioinformatics; 2014 Jul; 30(13):1830-6. PubMed ID: 24618463
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. 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]
14. 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]
15. MAC-ErrorReads: machine learning-assisted classifier for filtering erroneous NGS reads.
Sami A; El-Metwally S; Rashad MZ
BMC Bioinformatics; 2024 Feb; 25(1):61. PubMed ID: 38321434
[TBL] [Abstract][Full Text] [Related]
16. Mutation discovery in regions of segmental cancer genome amplifications with CoNAn-SNV: a mixture model for next generation sequencing of tumors.
Crisan A; Goya R; Ha G; Ding J; Prentice LM; Oloumi A; Senz J; Zeng T; Tse K; Delaney A; Marra MA; Huntsman DG; Hirst M; Aparicio S; Shah S
PLoS One; 2012; 7(8):e41551. PubMed ID: 22916110
[TBL] [Abstract][Full Text] [Related]
17. Ensemble-Based Somatic Mutation Calling in Cancer Genomes.
Huang W; Guo YA; Chang MM; Skanderup AJ
Methods Mol Biol; 2020; 2120():37-46. PubMed ID: 32124310
[TBL] [Abstract][Full Text] [Related]
18. BAYSIC: a Bayesian method for combining sets of genome variants with improved specificity and sensitivity.
Cantarel BL; Weaver D; McNeill N; Zhang J; Mackey AJ; Reese J
BMC Bioinformatics; 2014 Apr; 15():104. PubMed ID: 24725768
[TBL] [Abstract][Full Text] [Related]
19. Machine Learning-Based Method for Obesity Risk Evaluation Using Single-Nucleotide Polymorphisms Derived from Next-Generation Sequencing.
Wang HY; Chang SC; Lin WY; Chen CH; Chiang SH; Huang KY; Chu BY; Lu JJ; Lee TY
J Comput Biol; 2018 Dec; 25(12):1347-1360. PubMed ID: 30204480
[TBL] [Abstract][Full Text] [Related]
20. Accurate Ensemble Prediction of Somatic Mutations with SMuRF2.
Huang W; Sim NL; Skanderup AJ
Methods Mol Biol; 2022; 2493():53-66. PubMed ID: 35751808
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
