@article{fdi:010079857,
  title = {{TIP}_finder : an {HPC} software to detect transposable element insertion polymorphisms in large genomic datasets},
  author = {{O}rozco-{A}rias, {S}. and {T}obon-{O}rozco, {N}. and {P}ina, {J}. {S}. and {J}imenez-{V}aron, {C}. {F}. and {T}abares-{S}oto, {R}. and {G}uyot, {R}omain},
  editor = {},
  language = {{ENG}},
  abstract = {{T}ransposable elements ({TE}s) are non-static genomic units capable of moving indistinctly from one chromosomal location to another. {T}heir insertion polymorphisms may cause beneficial mutations, such as the creation of new gene function, or deleterious in eukaryotes, e.g., different types of cancer in humans. {A} particular type of {TE} called {LTR}-retrotransposons comprises almost 8% of the human genome. {A}mong {LTR} retrotransposons, human endogenous retroviruses ({HERV}s) bear structural and functional similarities to retroviruses. {S}everal tools allow the detection of transposon insertion polymorphisms ({TIP}s) but fail to efficiently analyze large genomes or large datasets. {H}ere, we developed a computational tool, named {TIP}_finder, able to detect mobile element insertions in very large genomes, through high-performance computing ({HPC}) and parallel programming, using the inference of discordant read pair analysis. {TIP}_finder inputs are (i) short pair reads such as those obtained by {I}llumina, (ii) a chromosome-level reference genome sequence, and (iii) a database of consensus {TE} sequences. {T}he {HPC} strategy we propose adds scalability and provides a useful tool to analyze huge genomic datasets in a decent running time. {TIP}_finder accelerates the detection of transposon insertion polymorphisms ({TIP}s) by up to 55 times in breast cancer datasets and 46 times in cancer-free datasets compared to the fastest available algorithms. {TIP}_finder applies a validated strategy to find {TIP}s, accelerates the process through {HPC}, and addresses the issues of runtime for large-scale analyses in the post-genomic era.},
  keywords = {{TIP}_finder ; bioinformatics ; {HPC} ; parallel programming ; polymorphism ; {HERV} ; post-genomic era ; {TIP}s},
  booktitle = {},
  journal = {{B}iology},
  volume = {9},
  numero = {9},
  pages = {281 [17 p.]},
  year = {2020},
  DOI = {10.3390/biology9090281},
  URL = {https://www.documentation.ird.fr/hor/fdi:010079857},
}