Peter Langfelder

Summary

Publications

  1. pmc Genetic analysis of DNA methylation and gene expression levels in whole blood of healthy human subjects
    Kristel R van Eijk
    Department of Medical Genetics, University Medical Center Utrecht, Utrecht 3584, CG, The Netherlands
    BMC Genomics 13:636. 2012
  2. pmc A systems genetic analysis of high density lipoprotein metabolism and network preservation across mouse models
    Peter Langfelder
    Department of Human Genetics, David Geffen School of Medicine at UCLA, Gonda Goldschmied Neuroscience and Genetics Research Center, 695 Charles E Young Drive South, Box 708822, Los Angeles, CA 90095 7088, USA
    Biochim Biophys Acta 1821:435-47. 2012
  3. pmc Weighted gene co-expression network analysis of the peripheral blood from Amyotrophic Lateral Sclerosis patients
    Christiaan G J Saris
    Department of Neurology, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht 3584 CX, The Netherlands
    BMC Genomics 10:405. 2009
  4. pmc Eigengene networks for studying the relationships between co-expression modules
    Peter Langfelder
    Department of Human Genetics and Department of Biostatistics, University of California, Los Angeles, CA 90095, USA
    BMC Syst Biol 1:54. 2007
  5. pmc WGCNA: an R package for weighted correlation network analysis
    Peter Langfelder
    Department of Human Genetics and Department of Biostatistics, University of California, Los Angeles, CA 90095, USA
    BMC Bioinformatics 9:559. 2008
  6. pmc Strategies for aggregating gene expression data: the collapseRows R function
    Jeremy A Miller
    Interdepartmental Program for Neuroscience, UCLA, Los Angeles, California, USA
    BMC Bioinformatics 12:322. 2011
  7. pmc Cluster and propensity based approximation of a network
    John Michael Ranola
    Biomathematics, University of California, Los Angeles, CA, USA
    BMC Syst Biol 7:21. 2013
  8. pmc Network methods for describing sample relationships in genomic datasets: application to Huntington's disease
    Michael C Oldham
    Department of Neurology, The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, USA
    BMC Syst Biol 6:63. 2012
  9. pmc Random generalized linear model: a highly accurate and interpretable ensemble predictor
    Lin Song
    Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, California, USA
    BMC Bioinformatics 14:5. 2013
  10. pmc Transcriptome analysis of HIV-infected peripheral blood monocytes: gene transcripts and networks associated with neurocognitive functioning
    Andrew J Levine
    Department of Neurology, National Neurological AIDS Bank, David Geffen School of Medicine, University of California, Los Angeles, United States Electronic address
    J Neuroimmunol 265:96-105. 2013

