Time-courses main paper

Overview and background

The time-course main (or umbrella) paper aims to open all the time-course data and to provide a meta-analysis across all time-courses. This analysis plan is arranged in two parts. The first part covers the analysis steps applied to all time-course data sets resulting in a data infrastructure that can be used for the work on the individual time-courses and makes the individual analyses comparable (at least to some extend) described in Time-courses_analysis_overview. The second part covers the actual meta-analysis work plan packaged into tasks that can be addressed by separate researchers/ collaborators where results can then be integrated for the paper. Papers for the individual time-courses are outlined in the Wiki section for the Time-courses_Satellite_papers.

Manuscript for Umbrella Paper

The manuscript will be linked from here.

Figures for time-course main paper

Figure 1: Overview and context of time-courses

• Overview of time-courses
  • Cartoon of human body visualizing the location of time course samples
  • Characterize the time-courses
  • Emphasize the diversity
  • Cell type, type of receptor, classification of outcome
  • What time points taken in each case

• Watanabe for cartoon
• Christine, David, Carsten, Al for table
• Within 2012

Figure 2: Put time courses in the snapshot framework

• Put time courses in the snapshot framework
• Distinguish differentiation/activation related to start and end point
  • Biolayout or similar
• Confirm key marker genes for each time-course with CAGE expression, as table (sanity check)

• Biolayout: Kim, (Kenny, Tom)
• Key marker gene table: Christine asks collaborators
• Early draft in November 2012

Figure 3: Early response

• Focus on early response
• Visualization
  • Separately for early, mid, late
  • Who: Albin, Robin, Boris, David
• Based on
  • Expression, enhancer usage, motif usage, miRNA, non-miRNA induced in time
  • Who: collaborators for each of the analysis results involved
  • Done, Dec 2012, December 1012, done, maybe next paper
• Identify commonalities, differences -> branching, where do cells become specialized
• Based on a range of evidences: expression enhancer usage, TF usage (MARA), miRNA, etc.
  • Why is IER transient?
• Distance approach (Biolayout?)
  • Identify ‘distance’ between time points
  • Make lists of genes: TF, known early response genes, signaling, receptors, etc.
• Who: David, Carsten, then put on a Wiki page and ask collaborators to add

• when? Analysis can take some time

Figure 4: Common network motifs

• Common network motifs etc.

Who: Erik A., Owen December 2012

Figure 5: Human - mouse comparison

• Species comparison
• IER similar aspects in terms of expression,
• Coexpression comparison: Yong
• Network comparisons: Erik, Owen

Figure 6: Validation

• knocking down and profile the novel elements that appear from the analysis in Fig#3. Overexpress + KD in cell system Illumina CAGE
• Maybe we can wait for the reviewers to tell us what to validate
• Depends on what we see in the analysis

Paper punch lines

• xxx

Analyses applied consistently to all time-courses

Can be found under Time-courses_analysis_overview.

Timecourse data

Please find the Timecourses here.