This page contains links to descriptions of the methods we used to
generate the data in EPConDB. If there is something we have not
covered please let us know.
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| Measuring Tissue-Specific Expression with the Q Statistic |
A survey of gene expression across a variety of tissues yields
important information about the expression patterns of genes. In
particular, it can be used to identify genes that are specific to a
given tissue of interest. EPConDB uses the Q statistic to do
this. This method description motivates and describes the use of the
Q statistic.
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| Predicting Regulatory Relationships between Transcription Factors and DoTS Transcripts |
Part of the transcriptional regulation of gene expression is
carried out by transcription factors that recognize a family of
short, similar DNA sequences called binding sites. A family of
binding sites can be represented by a positional weight matrix so
that putative binding sites can be computationally predicted in the
genome. Because binding sites are short and diverse relative to
their length many sites are predicted than are actually functional.
We have made TF-DoTS transcription regulation predictions for a
dozen or so islet- and/or pancreas-related TFs. To do this we have
taken a few steps to try to increase the reliability of the
predictions as well as to deal with uncertainty about the exact
binding sites families.
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| RNA Expression Experiment Categories |
Experiments are classified according to their intent.
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| Static and Dynamic Gene Lists for Differential Expression |
For selected microarray experiments analyzing at least two conditions and with at least three (biological) replicates per condition, we provide lists of genes which are likely to be differentially expressed between pairs of conditions. These lists are generated primarily using PaGE.
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