95 research outputs found
Expression reflects population structure
Population structure in genotype data has been extensively studied, and is revealed by looking at the principal components of the genotype matrix. However, no similar analysis of population structure in gene expression data has been conducted, in part because a naïve principal components analysis of the gene expression matrix does not cluster by population. We identify a linear projection that reveals population structure in gene expression data. Our approach relies on the coupling of the principal components of genotype to the principal components of gene expression via canonical correlation analysis. Our method is able to determine the significance of the variance in the canonical correlation projection explained by each gene. We identify 3,571 significant genes, only 837 of which had been previously reported to have an associated eQTL in the GEUVADIS results. We show that our projections are not primarily driven by differences in allele frequency at known cis-eQTLs and that similar projections can be recovered using only several hundred randomly selected genes and SNPs. Finally, we present preliminary work on the consequences for eQTL analysis. We observe that using our projection co-ordinates as covariates results in the discovery of slightly fewer genes with eQTLs, but that these genes replicate in GTEx matched tissue at a slightly higher rate
Expression reflects population structure
Population structure in genotype data has been extensively studied, and is revealed by looking at the principal components of the genotype matrix. However, no similar analysis of population structure in gene expression data has been conducted, in part because a naïve principal components analysis of the gene expression matrix does not cluster by population. We identify a linear projection that reveals population structure in gene expression data. Our approach relies on the coupling of the principal components of genotype to the principal components of gene expression via canonical correlation analysis. Our method is able to determine the significance of the variance in the canonical correlation projection explained by each gene. We identify 3,571 significant genes, only 837 of which had been previously reported to have an associated eQTL in the GEUVADIS results. We show that our projections are not primarily driven by differences in allele frequency at known cis-eQTLs and that similar projections can be recovered using only several hundred randomly selected genes and SNPs. Finally, we present preliminary work on the consequences for eQTL analysis. We observe that using our projection co-ordinates as covariates results in the discovery of slightly fewer genes with eQTLs, but that these genes replicate in GTEx matched tissue at a slightly higher rate
Near-optimal probabilistic RNA-seq quantification
We present kallisto, an RNA-seq quantification program that is two orders of magnitude faster than previous approaches and achieves similar accuracy. Kallisto pseudoaligns reads to a reference, producing a list of transcripts that are compatible with each read while avoiding alignment of individual bases. We use kallisto to analyze 30 million unaligned paired-end RNA-seq reads in <10 min on a standard laptop computer. This removes a major computational bottleneck in RNA-seq analysis
Gene-level differential analysis at transcript-level resolution
Compared to RNA-sequencing transcript differential analysis, gene-level differential expression analysis is more robust and experimentally actionable. However, the use of gene counts for statistical analysis can mask transcript-level dynamics. We demonstrate that ‘analysis first, aggregation second,’ where the p values derived from transcript analysis are aggregated to obtain gene-level results, increase sensitivity and accuracy. The method we propose can also be applied to transcript compatibility counts obtained from pseudoalignment of reads, which circumvents the need for quantification and is fast, accurate, and model-free. The method generalizes to various levels of biology and we showcase an application to gene ontologies
Tapping Thermodynamics of the One Dimensional Ising Model
We analyse the steady state regime of a one dimensional Ising model under a
tapping dynamics recently introduced by analogy with the dynamics of
mechanically perturbed granular media. The idea that the steady state regime
may be described by a flat measure over metastable states of fixed energy is
tested by comparing various steady state time averaged quantities in extensive
numerical simulations with the corresponding ensemble averages computed
analytically with this flat measure. The agreement between the two averages is
excellent in all the cases examined, showing that a static approach is capable
of predicting certain measurable properties of the steady state regime.Comment: 11 pages, 5 figure
Glassy systems under time-dependent driving forces: application to slow granular rheology
We study the dynamics of a glassy model with infinite range interactions
externally driven by an oscillatory force. We find a well-defined transition in
