linkstream2 microblog

Treefinder Retraction Note [interestingly, done editorially due to change in software-license terms] http://www.biomedcentral.com/1471-2148/15/243 HT @bornalibran

https://getpocket.com/?ep=1

Canonical genetic signatures [across 132 structures] of the adult human #brain [in 6 individuals]
http://www.nature.com/neuro/journal/vaop/ncurrent/full/nn.4171.html HT @ozgunharmanci

QT:{{”
We applied a correlation-based metric called differential stability to assess reproducibility of gene expression patterning across 132 structures in six individual brains, revealing mesoscale genetic organization. The genes with the highest differential stability are highly biologically relevant, with enrichment for brain-related annotations, disease associations, drug targets and literature citations.
“}}

A Multiscale Coarse-Graining Method for Biomolecul[es] http://pubs.acs.org/doi/abs/10.1021/jp044629q Simplified force field from fitting to all-atom #simulations

Sergei Izvekov and Gregory A. Voth *
J. Phys. Chem. B, 2005, 109 (7), pp 2469–2473
DOI: 10.1021/jp044629q

Heterogeneity in #singlecell RNAseq…hidden subpopulations by @OliverStegle lab http://www.nature.com/nbt/journal/v33/n2/full/nbt.3102.html scLVM corrects for cell cycle phase

Buettner, Florian, Kedar N. Natarajan, F. Paolo Casale, Valentina
Proserpio, Antonio Scialdone, Fabian J. Theis, Sarah A. Teichmann,
John C. Marioni, and Oliver Stegle. "Computational analysis of
cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals
hidden subpopulations of cells." Nature biotechnology 33, no. 2
(2015): 155-160.

#Singlecell ChIPseq reveals…subpopulations defined by chromatin statehttp://www.nature.com/nbt/journal/vaop/ncurrent/full/nbt.3383.html Sparse data: on order of 1K uniq. reads/cell

http://www.nature.com/nbt/journal/vaop/ncurrent/full/nbt.3383.html

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

A Helpful Reference

https://apps.lis.illinois.edu/wiki/download/attachments/4369699/curriculum+analysis.doc?version=4

Preserving Validity in Adaptive Data Analysis http://ibmresearchnews.blogspot.com/2015/08/preserving-validity-in-adaptive-data_6.html Using differential #privacy for correct #stats even w/ test-set reuse

QT:{{"
“A common next step would be to use the least-squares linear regression to check whether a simple linear combination of the three strongly correlated foods can predict the grade. It turns out that a little combination goes a long way: we discover that a linear combination of the three selected foods can explain a significant fraction of variance in the grade (plotted below). The regression analysis also reports that the p-value of this result is 0.00009 meaning that the probability of this happening purely by chance is less than 1 in 10,000.

Recall that no relationship exists in the true data distribution, so this discovery is clearly false. This spurious effect is known to experts as Freedman’s paradox. It arises since the variables (foods) used in the regression were chosen using the data itself.

…
We found that challenges of adaptivity can be addressed using techniques developed for privacy-preserving data analysis. These techniques rely on the notion of differential privacy that guarantees that the data analysis is not too sensitive to the data of any single individual. We rigorously demonstrated that ensuring differential privacy of an analysis also guarantees that the findings will be statistically valid. We then also developed additional approaches to the problem based on a new way to measure how much information an analysis reveals about a dataset.

The Thresholdout Algorithm

Using our new approach we designed an algorithm, called Thresholdout, that allows an analyst to reuse the holdout set of data for validating a large number of results, even when those results are produced by an adaptive analysis.

"}}

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