Evidence map›Paper›PMID 23918251›Full record

ArticleBioinformatics (Oxford, England)2013

Distilled single-cell genome sequencing and de novo assembly for sparse microbial communities.

Zeinab Taghavi, Narjes S Movahedi, Sorin Draghici, Hamidreza Chitsaz

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Graph Traversal Edit Distance and Extensions.Journal of computational biology : a journal of computational molecular cell biology · 2020
    Article
  2. Efficient Synergistic Single-Cell Genome Assembly.Frontiers in bioengineering and biotechnology · 2016
    Article
  3. Article
  4. 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.

Zeinab TaghaviDepartment of Computer Science and Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI 48202, USA.
Narjes S Movahedi
Sorin Draghici
Hamidreza Chitsaz

Funding

Pathway-Guide: A novel tool for the analysis of signaling and metabolic pathwaysR42GM087013 · NIGMS · ADVAITA CORPORATION · PI DRAGHICI, SORIN · 2011 to 2013
$2.2M
Novel methods for the analysis of gene signaling pathways with applications in obR01DK089167 · NIDDK · WAYNE STATE UNIVERSITY · PI DRAGHICI, SORIN · 2010 to 2013
$1.2M
NIDDK NIH HHS R01 DK089167NIGMS NIH HHS R42GM087013
6 · The paper itself

Abstract

motivationIdentification of every single genome present in a microbial sample is an important and challenging task with crucial applications. It is challenging because there are typically millions of cells in a microbial sample, the vast majority of which elude cultivation. The most accurate method to date is exhaustive single-cell sequencing using multiple displacement amplification, which is simply intractable for a large number of cells. However, there is hope for breaking this barrier, as the number of different cell types with distinct genome sequences is usually much smaller than the number of cells.

resultsHere, we present a novel divide and conquer method to sequence and de novo assemble all distinct genomes present in a microbial sample with a sequencing cost and computational complexity proportional to the number of genome types, rather than the number of cells. The method is implemented in a tool called Squeezambler. We evaluated Squeezambler on simulated data. The proposed divide and conquer method successfully reduces the cost of sequencing in comparison with the naïve exhaustive approach. AVAILABILITY: Squeezambler and datasets are available at http://compbio.cs.wayne.edu/software/squeezambler/.

Indexed as

Genome, MicrobialAlgorithmsBase SequenceHumansIntestinesSequence Analysis, DNASequence Homology, Nucleic Acid

Identifiers

PMID23918251
PMCPMC3777112

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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.