the (Temperature-Amplitude-Frequency) phase diagram between (i) a `glassy'
state characterized by the slow relaxation of one-time quantities, aging in
two-time quantities and a modification of the equilibrium
fluctuation-dissipation relation; and (ii) a `liquid' state with a finite
relaxation time. In the glassy phase, the degrees of freedom governing the slow
relaxation are thermalized to an effective temperature. Using Monte-Carlo
simulations, we investigate the effect of trapping regions in phase space on
the driven dynamics. We find that it alternates between periods of rapid motion
and periods of trapping. These results confirm the strong analogies between the
slow granular rheology and the dynamics of glasses. They also provide a
theoretical underpinning to earlier attempts to present a thermodynamic
description of moderately driven granular materials.Comment: Version accepted for publication - Physical Review
Meredys, a multi-compartment reaction-diffusion simulator using multistate realistic molecular complexes
<p>Abstract</p> <p>Background</p> <p>Most cellular signal transduction mechanisms depend on a few molecular partners whose roles depend on their position and movement in relation to the input signal. This movement can follow various rules and take place in different compartments. Additionally, the molecules can form transient complexes. Complexation and signal transduction depend on the specific states partners and complexes adopt. Several spatial simulator have been developed to date, but none are able to model reaction-diffusion of realistic multi-state transient complexes.</p> <p>Results</p> <p><it>Meredys </it>allows for the simulation of multi-component, multi-feature state molecular species in two and three dimensions. Several compartments can be defined with different diffusion and boundary properties. The software employs a Brownian dynamics engine to simulate reaction-diffusion systems at the reactive particle level, based on compartment properties, complex structure, and hydro-dynamic radii. Zeroth-, first-, and second order reactions are supported. The molecular complexes have realistic geometries. Reactive species can contain user-defined feature states which can modify reaction rates and outcome. Models are defined in a versatile NeuroML input file. The simulation volume can be split in subvolumes to speed up run-time.</p> <p>Conclusions</p> <p><it>Meredys </it>provides a powerful and versatile way to run accurate simulations of molecular and sub-cellular systems, that complement existing multi-agent simulation systems. <it>Meredys </it>is a Free Software and the source code is available at <url>http://meredys.sourceforge.net/</url>.</p
Nanoscale surface topography reshapes neuronal growth in culture
International audienceNeurons are sensitive to topographical cues provided either by in vivo or in vitro environments on the micrometric scale. We have explored the role of randomly distributed silicon nanopillars on primary hippocampal neurite elongation and axonal differentiation. We observed that neurons adhere on the upper part of nanopillars with a typical distance between adhesion points of about 500 nm. These neurons produce fewer neurites, elongate faster, and differentiate an axon earlier than those grown on flat silicon surfaces. Moreover, when confronted with a differential surface topography, neurons specify an axon preferentially on nanopillars. As a whole, these results highlight the influence of the physical environment in many aspects of neuronal growth
Modeling the Subsurface Structure of Sunspots
While sunspots are easily observed at the solar surface, determining their
subsurface structure is not trivial. There are two main hypotheses for the
subsurface structure of sunspots: the monolithic model and the cluster model.
Local helioseismology is the only means by which we can investigate
subphotospheric structure. However, as current linear inversion techniques do
not yet allow helioseismology to probe the internal structure with sufficient
confidence to distinguish between the monolith and cluster models, the
development of physically realistic sunspot models are a priority for
helioseismologists. This is because they are not only important indicators of
the variety of physical effects that may influence helioseismic inferences in
active regions, but they also enable detailed assessments of the validity of
helioseismic interpretations through numerical forward modeling. In this paper,
we provide a critical review of the existing sunspot models and an overview of
numerical methods employed to model wave propagation through model sunspots. We
then carry out an helioseismic analysis of the sunspot in Active Region 9787
and address the serious inconsistencies uncovered by
\citeauthor{gizonetal2009}~(\citeyear{gizonetal2009,gizonetal2009a}). We find
that this sunspot is most probably associated with a shallow, positive
wave-speed perturbation (unlike the traditional two-layer model) and that
travel-time measurements are consistent with a horizontal outflow in the
surrounding moat.Comment: 73 pages, 19 figures, accepted by Solar Physic
- …