NOISeq

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start [2013/03/22 18:53]
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start [2015/05/28 14:52]
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-NOISeq is a non-parametric approach for the identification of differentially expressed genes from count data or previously normalized count data. NOISeq empirically models the noise distribution of count changes by contrasting fold-change differences (M) and absolute expression differences (D) for all the features in samples within the same condition. ​+**NOISeq** is a non-parametric approach for the identification of differentially expressed genes from count data or previously normalized count data. NOISeq empirically models the noise distribution of count changes by contrasting fold-change differences (M) and absolute expression differences (D) for all the features in samples within the same condition. ​
 This reference distribution is then used to assess whether the M-D values computed between two conditions for a given gene is likely to be part of the noise or represent a true differential expression. This reference distribution is then used to assess whether the M-D values computed between two conditions for a given gene is likely to be part of the noise or represent a true differential expression.
  
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 Please, find {{:​posternoiseq_2012.pdf|here}} an outline of the NOISeq method. Please, find {{:​posternoiseq_2012.pdf|here}} an outline of the NOISeq method.
  
 +**NOISeqBIO** is the adaptation of NOISeq to handle biological variability. You can find a description of the NOISeqBIO method in this {{:​noiseqbio_techreport.pdf|Technical Report}} and also a summary in this {{:​posternoiseqbio.pdf|poster}}.
  
-A new version of the method is being developed to better handle biological variation. This new version is called NOISeqBIO. 
  
- +Both NOISeq and NOISeqBIO ​are included ​in [[http://​www.bioconductor.org/​packages/​release/​bioc/​html/​NOISeq.html|R/​Bioconductor NOISeq package]] together with a set of graphical tools to assess the quality of sequencing count data.
-Both NOISeq and NOISeqBIO ​have been implemented ​in R language.+