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Bitpacking techniques for indexing genomes: I. Hash tables

Overview of attention for article published in Algorithms for Molecular Biology, April 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#27 of 197)
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

twitter
11 tweeters
googleplus
1 Google+ user

Citations

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3 Dimensions

Readers on

mendeley
28 Mendeley
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Title
Bitpacking techniques for indexing genomes: I. Hash tables
Published in
Algorithms for Molecular Biology, April 2016
DOI 10.1186/s13015-016-0069-5
Pubmed ID
Authors

Thomas D. Wu, Wu, Thomas D

Abstract

Hash tables constitute a widely used data structure for indexing genomes that provides a list of genomic positions for each possible oligomer of a given size. The offset array in a hash table grows exponentially with the oligomer size and precludes the use of larger oligomers that could facilitate rapid alignment of sequences to a genome. We propose to compress the offset array using vectorized bitpacking. We introduce an algorithm and data structure called BP64-columnar that achieves fast random access in arrays of monotonically nondecreasing integers. Experimental results based on hash tables for the fly, chicken, and human genomes show that BP64-columnar is 3 to 4 times faster than publicly available implementations of universal coding schemes, such as Elias gamma, Elias delta, and Fibonacci compression. Furthermore, among vectorized bitpacking schemes, our BP64-columnar format yields retrieval times that are faster than the fastest known bitpacking format by a factor of 3 for retrieving a single value, and a factor of 2 for retrieving two adjacent values. Our BP64-columnar scheme enables compression of genomic hash tables with fast retrieval. It also has potential applications to other domains requiring differential coding with random access.

Twitter Demographics

The data shown below were collected from the profiles of 11 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Korea, Republic of 1 4%
France 1 4%
Luxembourg 1 4%
Unknown 25 89%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 21%
Student > Ph. D. Student 5 18%
Researcher 5 18%
Student > Master 4 14%
Professor > Associate Professor 2 7%
Other 4 14%
Unknown 2 7%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 13 46%
Agricultural and Biological Sciences 6 21%
Computer Science 3 11%
Environmental Science 1 4%
Engineering 1 4%
Other 0 0%
Unknown 4 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 July 2016.
All research outputs
#2,310,275
of 13,200,341 outputs
Outputs from Algorithms for Molecular Biology
#27
of 197 outputs
Outputs of similar age
#60,004
of 263,693 outputs
Outputs of similar age from Algorithms for Molecular Biology
#3
of 9 outputs
Altmetric has tracked 13,200,341 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 197 research outputs from this source. They receive a mean Attention Score of 3.0. This one has done well, scoring higher than 86% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 263,693 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.