Evidence map›Paper›PMID 24899342›Full record

ArticleGenome research2014

A cloud-compatible bioinformatics pipeline for ultrarapid pathogen identification from next-generation sequencing of clinical samples.

Samia N Naccache, Scot Federman, Narayanan Veeraraghavan, Matei Zaharia, Deanna Lee, Erik Samayoa, Jerome Bouquet, Alexander L Greninger, Ka-Cheung Luk, Barryett Enge and 16 more

3 registry-linked trialsOpen access · bronzeAbstract read
In one paragraph

Article in Genome research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 3 registered trials, which are not on this map. Cited by 268 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
268citing papers in PubMed, 1 pooled it
–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.

NCT02910037 nacompletednot on this mapstarted 2016, after this paper: background citation

Clinical Implementation of Metagenomic Next-Generation Sequencing for Precision Diagnosis of Acute Infectious Diseases; Neuroinflammatory Cohort

TypeinterventionalSponsorUniversity of California, San FranciscoRan2016 to 2017Enrolled214ConditionsEncephalitis, MeningitisArmsmNGS for pathogen detection
NCT05085158 unknown statusnot on this mapstarted 2023, after this paper: background citation

Pathogen Detection in HIV-infected Children and Adolescents With Non-malarial Febrile Illnesses Using Metagenomic Next-generation Sequencing Approach in Uganda

TypeobservationalSponsorMakerere UniversityRan2023 to 2024Enrolled138ConditionsHIV Infection
NCT07626073 enrolling by invitationnot on this mapstarted 2023, after this paper: background citation

h Can Provide the Detection Results of Pathogen Type and Resistant Gene. This Study is a Prospective Multi Centers Study to Explore Using the New Diagnostic Tool of " RPIP " and the Different Detection Methods of Next Generation Sequencing and Multiplex PC R in Patients With Pneumonia in ICU. Further Compare the Difference of Pathogen Identification and Clinical Impact by Different Diagnostic Methods.

Typeobservational_patient_registrySponsorChina Medical University HospitalRan2023 to 2028Enrolled200ConditionsRespiratory Pathogens
3 · Its place in the literature

Who cites it

268 citing papers in PubMed, 1 synthesis or guideline pooled it, 488 citations in OpenAlex.

  1. Pooled it
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  16. Observational
  17. Pathological and immune features of non-tuberculous mycobacteria andFrontiers in cellular and infection microbiology · 2025
    Article
  18. Frontiers in microbiology · 2025
    Article
  19. HPD-Kit: a comprehensive toolkit for pathogen detection and analysis.Frontiers in cellular and infection microbiology · 2025
    Article
  20. Review

208 more citing papers are in PubMed but not listed here.

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

26 authors at 8 institutions in 5 countries.

