User:Robert M. MacCallum/WTFGSB Reportback: Difference between revisions
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predict gene expr from histone acetylation using LOTS of ML methods (in R) | predict gene expr from histone acetylation using LOTS of ML methods (in R) | ||
===Grant Belgard=== | |||
brain transcriptomics | |||
by sequencing | |||
6 layers of neocortex | |||
many cell types spanning several layers | |||
paired end 50bp reads | |||
(you get some intronic reads) | |||
some intergenic regions detected (a few percent of reads) | |||
layer specific genes, various layers show various GO enrichments. |
Revision as of 03:33, 1 December 2009
Welcome Trust Functional Genomics and Systems Biology Workshop
30 November to 1 December 2009
Day one
Edison Liu
Estrogen (or is it EGF) receptor (ER) binding site analysis (ChIP and bioinf) - "Cosmic" score, correlation with RNA PolII binding and H3K4meX marks.
Some functional binding is 1Mb away from gene!! Only 9% in 5k "promoter".
Cool ChIA-PET (ChiA-seq) method to determine chromosomal loops.
Looping for efficient transcription, grouping of coregulated genes ("looped out" genes don't respond to ER)
Johan Rung
GWAS for type 2 diabetes
Day two
Seth Grant
Complexity of post-synaptic molecular machinery (several thousand proteins). Conserved in invertebrates (50% of prots) and single celled (25%). Evolution of the machinery (including plasticity) preceded evolution of synapses.
Very slow evolution.
Many diseases.
Caleb Webber
CNV in mouse
What's special about pathological CNVs? (vs. benign)
Human CNVs look up mouse phenotypes (somehow!)
Enrichment!
Florian Markowetz
ES cell histone modifications
days 1 3 5 of ES development - 4 analyses
Protein MS ChIP-chip histone Rna pol II Microarrays
day 0 nanog TF downreg -> network of TFs
clustering of smoothed histone profiles (around TSS)
when mRNA upreg, small local acetylation around TSS when mRNA down, wider deacetylation around TSS.
increased correlation between H acet and gene expression through time (more at day 5 than day 1) genome-wide
predict gene expr from histone acetylation using LOTS of ML methods (in R)
Grant Belgard
brain transcriptomics
by sequencing
6 layers of neocortex
many cell types spanning several layers
paired end 50bp reads
(you get some intronic reads)
some intergenic regions detected (a few percent of reads)
layer specific genes, various layers show various GO enrichments.