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Differential gene expression analysis tools exhibit substandard performance for long non-coding RNA-sequencing data

(2018) Genome Biology. 19(1).
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Keywords
RNA-seq, mRNA, lncRNA, Differential gene expression

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Citation

Please use this url to cite or link to this publication:

Chicago
Assefa, Alemu Takele, Katrijn De Paepe, Celine Everaert, Pieter Mestdagh, Olivier Thas, and Jo Vandesompele. 2018. “Differential Gene Expression Analysis Tools Exhibit Substandard Performance for Long Non-coding RNA-sequencing Data.” Genome Biology 19 (1).
APA
Assefa, A. T., De Paepe, K., Everaert, C., Mestdagh, P., Thas, O., & Vandesompele, J. (2018). Differential gene expression analysis tools exhibit substandard performance for long non-coding RNA-sequencing data. Genome Biology, 19(1).
Vancouver
1.
Assefa AT, De Paepe K, Everaert C, Mestdagh P, Thas O, Vandesompele J. Differential gene expression analysis tools exhibit substandard performance for long non-coding RNA-sequencing data. Genome Biology. Springer Nature; 2018;19(1).
MLA
Assefa, Alemu Takele et al. “Differential Gene Expression Analysis Tools Exhibit Substandard Performance for Long Non-coding RNA-sequencing Data.” Genome Biology 19.1 (2018): n. pag. Print.
@article{8599289,
  author       = {Assefa, Alemu Takele and De Paepe, Katrijn and Everaert, Celine and Mestdagh, Pieter and Thas, Olivier and Vandesompele, Jo},
  issn         = {1474-760X},
  journal      = {Genome Biology},
  number       = {1},
  publisher    = {Springer Nature},
  title        = {Differential gene expression analysis tools exhibit substandard performance for long non-coding RNA-sequencing data},
  url          = {http://dx.doi.org/10.1186/s13059-018-1466-5},
  volume       = {19},
  year         = {2018},
}

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