Evidence map›Paper›PMID 27095998›Full record

ArticleAlgorithms for molecular biology : AMB2016

Bitpacking techniques for indexing genomes: I. Hash tables.

Thomas D Wu

Abstract read
In one paragraph

Article in Algorithms for molecular biology : AMB, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Thomas D WuDepartment of Bioinformatics and Computational Biology, Genentech, Inc., 1 DNA Way, 94080, South San Francisco, CA 94080 USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHash 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.

resultsWe 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.

conclusionsOur 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.

Indexed as

Data compressionGenomicsHash tableSequence alignment

Identifiers

PMID27095998
PMCPMC4835851

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.