5,997 research outputs found
Ensemble Analysis of Adaptive Compressed Genome Sequencing Strategies
Acquiring genomes at single-cell resolution has many applications such as in
the study of microbiota. However, deep sequencing and assembly of all of
millions of cells in a sample is prohibitively costly. A property that can come
to rescue is that deep sequencing of every cell should not be necessary to
capture all distinct genomes, as the majority of cells are biological
replicates. Biologically important samples are often sparse in that sense. In
this paper, we propose an adaptive compressed method, also known as distilled
sensing, to capture all distinct genomes in a sparse microbial community with
reduced sequencing effort. As opposed to group testing in which the number of
distinct events is often constant and sparsity is equivalent to rarity of an
event, sparsity in our case means scarcity of distinct events in comparison to
the data size. Previously, we introduced the problem and proposed a distilled
sensing solution based on the breadth first search strategy. We simulated the
whole process which constrained our ability to study the behavior of the
algorithm for the entire ensemble due to its computational intensity. In this
paper, we modify our previous breadth first search strategy and introduce the
depth first search strategy. Instead of simulating the entire process, which is
intractable for a large number of experiments, we provide a dynamic programming
algorithm to analyze the behavior of the method for the entire ensemble. The
ensemble analysis algorithm recursively calculates the probability of capturing
every distinct genome and also the expected total sequenced nucleotides for a
given population profile. Our results suggest that the expected total sequenced
nucleotides grows proportional to of the number of cells and
proportional linearly with the number of distinct genomes
Corrected entropy of the rotating black hole solution of the new massive gravity using the tunneling method and Cardy formula
We study the AdS rotating black hole solution for the
Bergshoeff-Hohm-Townsend (BHT) massive gravity in three dimensions. The field
equations of the asymptotically AdS black hole of the static metric can be
expressed as the first law of thermodynamics, i.e. . The corrected
Hawking-like temperature and entropy of asymptotically AdS rotating black hole
are calculated using the Cardy formula and the tunneling method. Comparison of
these methods will help identify the unknown leading correction parameter
in the tunneling method.Comment: 6 page
Resurrecting the exponential and inverse power-law potentials in non-canonical inflation
We study inflation within the framework of non-canonical scalar field. In
this scenario, we obtain the inflationary observables such as the scalar
spectral index, the tensor-to-scalar ratio, the running of the scalar spectral
index as well as the equilateral non-Gaussianity parameter. Then, we apply
these results for the exponential and inverse power-law potentials. Our
investigation shows that although the predictions of these potentials in the
standard canonical inflation are completely ruled out by the Planck 2015
observations, their results in non-canonical scenario can lie inside the
allowed regions of the Planck 2015 data. We also find that in non-canonical
inflation, the predictions of the aforementioned potentials for the running of
the scalar spectral index and the equilateral non-Gaussianity parameter are in
well agreement with the Planck 2015 results. Furthermore, we show that in the
context of non-canonical inflation, the graceful exit problem of the
exponential and inverse power-law potentials is resolved.Comment: 18 pages, 3 figure
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