http://www.nature.com/ng/journal/v49/n5/full/ng.3818.html
Ref component analysis..of transcriptomes, by @Robson_Paul &co http://www.Nature.com/ng/journal/v49/n5/full/ng.3818.html Clustering similarity of samples to tissue references
http://www.nature.com/ng/journal/v49/n5/full/ng.3818.html
Ref component analysis..of transcriptomes, by @Robson_Paul &co http://www.Nature.com/ng/journal/v49/n5/full/ng.3818.html Clustering similarity of samples to tissue references
Evolution of BowTie Architectures http://journals.PLOS.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004055 3-layer, in-mid-out systems can have small a waist when their goal is compressible
#Aging increases cell-to-cell transcriptional variability upon immune stimulation, but just for 225 up-reg. genes http://science.ScienceMag.org/content/355/6332/1433
"Impacts of Neanderthal-Introgressed Sequences on the Landscape of Human Gene Expression"
(http://www.sciencedirect.com/science/article/pii/S0092867417301289)
#Neanderthal-Introgressed Sequences [&]…Gene Expression http://www.Cell.com/cell/abstract/S0092-8674(17)30128-9?_returnURL=http%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0092867417301289%3Fshowall%3Dtrue ASE for Hn SNPs shows lower #brain expression vs reference
#IHEC: A Blueprint for…Collab. & Discovery
http://www.Cell.com/cell/abstract/S0092-8674(16)31528-8?_returnURL=http%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0092867416315288%3Fshowall%3Dtrue Summary bullets on heterogeneity, disease, rel. to SNPs, comp. tools
.@denovodb: a compendium of [initially ~33K] human de novo variants w. phenotype, freely downloadable as a TSV table
https://academic.OUP.com/nar/article-lookup/doi/10.1093/nar/gkw865
QT:{{”
As of July 2016, denovo-db contained 40 different studies and 32,991 de novo variants from 23,098 trios. Database features include basic variant information (chromosome location, change, type); detailed annotation at the transcript and protein levels; severity scores; frequency; validation status; and, most importantly, the phenotype of the individual with the variant.
“}}
denovo-db.gs.washington.edu/denovo-db/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5210614/
#Network analytics in the age of #BigData
http://science.ScienceMag.org/content/353/6295/123.full Emphasizes analyzing connectivity of graph structures (eg motifs) v nodes
QT:{{”
To mine the wiring patterns of networked data and uncover the functional organization, it is not enough to consider only simple descriptors, such as the number of interactions that each entity (node) has with other entities (called node degree), because two networks can be identical in such simple descriptors, but have a very different connectivity structure (see the figure). Instead, Benson et al. use higher-order descriptors called graphlets (e.g., a triangle) that are based on small subnetworks obtained on a subset of nodes in the data that contain all interactions that appear in the data (3). They identify network regions rich in instances of a particular graphlet type, with few of the instances of the particular graphlet crossing the boundaries of the regions. If the graphlet type is specified in advance, the method can uncover the nodes interconnected by it, which enabled Benson et al. to group together 20 neurons in the nematode worm neuronal network that are known to control a particular type of movement. In this way, the method unifies the local wiring patterning with higher-order structural modularity imposed by it, uncovering higher-order functional regions in networked data. “}}
De novo assembly of the A aegypti genome using #HiC, by @erezaterez et al http://science.ScienceMag.org/content/early/2017/03/22/science.aal3327.full Works on human too, w. promise for #SVs
De novo assembly of the Aedes aegypti genome using Hi-C yields chromosome-length scaffolds
Olga Dudchenko1,2,3,4,
Sanjit S. Batra1,2,3,*,
Arina D. Omer1,2,3,*,
Sarah K. Nyquist1,3,
Marie Hoeger1,3,
Neva C. Durand1,2,3,
Muhammad S. Shamim1,2,3,
Ido Machol1,2,3,
Eric S. Lander5,6,7,
Aviva Presser Aiden1,2,8,9,
Erez Lieberman Aiden1,2,3,4,5,†
Science 23 Mar 2017:
eaal3327
DOI: 10.1126/science.aal3327
on whole genome assembly from Hi-C reads. There is also some info on chromosomal rearrangement from Hi-C.
Mechanisms underlying #SV formation in…disorders
http://www.Nature.com/nrg/journal/v17/n4/abs/nrg.2015.25.html Highlights importance of repeats in creating genomic plasticity
Nat Rev Genet. 2016 Apr;17(4):224-38. doi: 10.1038/nrg.2015.25. Epub 2016 Feb 29.
Mechanisms underlying structural variant formation in genomic disorders. Carvalho CM, Lupski JR
Thermodynamic characterization of #networks using graph polynomials https://journals.APS.org/pre/abstract/10.1103/PhysRevE.92.032810 Application to the stockmarket & biological data