2,833 research outputs found
On Greedy Algorithms for Binary de Bruijn Sequences
We propose a general greedy algorithm for binary de Bruijn sequences, called
Generalized Prefer-Opposite (GPO) Algorithm, and its modifications. By
identifying specific feedback functions and initial states, we demonstrate that
most previously-known greedy algorithms that generate binary de Bruijn
sequences are particular cases of our new algorithm
On Binary de Bruijn Sequences from LFSRs with Arbitrary Characteristic Polynomials
We propose a construction of de Bruijn sequences by the cycle joining method
from linear feedback shift registers (LFSRs) with arbitrary characteristic
polynomial . We study in detail the cycle structure of the set
that contains all sequences produced by a specific LFSR on
distinct inputs and provide a fast way to find a state of each cycle. This
leads to an efficient algorithm to find all conjugate pairs between any two
cycles, yielding the adjacency graph. The approach is practical to generate a
large class of de Bruijn sequences up to order . Many previously
proposed constructions of de Bruijn sequences are shown to be special cases of
our construction
Extreme Scale De Novo Metagenome Assembly
Metagenome assembly is the process of transforming a set of short,
overlapping, and potentially erroneous DNA segments from environmental samples
into the accurate representation of the underlying microbiomes's genomes.
State-of-the-art tools require big shared memory machines and cannot handle
contemporary metagenome datasets that exceed Terabytes in size. In this paper,
we introduce the MetaHipMer pipeline, a high-quality and high-performance
metagenome assembler that employs an iterative de Bruijn graph approach.
MetaHipMer leverages a specialized scaffolding algorithm that produces long
scaffolds and accommodates the idiosyncrasies of metagenomes. MetaHipMer is
end-to-end parallelized using the Unified Parallel C language and therefore can
run seamlessly on shared and distributed-memory systems. Experimental results
show that MetaHipMer matches or outperforms the state-of-the-art tools in terms
of accuracy. Moreover, MetaHipMer scales efficiently to large concurrencies and
is able to assemble previously intractable grand challenge metagenomes. We
demonstrate the unprecedented capability of MetaHipMer by computing the first
full assembly of the Twitchell Wetlands dataset, consisting of 7.5 billion
reads - size 2.6 TBytes.Comment: Accepted to SC1
Boltzmann samplers for random generation of lambda terms
Randomly generating structured objects is important in testing and optimizing
functional programs, whereas generating random -terms is more specifically
needed for testing and optimizing compilers. For that a tool called QuickCheck
has been proposed, but in this tool the control of the random generation is
left to the programmer. Ten years ago, a method called Boltzmann samplers has
been proposed to generate combinatorial structures. In this paper, we show how
Boltzmann samplers can be developed to generate lambda-terms, but also other
data structures like trees. These samplers rely on a critical value which
parameters the main random selector and which is exhibited here with
explanations on how it is computed. Haskell programs are proposed to show how
samplers are actually implemented
A polynomial delay algorithm for the enumeration of bubbles with length constraints in directed graphs and its application to the detection of alternative splicing in RNA-seq data
We present a new algorithm for enumerating bubbles with length constraints in
directed graphs. This problem arises in transcriptomics, where the question is
to identify all alternative splicing events present in a sample of mRNAs
sequenced by RNA-seq. This is the first polynomial-delay algorithm for this
problem and we show that in practice, it is faster than previous approaches.
This enables us to deal with larger instances and therefore to discover novel
alternative splicing events, especially long ones, that were previously
overseen using existing methods.Comment: Peer-reviewed and presented as part of the 13th Workshop on
Algorithms in Bioinformatics (WABI2013
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