Differences

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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.
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-A new version of the method is being developed to better handle biological variation. This new version is called NOISeqBIO.
+//**NEW!!!**//\\
+A new version of the method is being developed to better handle biological variation. This new version is called **NOISeqBIO** and it is described in this {{:noiseqbio_techreport.pdf|Technical Report}} and also in this {{:posternoiseqbio.pdf|poster}}.

NOISeq