MetaOmics statistics

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Citations per year

Number of citations per year for the bioinformatics software tool MetaOmics
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Tool usage distribution map

This map represents all the scientific publications referring to MetaOmics per scientific context
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Associated diseases

This word cloud represents MetaOmics usage per disease context
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Protocols

MetaOmics specifications

Information


Unique identifier OMICS_04031
Name MetaOmics
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License Apache License version 2.0
Computer skills Advanced
Version 0.3.4
Stability Stable
Maintained Yes

Subtools


  • CPI
  • MetaClust
  • MetaPredict

Download


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Versioning


No version available

Documentation


Maintainer


  • person_outline George Tseng

Additional information


http://www.pitt.edu/~tsengweb/MetaOmicsFAQ.htm

Publications for MetaOmics

MetaOmics citations

 (23)
library_books

Small RNA profiling of low biomass samples: identification and removal of contaminants

2018
BMC Biol
PMCID: 5952572
PMID: 29759067
DOI: 10.1186/s12915-018-0522-7

[…] rom sRNA sequencing of column eluates and the plasma titration experiment, as well as preparation of the figures are available at 10.5281/zenodo.1209974 and are also available from https://git.ufz.de/metaOmics/contaminomics. Accessions of publically available data analysed during the current study are listed in Additional file : Table S1. Individual data values for Figs. , and are listed in Addi […]

library_books

Host Microbe Interactions in Airway Disease: toward Disease Mechanisms and Novel Therapeutic Strategies

2018
mSystems
PMCID: 5850075
PMID: 29556535
DOI: 10.1128/mSystems.00158-17

[…] rred differences in murine Th2 and Th17 cell expansion and epidermal thickening (). I anticipate that, as the cost of high-throughput sequencing and mass spectrometry continues to decline, functional metaomics will become more accessible on limited scientific and clinical budgets and will play a central role in advancing our understanding of the role of the microbiota in human disease.A second goa […]

library_books

Feature genes in metastatic breast cancer identified by MetaDE and SVM classifier methods

2018
PMCID: 5802200
PMID: 29328377
DOI: 10.3892/mmr.2018.8398

[…] ritical regulator for the metastatic process (). Comprehensive understanding of metastasis progression is very important for identifying novel therapeutic strategies to prevent metastatic disease.The MetaOmics software in R language is comprised of the MetaDE, MetaQC and MetaPath packages. The MetaDE package primarily contains 12 state-of-the-art genomic meta-analysis methods to detect differentia […]

library_books

HipMCL: a high performance parallel implementation of the Markov clustering algorithm for large scale networks

2018
Nucleic Acids Res
PMCID: 5888241
PMID: 29315405
DOI: 10.1093/nar/gkx1313

[…] irwise similarities above 30% and at 70% length coverage bidirectionally for all the predicted proteins of the isolate genomes stored in IMG (Isolates 1, 2 and 3) and (ii) similarities of proteins in Metaclust50 (https://metaclust.mmseqs.com/) dataset which contains predicted genes from metagenomes and metatranscriptomes of assembled contigs from IMG/M and NCBI. For the three isolate datasets, we […]

library_books

Evidence for widespread dysregulation of circadian clock progression in human cancer

2018
PeerJ
PMCID: 5797448
PMID: 29404219
DOI: 10.7717/peerj.4327

[…] ipt IDs and Entrez Gene IDs to calculate gene-level abundances.For the remaining datasets, raw (in the case of Affymetrix) or processed microarray data were obtained from NCBI GEO and processed using MetaPredict, which maps probes to Entrez Gene IDs and performs intra-study normalization and log-transformation (). MetaPredict processes raw Affymetrix data using RMA and customCDFs (; ). As in our p […]

library_books

A Practical and Time Efficient High Intensity Interval Training Program Modifies Cardio Metabolic Risk Factors in Adults with Risk Factors for Type II Diabetes

2017
PMCID: 5596071
PMID: 28943861
DOI: 10.3389/fendo.2017.00229

[…] For the METAPREDICT HIT trial, we recruited 189 participants (Figure ) across 5 geographical regions: Nottingham (n = 37) and Loughborough (n = 18) in the UK, Stockholm (Sweden, n = 36), Copenhagen (Denmark, […]


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MetaOmics institution(s)
Departments of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Epidemiology and Biostatistics, University of Maryland, College Park, MD, USA; Department of Biostatistics, University of Florida, Gainesville, FL, USA; School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA; Division of Biostatistics, Medical College of Wisconsin, Milwaukee, WI, USA; Departments of Pathology, University of Pittsburgh, Pittsburgh, PA, USA; School of Statistics, Capital University of Economics and Business, China; Department of Mathematical Sciences, Florida Atlantic University, Boca Raton, FL, USA; Department of Statistics, Keimyung University, Korea; Henry Ford Health System, USA; Division of Biostatistics, Ohio State University, OH, USA; Department of Pharmacology & Chemical Biology, University of Pittsburgh, Pittsburgh, PA, USA; Centre for Addiction and Mental Health, University of Toronto, Toronto, ON, Canada
MetaOmics funding source(s)
Supported by NCI of the National Institutes of Health under award number R01CA190766 and by National Nature Science Foundation of China (11701391).

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