Time-courses analysis overview

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.

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

Enhancers and their RNA (Albin et al.)

Alternative promoters (Emmanuel Dimont; Martin Taylor, Sarah Baker)

MARA (Erik van Nimwegen, Peter Pemberton-Ross)

• 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.)
• 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
• SNP of each promoter, enhancer, ncRNAs at each isolated key feature in time courses
• 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?)