Collaborators

Detail Information

Publications17

  1. pmc Genetic analysis of DNA methylation and gene expression levels in whole blood of healthy human subjects
    Kristel R van Eijk
    Department of Medical Genetics, University Medical Center Utrecht, Utrecht 3584, CG, The Netherlands
    BMC Genomics 13:636. 2012
    ..However, recent studies suggest that the relationship between genetic variation, DNA methylation and expression is more complex...
  2. pmc A systems genetic analysis of high density lipoprotein metabolism and network preservation across mouse models
    Peter Langfelder
    Department of Human Genetics, David Geffen School of Medicine at UCLA, Gonda Goldschmied Neuroscience and Genetics Research Center, 695 Charles E Young Drive South, Box 708822, Los Angeles, CA 90095 7088, USA
    Biochim Biophys Acta 1821:435-47. 2012
    ..This article is part of a Special Issue entitled Advances in High Density Lipoprotein Formation and Metabolism: A Tribute to John F. Oram (1945-2010)...
  3. pmc Weighted gene co-expression network analysis of the peripheral blood from Amyotrophic Lateral Sclerosis patients
    Christiaan G J Saris
    Department of Neurology, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht 3584 CX, The Netherlands
    BMC Genomics 10:405. 2009
    ..Since access to spinal cord tissue is not possible at disease onset, we investigated changes in gene expression profiles in whole blood of ALS patients...
  4. pmc Eigengene networks for studying the relationships between co-expression modules
    Peter Langfelder
    Department of Human Genetics and Department of Biostatistics, University of California, Los Angeles, CA 90095, USA
    BMC Syst Biol 1:54. 2007
    ..Ample literature exists on how to detect biologically meaningful modules in networks but there is a need for methods that allow one to study the relationships between modules...
  5. pmc WGCNA: an R package for weighted correlation network analysis
    Peter Langfelder
    Department of Human Genetics and Department of Biostatistics, University of California, Los Angeles, CA 90095, USA
    BMC Bioinformatics 9:559. 2008
    ..While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial...
  6. pmc Strategies for aggregating gene expression data: the collapseRows R function
    Jeremy A Miller
    Interdepartmental Program for Neuroscience, UCLA, Los Angeles, California, USA
    BMC Bioinformatics 12:322. 2011
    ..Several standard statistical summary techniques can be used, but network methods also provide useful alternative methods to find representatives. Currently few collapsing functions are developed and widely applied...
  7. pmc Cluster and propensity based approximation of a network
    John Michael Ranola
    Biomathematics, University of California, Los Angeles, CA, USA
    BMC Syst Biol 7:21. 2013
    ..Multigraph networks are attractive because they support likelihood based inference. Unfortunately, it is unclear how to adjust current statistical methods to detect the clusters inherent in many data sets...
  8. pmc Network methods for describing sample relationships in genomic datasets: application to Huntington's disease
    Michael C Oldham
    Department of Neurology, The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, USA
    BMC Syst Biol 6:63. 2012
    ..Consequently, the full extent of sample variation in genomic studies is often under-appreciated, complicating downstream analytical tasks such as gene co-expression network analysis...
  9. pmc Random generalized linear model: a highly accurate and interpretable ensemble predictor
    Lin Song
    Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, California, USA
    BMC Bioinformatics 14:5. 2013
    ..Since limited evaluations suggested that these ensemble predictors were less accurate than alternative predictors, they have found little attention in the literature...
  10. pmc Transcriptome analysis of HIV-infected peripheral blood monocytes: gene transcripts and networks associated with neurocognitive functioning
    Andrew J Levine
    Department of Neurology, National Neurological AIDS Bank, David Geffen School of Medicine, University of California, Los Angeles, United States Electronic address
    J Neuroimmunol 265:96-105. 2013
    ..We hypothesized that transcriptome changes in peripheral blood monocytes relate to neurocognitive functioning in HIV+ individuals, and that such alterations could be useful as biomarkers of worsening HAND...
  11. pmc Is human blood a good surrogate for brain tissue in transcriptional studies?
    Chaochao Cai
    Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
    BMC Genomics 11:589. 2010
    ..We tested this hypothesis by relating three human brain expression data sets (from cortex, cerebellum and caudate nucleus) to two large human blood expression data sets (comprised of 1463 individuals)...
  12. pmc Is my network module preserved and reproducible?
    Peter Langfelder
    Department of Human Genetics, University of California, Los Angeles, Los Angeles, California, United States of America
    PLoS Comput Biol 7:e1001057. 2011
    ..Data, R software and accompanying tutorials can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/ModulePreservation...
  13. pmc Comparison of co-expression measures: mutual information, correlation, and model based indices
    Lin Song
    Human Genetics, David Geffen School of Medicine, University of California, California, Los Angeles, USA
    BMC Bioinformatics 13:328. 2012
    ..Further, it is important to assess what transformations of these and other co-expression measures lead to biologically meaningful modules (clusters of genes)...
  14. pmc Functional organization of the transcriptome in human brain
    Michael C Oldham
    Interdepartmental Program for Neuroscience, University of California Los Angeles, Los Angeles, California 90095, USA
    Nat Neurosci 11:1271-82. 2008
    ..Our findings provide a new foundation for neurogenetic inquiries by revealing a robust and previously unrecognized organization to the human brain transcriptome...
  15. pmc When is hub gene selection better than standard meta-analysis?
    Peter Langfelder
    Department of Human Genetics, University of California Los Angeles, Los Angeles, California, United States of America
    PLoS ONE 8:e61505. 2013
    ..The article also reports a comparison of meta-analysis techniques applied to gene expression data and presents novel R functions for carrying out consensus network analysis, network based screening, and meta analysis...
  16. pmc Gene networks associated with conditional fear in mice identified using a systems genetics approach
    Christopher C Park
    Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
    BMC Syst Biol 5:43. 2011
    ..To explore the genetic networks governing the biology of conditional fear, we used a systems genetics approach to analyze a hybrid mouse diversity panel (HMDP) with high mapping resolution...
  17. ncbi request reprint Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R
    Peter Langfelder
    Department of Human Genetics, University of California at Los Angeles, CA 90095 7088, USA
    Bioinformatics 24:719-20. 2008
    ..We illustrate the use of these methods by applying them to protein-protein interaction network data and to a simulated gene expression data set...