83 research outputs found
CO-phylum: An Assembly-Free Phylogenomic Approach for Close Related Organisms
Phylogenomic approaches developed thus far are either too time-consuming or
lack a solid evolutionary basis. Moreover, no phylogenomic approach is capable
of constructing a tree directly from unassembled raw sequencing data. A new
phylogenomic method, CO-phylum, is developed to alleviate these flaws.
CO-phylum can generate a high-resolution and highly accurate tree using
complete genome or unassembled sequencing data of close related organisms, in
addition, CO-phylum distance is almost linear with p-distance.Comment: 21 pages, 6 figure
Reverse-Safe Data Structures for Text Indexing
We introduce the notion of reverse-safe data structures. These are data structures that prevent the reconstruction of the data they encode (i.e., they cannot be easily reversed). A data structure D is called z-reverse-safe when there exist at least z datasets with the same set of answers as the ones stored by D. The main challenge is to ensure that D stores as many answers to useful queries as possible, is constructed efficiently, and has size close to the size of the original dataset it encodes. Given a text of length n and an integer z, we propose an algorithm which constructs a z-reverse-safe data structure that has size O(n) and answers pattern matching queries of length at most d optimally, where d is maximal for any such z-reverse-safe data structure. The construction algorithm takes O(n ω log d) time, where ω is the matrix multiplication exponent. We show that, despite the n ω factor, our engineered implementation takes only a few minutes to finish for million-letter texts. We further show that plugging our method in data analysis applications gives insignificant or no data utility loss. Finally, we show how our technique can be extended to support applications under a realistic adversary model
RasBhari: optimizing spaced seeds for database searching, read mapping and alignment-free sequence comparison
Many algorithms for sequence analysis rely on word matching or word
statistics. Often, these approaches can be improved if binary patterns
representing match and don't-care positions are used as a filter, such that
only those positions of words are considered that correspond to the match
positions of the patterns. The performance of these approaches, however,
depends on the underlying patterns. Herein, we show that the overlap complexity
of a pattern set that was introduced by Ilie and Ilie is closely related to the
variance of the number of matches between two evolutionarily related sequences
with respect to this pattern set. We propose a modified hill-climbing algorithm
to optimize pattern sets for database searching, read mapping and
alignment-free sequence comparison of nucleic-acid sequences; our
implementation of this algorithm is called rasbhari. Depending on the
application at hand, rasbhari can either minimize the overlap complexity of
pattern sets, maximize their sensitivity in database searching or minimize the
variance of the number of pattern-based matches in alignment-free sequence
comparison. We show that, for database searching, rasbhari generates pattern
sets with slightly higher sensitivity than existing approaches. In our Spaced
Words approach to alignment-free sequence comparison, pattern sets calculated
with rasbhari led to more accurate estimates of phylogenetic distances than the
randomly generated pattern sets that we previously used. Finally, we used
rasbhari to generate patterns for short read classification with CLARK-S. Here
too, the sensitivity of the results could be improved, compared to the default
patterns of the program. We integrated rasbhari into Spaced Words; the source
code of rasbhari is freely available at http://rasbhari.gobics.de
Phylogenetic Tree Construction for Starfish and Primate Genomes via Alignment Free Methods
A phylogenetic tree is a tree like diagram showing the evolutionary relationship among various species based on their differences or similarity in their physical or genetic makeup.The similarity in their genetic makeup is traditionally measured based on pairwise distance between their gene sequences using sequence alignment methods. Due to the advancement in next generation sequencing technologies there is a huge amount of datasets available for partially or completely sequenced genomes. These massive datasets requires a faster comparison methods other than the traditional alignment-based approaches. Therefore, alignment free approaches are gaining popularity in recent years. In this thesis, we compare alignment-based and various alignment free methods for phylogenetic tree construction. The alignment free methods we study are based on k-mer frequency, Average Common Substring (ACS) and ACS with position restrictions and mismatches. The position restricted ACS is a novel contribution of this thesis. To evaluate performance of the alignment free approaches we applied it to phylogeny reconstruction using DNA ( 27 primate mitochondrial genomes) and protein (Starfish RNA-seq) sequence sets. The phylogenetic trees are constructed using Neighbor joining to the distance matrices obtained with the above mentioned alignment-free methods. The resulting phylogenetic trees are then compared with the reference tree using Branch Score Distance measure. Both the Neighbor joining and the Branch Score Distance Measure are calculated by using the programs neighbor and treedist from the PHYLIP package
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