Samia N NaccacheDepartment of Laboratory Medicine, UCSF, San Francisco, California 94107, USA; UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, California 94107, USA;
Scot FedermanDepartment of Laboratory Medicine, UCSF, San Francisco, California 94107, USA; UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, California 94107, USA;
Narayanan VeeraraghavanDepartment of Laboratory Medicine, UCSF, San Francisco, California 94107, USA; UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, California 94107, USA;
Matei ZahariaDepartment of Computer Science, University of California, Berkeley, California 94720, USA;
Deanna LeeDepartment of Laboratory Medicine, UCSF, San Francisco, California 94107, USA; UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, California 94107, USA;
Erik SamayoaDepartment of Laboratory Medicine, UCSF, San Francisco, California 94107, USA; UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, California 94107, USA;
Jerome BouquetDepartment of Laboratory Medicine, UCSF, San Francisco, California 94107, USA; UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, California 94107, USA;
Alexander L GreningerDepartment of Biochemistry, UCSF, San Francisco, California 94107, USA;
Ka-Cheung LukAbbott Diagnostics, Abbott Park, Illinois 60064, USA;
Barryett EngeViral and Rickettsial Disease Laboratory, California Department of Public Health, Richmond, California 94804, USA;
Debra A WadfordViral and Rickettsial Disease Laboratory, California Department of Public Health, Richmond, California 94804, USA;
Sharon L MessengerViral and Rickettsial Disease Laboratory, California Department of Public Health, Richmond, California 94804, USA;
Gillian L GenrichDepartment of Laboratory Medicine, UCSF, San Francisco, California 94107, USA;
Kristen PellegrinoDepartment of Family and Community Medicine, UCSF, San Francisco, California 94143, USA;
Gilda GrardViral Emergent Diseases Unit, Centre International de Recherches Médicales de Franceville, Franceville, BP 769, Gabon;
Eric LeroyViral Emergent Diseases Unit, Centre International de Recherches Médicales de Franceville, Franceville, BP 769, Gabon;
Bradley S SchneiderMetabiota, Inc., San Francisco, California 94104, USA;
Joseph N FairMetabiota, Inc., San Francisco, California 94104, USA;
Miguel A MartínezDepartamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, 62260, Mexico;
Pavel IsaDepartamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, 62260, Mexico;
John A CrumpDivision of Infectious Diseases and International Health and the Duke Global Health Institute, Duke University Medical Center, Durham, North Carolina 27708, USA; Kilimanjaro Christian Medical Centre, Moshi, Kilimanjaro, 7393, Tanzania; Centre for International Health, University of Otago, Dunedin, 9054, New Zealand;
Joseph L DeRisiDepartment of Biochemistry, UCSF, San Francisco, California 94107, USA;
Taylor SittlerDepartment of Laboratory Medicine, UCSF, San Francisco, California 94107, USA;
John HackettAbbott Diagnostics, Abbott Park, Illinois 60064, USA;
Steve MillerDepartment of Laboratory Medicine, UCSF, San Francisco, California 94107, USA; UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, California 94107, USA;
Charles Y ChiuDepartment of Laboratory Medicine, UCSF, San Francisco, California 94107, USA; UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, California 94107, USA; Department of Medicine, Division of Infectious Diseases, UCSF, San Francisco, California 94143, USA.
University of California, San Francisco · USCalifornia Department of Public Health · USAbbott (United States) · USCentre International de Recherches Médicales de Franceville · GAMetabiota (United States) · USUniversidad Nacional Autónoma de México · MXDuke Medical Center · USUniversity of California, Berkeley · US

Funding

MEDICAL SCIENTIST TRAINING PROGRAMT32GM007618 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ANDERSON, MARK S · 1985 to 2020
$29.6M
Pan-Genomic Approaches for Comprehensive Blood Screening of Novel or Emerging Infectious AgentsR01HL105704 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CHIU, CHARLES YEN · 2011 to 2020
$5.9M
NHLBI NIH HHS R01 HL105704NIGMS NIH HHS T32 GM007618
6 · The paper itself

Abstract

Unbiased next-generation sequencing (NGS) approaches enable comprehensive pathogen detection in the clinical microbiology laboratory and have numerous applications for public health surveillance, outbreak investigation, and the diagnosis of infectious diseases. However, practical deployment of the technology is hindered by the bioinformatics challenge of analyzing results accurately and in a clinically relevant timeframe. Here we describe SURPI ("sequence-based ultrarapid pathogen identification"), a computational pipeline for pathogen identification from complex metagenomic NGS data generated from clinical samples, and demonstrate use of the pipeline in the analysis of 237 clinical samples comprising more than 1.1 billion sequences. Deployable on both cloud-based and standalone servers, SURPI leverages two state-of-the-art aligners for accelerated analyses, SNAP and RAPSearch, which are as accurate as existing bioinformatics tools but orders of magnitude faster in performance. In fast mode, SURPI detects viruses and bacteria by scanning data sets of 7-500 million reads in 11 min to 5 h, while in comprehensive mode, all known microorganisms are identified, followed by de novo assembly and protein homology searches for divergent viruses in 50 min to 16 h. SURPI has also directly contributed to real-time microbial diagnosis in acutely ill patients, underscoring its potential key role in the development of unbiased NGS-based clinical assays in infectious diseases that demand rapid turnaround times.

Indexed as

High-Throughput Nucleotide SequencingComputational BiologyDatabases, Nucleic AcidHumansMetagenomicsReproducibility of ResultsROC CurveSoftware

Identifiers

PMID24899342
PMCPMC4079973
OpenAlexW2137662380

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

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.