Evidence map›Paper›PMID 21342554›Full record

ArticleBMC bioinformatics2011

Strobe sequence design for haplotype assembly.

Christine Lo, Ali Bashir, Vikas Bansal, Vineet Bafna

Abstract read
In one paragraph

Article in BMC bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
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  3. Article
  4. Review
  5. Article
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  11. Stepping stones in DNA sequencing.Biotechnology journal · 2012
    Review
  12. Review
  13. Article
  14. 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.

Christine LoDepartment of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92093, USA. cylo@cs.ucsd.edu
Ali Bashir
Vikas Bansal
Vineet Bafna

Funding

iDASH: Integrating Data for Analysis, Anonymization, and SharingU54HL108460 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI OHNO-MACHADO, LUCILA · 2010 to 2015
$19.1M
Algorithmic strategies for detecting structural variation in genomesR01HG004962 · NHGRI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BAFNA, VINEET · 2009 to 2012
$1.3M
NHGRI NIH HHS R01 HG004962NHGRI NIH HHS R01-HG004962NHLBI NIH HHS 5U54HL108460
6 · The paper itself

Abstract

backgroundHumans are diploid, carrying two copies of each chromosome, one from each parent. Separating the paternal and maternal chromosomes is an important component of genetic analyses such as determining genetic association, inferring evolutionary scenarios, computing recombination rates, and detecting cis-regulatory events. As the pair of chromosomes are mostly identical to each other, linking together of alleles at heterozygous sites is sufficient to phase, or separate the two chromosomes. In Haplotype Assembly, the linking is done by sequenced fragments that overlap two heterozygous sites. While there has been a lot of research on correcting errors to achieve accurate haplotypes via assembly, relatively little work has been done on designing sequencing experiments to get long haplotypes. Here, we describe the different design parameters that can be adjusted with next generation and upcoming sequencing technologies, and study the impact of design choice on the length of the haplotype.

resultsWe show that a number of parameters influence haplotype length, with the most significant one being the advance length (distance between two fragments of a clone). Given technologies like strobe sequencing that allow for large variations in advance lengths, we design and implement a simulated annealing algorithm to sample a large space of distributions over advance-lengths. Extensive simulations on individual genomic sequences suggest that a non-trivial distribution over advance lengths results a 1-2 order of magnitude improvement in median haplotype length.

conclusionsOur results suggest that haplotyping of large, biologically important genomic regions is feasible with current technologies.

Indexed as

AlgorithmsHaplotypesComputational BiologyGenome, HumanGenomicsHumansPolymorphism, Single NucleotideSequence Analysis, DNA

Identifiers

PMID21342554
PMCPMC3044279

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Registered trials

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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.