6 research outputs found
Identifying High-Confidence TFâTarget Interactions and TF Modules
<p>Different lines of evidence indicative of TFâtarget interactions are combined to yield an integrated probabilistic measure of interaction propensity. Using a positive and a negative validation set, the input evidences are independently converted into LLSs. Individual LLSs are integrated into one value per TFâtarget pair. TF modules are identified as subsets of TFs that regulate common genes.</p
Quality Assessment of the Predicted TFâTarget Gene Interactions
<div><p>(A) ROC curves are average of two cross-validations (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0020070#s3" target="_blank">Materials and Methods</a>). Lines show specificity and sensitivity accounting for binding evidence only and for integrating all evidences based on the Bayesian approach (with and without [âBayes sumâ] additional filtering). Additional filtering requires that at least two evidences have LLS > 0.5 (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0020070#s3" target="_blank">Materials and Methods</a>). Single points refer to previous selections [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0020070#pcbi-0020070-b011" target="_blank">11</a>] based on binding evidence (chIP-chip, <i>p<sub>b</sub></i> < 0.001, <i>p<sub>b</sub></i> < 0.005) and motif presence in zero, two, or three yeast species, respectively. Blue arrows indicate the respective LLS thresholds.</p><p>(B) Target gene sets were validated against Gene Ontology categories taken from SGD [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0020070#pcbi-0020070-b031" target="_blank">31</a>] and clusters of coexpressed genes (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0020070#s3" target="_blank">Materials and Methods</a>). In the latter case, all evidences based on expression data were excluded when assigning TFs to targets. The vertical bars indicate the fractions of TFs or TF modules for which the target genes significantly overlap with at least one category or cluster (<i>p</i> < 10<sup>â4</sup>, hypergeometric distribution). The filtering criteria for the three sets of predicted interactions were chosen such that all selections have the same specificity (0.995). Yellow indicates using binding <i>p</i>-values as the sole selection criterion; green, selections by Harbison et al. [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0020070#pcbi-0020070-b011" target="_blank">11</a>] based on binding motifs conserved in at least three species and with binding <i>p</i>-values <i>(p<sub>b</sub>)</i> < 0.005; and blue, combining all possible lines of evidence; at least two predicted LLSs must be > 0.5; the sum of all evidences must yield a LLS > 5. All modules are significant with <i>p</i><sub>mod</sub> < 10<sup>â4</sup>, except for the light and dark blue bars (<i>p</i><sub>mod</sub> < 0.1 and < 10<sup>â6</sup>, respectively). The <i>p</i><sub>mod</sub> does not apply to the single TFs.</p><p>(C) LLSs were determined based on all evidences, but excluding binding under nonstandard conditions. The average LLS (sliding window) is plotted versus binding <i>p</i>-values under nonstandard conditions. Blue line indicates all TFâtarget pairs; red line, subset excluding pairs binding under standard conditions (i.e., LLS is exclusively based on evidences other than binding). Horizontal lines indicate global average LLS (solid lines) and average plus one standard deviation (dashed lines).</p></div
Combinatorial Regulation by TF Modules
<div><p>(A) Bars show average centrality (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0020070#s3" target="_blank">Materials and Methods</a>) of target genes overlapping with stress-related clusters (± standard error). Values above bars are numbers of overlapping target genes. Generic TFs such as Yap1p or Swi6p are reused in several modules. Combination with other TFs yields specificity (i.e., a smaller number of target genes and an increased centrality).</p><p>(B) Hierarchy of TF modules. Arrows represent a subset relationship (i.e., all TFs of the source module are contained in the target module). Downstream TF modules always share their targets with upstream TF modules. Annotations are based on significant (<i>p</i> < 10<sup>â4</sup>, hypergeometric distribution) overlaps between the target gene sets and the respective functional category. Values in parentheses are numbers of target genes (black) and numbers of overlapping genes (red, green).</p><p>(C) Complete hierarchy of the 363 significant TF modules (<i>p</i><sub>mod</sub> < 10<sup>â4</sup>). Highlighted regions contain TF modules that are enriched with the respective TFs or TF complexes.</p></div
Rpn4p and Pdr1p Binding under Normal and Stress Conditions (H<sub>2</sub>O<sub>2</sub> and MMS)
<p>Binding <i>p</i>-values for MMS (this study) and other conditions (taken from [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0020070#pcbi-0020070-b011" target="_blank">11</a>]) are shown for groups of (A) Rpn4p and (B) Pdr1p targets (LLS > 5) with coherent binding patterns (red, strong binding; black, no binding). Additional transcription factors coregulating a significant (<i>p</i> < 0.001) number of genes either as individual TFs or as members of TF modules are listed below each cluster.</p
Bulletin mensuel de statistique / Institut national de la statistique et des Ă©tudes Ă©conomiques...
septembre 19801980/09 (N9,A31)
Additional file 3: Figure E1. of Meta-analysis derived atopic dermatitis (MADAD) transcriptome defines a robust AD signature highlighting the involvement of atherosclerosis and lipid metabolism pathways
A) Prisma. B) MADAD Datasets. C) Meta-Analysis Workflow. (PDF 608ĂÂ kb