Evidence map›Paper›PMID 25064564›Full record

ArticleBioinformatics (Oxford, England)2014

Compression and fast retrieval of SNP data.

Francesco Sambo, Barbara Di Camillo, Gianna Toffolo, Claudio Cobelli

Open access · bronzeAbstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.3field-weighted citation impact, top 14% of its field
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

6 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Analysis-ready VCF at Biobank scale using Zarr.bioRxiv : the preprint server for biology · 2025
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  3. Article
  4. IGD: a simple, efficient genotype data format.Bioinformatics advances · 2025
    Article
  5. Article
  6. 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

4 authors at 1 institution in 1 country.

Francesco SamboDepartment of Information Engineering, University of Padova, via Gradenigo 6/a, 35131 Padova, Italy.
Barbara Di CamilloDepartment of Information Engineering, University of Padova, via Gradenigo 6/a, 35131 Padova, Italy.
Gianna ToffoloDepartment of Information Engineering, University of Padova, via Gradenigo 6/a, 35131 Padova, Italy.
Claudio CobelliDepartment of Information Engineering, University of Padova, via Gradenigo 6/a, 35131 Padova, Italy.
University of Padua · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationThe increasing interest in rare genetic variants and epistatic genetic effects on complex phenotypic traits is currently pushing genome-wide association study design towards datasets of increasing size, both in the number of studied subjects and in the number of genotyped single nucleotide polymorphisms (SNPs). This, in turn, is leading to a compelling need for new methods for compression and fast retrieval of SNP data.

resultsWe present a novel algorithm and file format for compressing and retrieving SNP data, specifically designed for large-scale association studies. Our algorithm is based on two main ideas: (i) compress linkage disequilibrium blocks in terms of differences with a reference SNP and (ii) compress reference SNPs exploiting information on their call rate and minor allele frequency. Tested on two SNP datasets and compared with several state-of-the-art software tools, our compression algorithm is shown to be competitive in terms of compression rate and to outperform all tools in terms of time to load compressed data. AVAILABILITY AND IMPLEMENTATION: Our compression and decompression algorithms are implemented in a C++ library, are released under the GNU General Public License and are freely downloadable from http://www.dei.unipd.it/~sambofra/snpack.html.

Indexed as

AlgorithmsPolymorphism, Single NucleotideData CompressionGene FrequencyGenome-Wide Association StudyHumansLinkage DisequilibriumSoftware

Identifiers

PMID25064564
PMCPMC4609015
OpenAlexW2106935424

What OpenQuestion holds

Textmetadata
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.