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 (Erik Arner, Owen Rackham, Sarah)
Enhancers and their RNA (Albin et al.)
Alternative promoters (Emmanuel Dimont; Martin Taylor, Sarah Baker)
MARA (Erik van Nimwegen, Peter Pemberton-Ross, Erik Arner)
miRNA (Erik Arner, Pal Saetrom, others)
- 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?)
