Time-courses analysis overview
Instructions
Here you find a description of the analyses applied consistently to all (or certain classes of) time-courses. Follow the links in this overview page to get to the detailed descriptions.
Analysis providers: please edit this page to establish downstream pages detailing your analysis following the guidelines below. You can change the suggested links below before you establish the page!
Analysis overview
Quality control with a set of basic analyses (Erik Arner's analysis)
DPI clustering (Hideya Kawaji)
TSS classifier (Timo Lassmann)
Novel motifs in time-courses (Vsevolod Makeev, Ivan Kulakovskiy, Ulf Schaefer, Yulia Medvedeva, Michael Rehli)
Expression analysis by CAGE (Break don to smaller items here? Or establish many sub-pages). (Erik Arner, Owen Rackham, Sarah, Wyeth Wasserman, Anthony Mathelier, Boris Lenhard, Vanja Haberle, Finn Drablos, Morten Rye, Carlo Cannistraci, Tim Ravasi, Kim-Anh Le Cao, others)
Enhancers and their RNA (Albin et al.)
Alternative promoters (Emmanuel Dimont; Martin Taylor, Sarah Baker)
MARA (Erik van Nimwegen, Peter Pemberton-Ross, Erik Arner)
Genome variation and expression (Kenneth Baillie)
miRNA (Erik Arner, Pal Saetrom, others)
Other topics (establish page yourself):
- TF analysis expression, TF based network
- TF that characterize a given cellular state (and drive it?);
- TF and diseases literature search
- Biolayout to all samples
- Antisense promoters
- Enhancers connection to target (Hi-C, Chia-PET. Etc.)
- SNP of each promoter, enhancer, ncRNAs at each isolated key feature in time courses
- Noncoding RNA: long and small; including Retrotransposon elements expression
- The above non-coding RNA that characterize a cellular state
- Retrotransposons retrotransposition (targeted RE capture)
- Antisense and ncRNAs associated to TF and other protein coding RNAs
- ncRNAs that show up in specific time course points, candidate for specific validation
- Seed for future mechanistic studies by each laboratory
- Human versus mouse, data analysis for both systems
- Concordant-discordant promoters in the time course (within time course; what is their biology)
- Ripple of transcription (and what is the relation with enhancer?)
Guidelines for the content
- A description of the analysis - not all the maths or programming, but a simple word description of what the analysis does, what it is likely to tell us, what are the assumptions and limitations
- What their analysis already provides at the practical level: visualizations/images, tables, statistics, lists of genes etc. If the output is a table or text file, where can we go to get images or further analysis? Links to the outputs within the wiki.
- Reference papers where this analysis or a similar analysis has been used, for those who want further information behind the mathematics and statistics or examples of the interpretation.
- Who to contact if trouble arises. Level of collaboration available (eg is the provider able to do custom analysis if we can't manage it ourselves).
- Links to webpages that were used to develop the resource/output.
- Links to websites that provide results or data or analysis.
- Maybe a Standard Operating Procedure of how to perform the analysis? (ie scripts, user guide for web-based analysis....etc.)
