Evidence map›Paper›PMID 31482150›Full record

ArticleJournal of biomedical informatics: X2019

CCMP: software-as-a-service approach for fully-automated microbiome profiling.

Sung Yong Park, Sayan Nanda, Gina Faraci, Younghu Park, Ha Youn Lee

Abstract read
In one paragraph

Article in Journal of biomedical informatics: X, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing 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.

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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

5 authors.

Sung Yong ParkDepartment of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Sayan NandaDepartment of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Gina FaraciDepartment of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Younghu ParkDepartment of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Ha Youn LeeDepartment of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.

Funding

HIV Incidence Assay via Deep Sequencing and Statistical TestsR01AI095066 · NIAID · UNIVERSITY OF SOUTHERN CALIFORNIA · PI LEE, HA YOUN · 2011 to 2025
$8.4M
Simulator for Primary HIV Replication and EvolutionR01AI083115 · NIAID · UNIVERSITY OF SOUTHERN CALIFORNIA · PI LEE, HA YOUN · 2009 to 2017
$3.9M
NIAID NIH HHS R01 AI083115NIAID NIH HHS R01 AI095066
6 · The paper itself

Abstract

Microbiome profiling holds great promise for the development of novel disease biomarkers and therapeutics. Next-generation sequencing is currently the preferred method for microbiome data collection and multiple standardized tools, packages, and pipelines have been developed for the purpose of raw data processing and microbial annotation. However, these currently available pipelines come with entry-level barriers such as high-performance hardware, software installation, and sequential command-line scripting that often deter end-users. We thus created Cloud Computing for Microbiome Profiling (CCMP, https://ccmp.usc.edu), a public cloud-based web tool which combines the analytical power of current microbiome analysis platforms with a user-friendly interface. CCMP is a free-of-charge software-as-a-service (SaaS) that simplifies user experience by enabling users to complete their analysis in a single step, uploading raw sequencing data files. Once users upload 16S ribosomal RNA gene sequence data, our pipeline performs taxonomic annotation, abundance profiling, and statistical tests to report microbiota signatures altered by diseases or experimental conditions. CCMP took a 125 gigabyte (GB) input of 16S ribosomal RNA gene sequence data from 1052 specimens in FASTQ format and reported figures and tables of taxonomic annotations, statistical tests,

Identifiers

PMID31482150
PMCPMC6719681

What OpenQuestion holds

Textmetadata
LicenceTDM
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.