346 related articles for article (PubMed ID: 35176018)
1. Tool evaluation for the detection of variably sized indels from next generation whole genome and targeted sequencing data.
Wang N; Lysenkov V; Orte K; Kairisto V; Aakko J; Khan S; Elo LL
PLoS Comput Biol; 2022 Feb; 18(2):e1009269. PubMed ID: 35176018
[TBL] [Abstract][Full Text] [Related]
2. 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]
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. Comparison of INDEL Calling Tools with Simulation Data and Real Short-Read Data.
Li D; Kim W; Wang L; Yoon KA; Park B; Park C; Kong SY; Hwang Y; Baek D; Lee ES; Won S
IEEE/ACM Trans Comput Biol Bioinform; 2019; 16(5):1635-1644. PubMed ID: 30004886
[TBL] [Abstract][Full Text] [Related]
5. Performance comparison of whole-genome sequencing platforms.
Lam HY; Clark MJ; Chen R; Chen R; Natsoulis G; O'Huallachain M; Dewey FE; Habegger L; Ashley EA; Gerstein MB; Butte AJ; Ji HP; Snyder M
Nat Biotechnol; 2011 Dec; 30(1):78-82. PubMed ID: 22178993
[TBL] [Abstract][Full Text] [Related]
6. INDELseek: detection of complex insertions and deletions from next-generation sequencing data.
Au CH; Leung AY; Kwong A; Chan TL; Ma ES
BMC Genomics; 2017 Jan; 18(1):16. PubMed ID: 28056804
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Systematic comparison of germline variant calling pipelines cross multiple next-generation sequencers.
Chen J; Li X; Zhong H; Meng Y; Du H
Sci Rep; 2019 Jun; 9(1):9345. PubMed ID: 31249349
[TBL] [Abstract][Full Text] [Related]
9. mInDel: a high-throughput and efficient pipeline for genome-wide InDel marker development.
Lv Y; Liu Y; Zhao H
BMC Genomics; 2016 Apr; 17():290. PubMed ID: 27079510
[TBL] [Abstract][Full Text] [Related]
10. Indel detection from RNA-seq data: tool evaluation and strategies for accurate detection of actionable mutations.
Sun Z; Bhagwate A; Prodduturi N; Yang P; Kocher JA
Brief Bioinform; 2017 Nov; 18(6):973-983. PubMed ID: 27473065
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Bioinformatics Basics for High-Throughput Hybridization-Based Targeted DNA Sequencing from FFPE-Derived Tumor Specimens: From Reads to Variants.
Sun S; Murray SS
Methods Mol Biol; 2019; 1908():37-48. PubMed ID: 30649719
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. 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]
15. 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]
16. Performance evaluation of indel calling tools using real short-read data.
Hasan MS; Wu X; Zhang L
Hum Genomics; 2015 Aug; 9(1):20. PubMed ID: 26286629
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. The challenge of detecting indels in bacterial genomes from short-read sequencing data.
Steglich M; Nübel U
J Biotechnol; 2017 May; 250():11-15. PubMed ID: 28267569
[TBL] [Abstract][Full Text] [Related]
19. SMaSH: a benchmarking toolkit for human genome variant calling.
Talwalkar A; Liptrap J; Newcomb J; Hartl C; Terhorst J; Curtis K; Bresler M; Song YS; Jordan MI; Patterson D
Bioinformatics; 2014 Oct; 30(19):2787-95. PubMed ID: 24894505
[TBL] [Abstract][Full Text] [Related]
20. Comparative assessments of indel annotations in healthy and cancer genomes with next-generation sequencing data.
Chen J; Guo JT
BMC Med Genomics; 2020 Nov; 13(1):170. PubMed ID: 33167946
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
