Evidence map›Paper›PMID 22419786›Full record

ArticleBioinformatics (Oxford, England)2012

Fulcrum: condensing redundant reads from high-throughput sequencing studies.

Matthew S Burriesci, Erik M Lehnert, John R Pringle

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Article
  2. Review
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  8. Conducting metagenomic studies in microbiology and clinical research.Applied microbiology and biotechnology · 2018
    Review
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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

3 authors.

Matthew S BurriesciDepartment of Genetics, Stanford University School of Medicine, Stanford, CA 94305-5120, USA.
Erik M Lehnert
John R Pringle

Funding

INSTITUTIONAL TRAINING GRANT IN GENOME SCIENCET32HG000044 · NHGRI · STANFORD UNIVERSITY · PI MICHAEL P. SNYDER · 1995 to 2026
$32.2M
NHGRI NIH HHS 5 T32 HG000044NHGRI NIH HHS T32 HG000044
6 · The paper itself

Abstract

motivationUltra-high-throughput sequencing produces duplicate and near-duplicate reads, which can consume computational resources in downstream applications. A tool that collapses such reads should reduce storage and assembly complications and costs.

resultsWe developed Fulcrum to collapse identical and near-identical Illumina and 454 reads (such as those from PCR clones) into single error-corrected sequences; it can process paired-end as well as single-end reads. Fulcrum is customizable and can be deployed on a single machine, a local network or a commercially available MapReduce cluster, and it has been optimized to maximize ease-of-use, cross-platform compatibility and future scalability. Sequence datasets have been collapsed by up to 71%, and the reduced number and improved quality of the resulting sequences allow assemblers to produce longer contigs while using less memory.

Indexed as

SoftwareAlgorithmsGene Expression ProfilingHigh-Throughput Nucleotide SequencingHumansPseudomonasSequence Analysis, DNA

Identifiers

PMID22419786
PMCPMC3348557

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.