Abstract:
:RNA-Seq is gradually becoming the standard tool for transcriptomic expression studies in biological research. Although considerable progress has been recorded in the development of statistical algorithms for the detection of differentially expressed genes using RNA-Seq data, the list of detected genes can differ significantly between algorithms. We present a new method (PANDORA) that combines multiple algorithms toward a summarized result, more efficiently reflecting true experimental outcomes. This is achieved through the systematic combination of several analysis algorithms, by weighting their outcomes according to their performance with realistically simulated data sets generated from real data. Results supported by the analysis of both simulated and real data from different organisms as well as correlation with PolII occupancy demonstrate that PANDORA improves the detection of differential expression. It accomplishes this by optimizing the tradeoff between standard performance measurements, such as precision and sensitivity.
journal_name
Nucleic Acids Resjournal_title
Nucleic acids researchauthors
Moulos P,Hatzis Pdoi
10.1093/nar/gku1273subject
Has Abstractpub_date
2015-02-27 00:00:00pages
e25issue
4eissn
0305-1048issn
1362-4962pii
gku1273journal_volume
43pub_type
杂志文章abstract::Proteins perform biological functions through cascading interactions with each other by forming protein complexes. As a result, interactions among proteins, called protein-protein interactions (PPIs) are not completely free from selection constraint during evolution. Therefore, the identification and analysis of PPI c...
journal_title:Nucleic acids research
pub_type: 杂志文章
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journal_title:Nucleic acids research
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journal_title:Nucleic acids research
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journal_title:Nucleic acids research
pub_type: 杂志文章
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journal_title:Nucleic acids research
pub_type: 杂志文章
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journal_title:Nucleic acids research
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abstract::The numerous genomic sequences and ESTs released by the Arabidopsis thaliana Genome Initiative (AGI) have allowed a systematic and functional study of the DEAD box RNA helicase family. Sequencing and in silico analysis led to the characterization of 28 novel A. thaliana DEAD box RNA helicases forming a family of 32 me...
journal_title:Nucleic acids research
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journal_title:Nucleic acids research
pub_type: 杂志文章
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journal_title:Nucleic acids research
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journal_title:Nucleic acids research
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journal_title:Nucleic acids research
pub_type: 杂志文章
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journal_title:Nucleic acids research
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journal_title:Nucleic acids research
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journal_title:Nucleic acids research
pub_type: 杂志文章
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更新日期:2011-10-01 00:00:00
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journal_title:Nucleic acids research
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