Posts Tagged ‘jc’

Gene-gene and gene-environment interactions detected by transcriptome sequence analysis in twins : Nature Genetics : Nature Publishing Group

March 3, 2016

Gene-gene & gene-env interactions…by #transcriptome…in twins by @dermitzakis lab
http://www.nature.com/ng/journal/v47/n1/full/ng.3162.html Nice model for ASE HT @cjieming

Gene-gene and gene-environment interactions detected by transcriptome sequence analysis in twins
Alfonso Buil, Andrew Anand Brown, Tuuli Lappalainen, Ana Viñuela, Matthew N Davies, Hou-Feng Zheng, J Brent Richards, Daniel Glass, Kerrin S Small, Richard Durbin, Timothy D Spector & Emmanouil T Dermitzakis

http://www.nature.com/ng/journal/v47/n1/full/ng.3162.html

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pQTLs

July 21, 2015

Impact of regulatory variation from RNA to protein
http://www.sciencemag.org/content/347/6222/664.abstract pQTLs for prot levels less related to #eQTLs & rQTLs than expected

How genetics affect phenotypic variation
http://www.sciencemag.org/content/347/6222/664.abstract

Drosophila Muller F Elements Maintain a Distinct Set of Genomic Properties Over 40 Million Years of Evolution

May 15, 2015

“this has got to be a record… imported this into Zotero to find the total author count. It’s 1,014”
http://www.g3journal.org/content/5/5/719.abstract

Analyses of allele-specific gene expression in highly divergent mouse crosses identifies pervasive allelic imbalance : Nature Genetics : Nature Publishing Group

March 29, 2015

http://www.nature.com/ng/journal/vaop/ncurrent/full/ng.3222.html

Nat Genet. 2015 Mar 2. doi: 10.1038/ng.3222. [Epub ahead of print]

Analyses of allele-specific gene expression in highly divergent mouse crosses identifies pervasive allelic imbalance.

Crowley JJ1, Zhabotynsky V1, Sun W2, Huang S3, Pakatci IK3, Kim Y1, Wang JR3, Morgan AP4, Calaway JD4, Aylor DL1, Yun Z1, Bell TA4, Buus RJ4, Calaway ME4, Didion JP4, Gooch TJ4, Hansen SD4, Robinson NN4, Shaw GD4, Spence JS1, Quackenbush CR1, Barrick CJ1, Nonneman RJ1, Kim K5, Xenakis J5, Xie Y1,Valdar W6, Lenarcic AB1, Wang W3, Welsh CE3, Fu CP3, Zhang Z3, Holt J3, Guo Z3, Threadgill DW7, Tarantino LM8, Miller DR4, Zou F5, McMillan L3, Sullivan PF9, Pardo-Manuel de Villena F4.

http://www.nature.com/ng/journal/v47/n4/full/ng.3222.html

Carefully controlled allele expt – hets midway in expr betw homs for parents for 76pct (additive model) but 25pct hets diff. from parents

ASE in…divergent mouse crosses identifies pervasive allelic imbalance, 80%, w/ 60% closely following additive model
http://www.nature.com/ng/journal/vaop/ncurrent/full/ng.3222.html

Hybrid curation of gene–mutation relations combining automated extraction and crowdsourcing

November 1, 2014

Curation of gene–mutation relations… automated extraction &
#crowdsourcing http://database.oxfordjournals.org/content/2014/bau094.abstract?ct $AMZN’s turkers help to get 90% accuracy

Signaling hypergraphs: Trends in Biotechnology

October 9, 2014

Signaling #hypergraphs
http://www.cell.com/trends/biotechnology/abstract/S0167-7799(14)00071-7 Edges from interactions of 2 sets of nodes. Better representation of assemblies & #complexes.

QT:{{”
each edge is defined not by interaction of 2 nodes (as in graphs), but 2 sets of nodes (known as hypernodes in hypergraphs)……The use of hypernodes also represents three concepts better than directed or non-directed graphs: protein complexes, protein assemblies and regulation (especially involving complexes/assemblies).
“}}

Signaling hypergraphs. Ritz et al. (2014) TIB

This opinion paper advocates the use of hypergraphs to complement graph-based signaling network and pathway analyses, where each edge is defined not by interaction of 2 nodes (as in graphs), but 2 sets of nodes (known as hypernodes in hypergraphs). They argue that
hypergraphs is a set-based method that acts like a more general version of a graph. The use of hypernodes also represents three concepts better than directed or non-directed graphs: protein complexes, protein assemblies and regulation (especially involving complexes/assemblies). They propose that hypergraphs can be very useful in situations where the effects of individual proteins might be neglected in graphs but will have a noticeable effect when these proteins are included in protein complexes as hypernodes. They use 3 applications as examples: pathway enrichment, pathway reconstruction, and pathway crosstalk.

23andme research portal

September 19, 2014

https://www.23andme.com/researchportal

less than 10 percent of the human genome is functional

July 30, 2014

~8%

http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004525

amino acid changes in 1000 Genomes Project Thornton Lab

June 23, 2014

1000G v disease variants
http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1003382

correlations – “stay away from bedsheets”

May 13, 2014

need adjusted p values after multiple hypothesis correction

Spurious Correlations
http://www.tylervigen.com