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Hobbes: a Gram-Based Read Aligner.
~
Honnalli, Nagesh V.
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Hobbes: a Gram-Based Read Aligner.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Hobbes: a Gram-Based Read Aligner./
作者:
Honnalli, Nagesh V.
面頁冊數:
62 p.
附註:
Source: Masters Abstracts International, Volume: 49-06, page: .
Contained By:
Masters Abstracts International49-06.
標題:
Biology, Bioinformatics. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1493961
ISBN:
9781124675350
Hobbes: a Gram-Based Read Aligner.
Honnalli, Nagesh V.
Hobbes: a Gram-Based Read Aligner.
- 62 p.
Source: Masters Abstracts International, Volume: 49-06, page: .
Thesis (M.S.)--University of California, Irvine, 2011.
Read alignment is an essential tool in a sequence analyst's repertoire as it is used in applications like genome sequence variation, RNA splicing, ChipSeq, etc. Hundreds of gigabytes of data is generated every day, owing to the newer sequencing technologies used by machines like Illumina, Roche and HeliScope. Mapping billions of read sequences to large reference sequences is a challenging computational problem. Many existing solutions use either a gram-based or a tree-based approach to solve it. In this thesis, we present a q-gram based read aligner, called Hobbes, which implements two novel techniques. We introduce a judicious way of selecting q-grams and a powerful filter called bitvector filter. These two techniques combined with several implementation-level optimizations substantially improve the mapping time. Experiments show that Hobbes maps reads significantly faster than Bowtie and BWA across different read lengths, number of reads, reference-sequence lengths, number of mappings per read and hamming distance thresholds. Increasing the size of the bitvector filter improves the mapping time at the cost of index size. Nowadays, where larger memory is becoming more affordable by the day, we believe, a sequence analyst's objective is to spend as less CPU hours at read mapping as possible, with the cost of memory being less of a concern. Hobbes is available at http://hobbes.ics.uci.edu.
ISBN: 9781124675350Subjects--Topical Terms:
1018415
Biology, Bioinformatics.
Hobbes: a Gram-Based Read Aligner.
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Read alignment is an essential tool in a sequence analyst's repertoire as it is used in applications like genome sequence variation, RNA splicing, ChipSeq, etc. Hundreds of gigabytes of data is generated every day, owing to the newer sequencing technologies used by machines like Illumina, Roche and HeliScope. Mapping billions of read sequences to large reference sequences is a challenging computational problem. Many existing solutions use either a gram-based or a tree-based approach to solve it. In this thesis, we present a q-gram based read aligner, called Hobbes, which implements two novel techniques. We introduce a judicious way of selecting q-grams and a powerful filter called bitvector filter. These two techniques combined with several implementation-level optimizations substantially improve the mapping time. Experiments show that Hobbes maps reads significantly faster than Bowtie and BWA across different read lengths, number of reads, reference-sequence lengths, number of mappings per read and hamming distance thresholds. Increasing the size of the bitvector filter improves the mapping time at the cost of index size. Nowadays, where larger memory is becoming more affordable by the day, we believe, a sequence analyst's objective is to spend as less CPU hours at read mapping as possible, with the cost of memory being less of a concern. Hobbes is available at http://hobbes.ics.uci.edu.
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