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gPCA specifications


Unique identifier OMICS_19780
Name gPCA
Alternative name guided Principal Component Analysis
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License GNU General Public License version 3.0
Computer skills Advanced
Version 1.0
Stability Stable
Source code URL
Maintained Yes




No version available



  • person_outline Jeanette Eckel-Passow
  • person_outline Sarah Reese

Publication for guided Principal Component Analysis

gPCA citations


Comparative Profiling of Ubiquitin Proteasome System Interplay with Influenza A Virus PB2 Polymerase Protein Recapitulating Virus Evolution in Humans

PMCID: 5700371
PMID: 29202037
DOI: 10.1128/mSphere.00330-17

[…] he human UPS shows a number of noticeable benefits allowing the straightforward delivery of high-quality, systematic interaction mapping. It takes advantage of the excellent performance of the PPI HT-GPCA for the specific and sensitive detection of PPIs (, , ). Although the HT-GPCA can tolerate a certain distance between interacting pairs of proteins (, ), it is assumed that the use of a single Gl […]


Multidomain analyses of a longitudinal human microbiome intestinal cleanout perturbation experiment

PLoS Comput Biol
PMCID: 5576755
PMID: 28821012
DOI: 10.1371/journal.pcbi.1005706
call_split See protocol

[…] case that smaller groups of RSVs, say at the genus level, are the relevant units of analysis.To deal with some of these issues, we have developed a new method which we call adaptive generalized PCA (gPCA). The mathematical details and justification are given in a separate paper and R package available on CRAN [, ]. The method was developed in the context of analyzing the data in the present study […]


Maternal smoking impacts key biological pathways in newborns through epigenetic modification in Utero

BMC Genomics
PMCID: 5124223
PMID: 27887572
DOI: 10.1186/s12864-016-3310-1

[…] Ba1, N = 8 MoBa2) were also removed. For each dataset, we accounted for the two different probe designs by applying the intra-array normalization strategy Beta Mixture Quantile dilation (BMIQ) [].The gPCA program was used to determine the presence of batch effects, using plate to represent batch and ComBat was applied for batch correction using the SVA package in R for both MoBa 1 and MoBa 2 cohor […]


Molecular characterization of systemic sclerosis esophageal pathology identifies inflammatory and proliferative signatures

PMCID: 4518531
PMID: 26220546
DOI: 10.1186/s13075-015-0695-1

[…] odule using nonparametric settings []. The statistical significance of batch bias before (p <0.001) and after (p = 0.997) adjustment with ComBat was assessed with guided principal component analysis (gPCA; Additional file ) [].Transcripts that were differentially expressed between patients with and without SSc (unpaired t test) and transcripts differentially expressed between SSc patients’ upper a […]


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gPCA institution(s)
Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA; Biostatistics Shared Resource Core, VCU Massey Cancer Center, Virginia Commonwealth University, Richmond, VA, USA; Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA; Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
gPCA funding source(s)
Supported by National Institutes of Health research grants (R01 HL87660, R01 CA128931, CA140286 and T32 ES007334); Mayo Clinic Center for Individualized Medicine.

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