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Bioinformatic Pipelines to Analyze lncRNAs RNAseq Data.
Agnelli, Luca; Bortoluzzi, Stefania; Pruneri, Giancarlo.
Affiliation
  • Agnelli L; Department of Pathology, IRCCS Istituto Nazionale dei Tumori, Milan, Italy. luca.agnelli@istitutotumori.mi.it.
  • Bortoluzzi S; Department of Oncology and Hemato-oncology, University of Milan, Milan, Italy. luca.agnelli@istitutotumori.mi.it.
  • Pruneri G; Department of Molecular Medicine, University of Padova, Padova, Italy.
Methods Mol Biol ; 2348: 55-69, 2021.
Article in En | MEDLINE | ID: mdl-34160799
ABSTRACT
RNA-sequencing could be nowadays considered the gold standard to study the coding and noncoding transcriptome. The great advantage of high-throughput sequencing in the characterization and quantification of long noncoding RNA (lncRNA) resides in its capability to capture the complexity of lncRNA transcripts configuration patterns, even in the presence of several alternative isoforms, with superior accuracy and discovery power compared to other technologies such as microarrays or PCR-based methods. In this chapter, we provide a protocol for lncRNA analysis using through high-throughput sequencing, indicating the main difficulties in the annotation pipeline and showing how an accurate evaluation of the procedure can help to minimize biased observations.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Sequence Analysis, RNA / Computational Biology / Gene Expression Profiling / Transcriptome / RNA, Long Noncoding Language: En Journal: Methods Mol Biol Year: 2021 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Sequence Analysis, RNA / Computational Biology / Gene Expression Profiling / Transcriptome / RNA, Long Noncoding Language: En Journal: Methods Mol Biol Year: 2021 Document type: Article