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Abstract:
We present One Hand Clapping (OHC), a method for
the detection of condition-specific interactions
between transcription factors (TFs) from
genome-wide gene activity measurements. OHC is
based on a mapping between transcription factors
and their target genes. Given a single case–control
experiment, it uses a linear regression model to
assess whether the common targets of two arbitrary
TFs behave differently than expected from the
genes targeted by only one of the TFs. When
applied to osmotic stress data in S. cerevisiae,
OHC produces consistent results across three
types of expression measurements: gene expression
microarray data, RNA Polymerase II ChIP-chip
binding data and messenger RNA synthesis rates.
Among the eight novel, condition-specific TF pairs,
we validate the interaction between Gcn4p and
Arr1p experimentally. We apply OHC to a large
gene activity dataset in S. cerevisiae and provide a
compendium of condition-specific TF interactions.
