Panorama of ancient metazoan #macromolecular complexes
http://www.nature.com/nature/journal/v525/n7569/abs/nature14877.html Finding many more #complexes from integrating many co-elutions
http://www.nature.com/nature/journal/v525/n7569/full/nature14877.html#affil-auth
Punctuated equilibrium in the large-scale #evolution of #programming languages http://rsif.royalsocietypublishing.org/content/12/107/20150249 Clustering groups these into trees
Punctuated equilibrium in the large-scale evolution of programming languages
Sergi Valverde, Ricard V. Solé
Why human disease-associated residues appear as WT in other species http://mbe.oxfordjournals.org/content/31/7/1787.abstract Compensation by their 3D structural neighbors
#Chromatin…shapes the mutational landscape of cancer
http://www.nature.com/nature/journal/v518/n7539/full/nature14221.html Low DNase correlates w/ high SNVs in melanoma. True generally?
#SingleCell chromatin accessibility
http://www.nature.com/nature/journal/v523/n7561/full/nature14590.html >1.6k ATAC-seq expts; many on @ENCODE_NIH cell lines H1, GM12878 & K562
Multiple hypothesis testing in genomics
http://onlinelibrary.wiley.com/doi/10.1002/sim.6082/full Nice overview, comparing familywise error & FDR control + FDP estimation
http://www.few.vu.nl/~mavdwiel/HDDA/tutorial_multtest.pdf
QT:{{”
This paper presents an overview of the current state-of-the-art in multiple testing in genomics data from a user’s perspective. We describe methods for familywise error control, false discovery rate control and false discovery proportion estimation and confidence, both conceptually and practically, and explain when to use which type of error rate. We elaborate the assumptions underlying the methods, and discuss pitfalls in the interpretation of results. In our discussion we take into account the exploratory nature of genomics experiments, looking at selection of genes before or after testing, and at the role of validation experiments.
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DNA sequence…#compression
http://bib.oxfordjournals.org/content/16/1/1.full Nice review comparing approaches on 2 axes: classic v Nextgen & reference-based v -free
Not much on LD-based approaches
Zexuan Zhu
Yongpeng Zhang
Zhen Ji
Shan He
Xiao Yang
Brief Bioinform (2015) 16 (1): 1-15.doi: 10.1093/bib/bbt087
First published online: December 3, 2013
[440 @GencodeGenes] #Pseudogenes transcribed in breast…carcinoma show subtype-specific expression & ceRNA potential http://www.biomedcentral.com/1471-2164/16/113
Similarity #network fusion for aggregating data types http://www.nature.com/nmeth/journal/v11/n3/full/nmeth.2810.html Combines mRNA, miRNA & gene fusions to classify cancer subtypes
http://compbio.cs.toronto.edu/SNF/SNF
Identification of #Asthma Phenotypes Using Cluster Analysis
http://www.atsjournals.org/doi/abs/10.1164/rccm.200906-0896OC#.VWk-gFxViko 5 canonical groups based on lung function, meds usage, &c
Canonical clustering of asthmatic patients into different groups
linkstream2 microblog 