DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: ManiNetCluster: a novel manifold learning approach to reveal the functional links between gene networks

Abstract

BACKGROUND:The coordination of genomic functions is a critical and complex process across biological systems such as phenotypes or states (e.g., time, disease, organism, environmental perturbation). Understanding how the complexity of genomic function relates to these states remains a challenge. To address this, we have developed a novel computational method, ManiNetCluster, which simultaneously aligns and clusters gene networks (e.g., co-expression) to systematically reveal the links of genomic function between different conditions. Specifically, ManiNetCluster employs manifold learning to uncover and match local and non-linear structures among networks, and identifies cross-network functional links. RESULTS:We demonstrated that ManiNetCluster better aligns the orthologous genes from their developmental expression profiles across model organisms than state-of-the-art methods (p-value <2.2×10-16). This indicates the potential non-linear interactions of evolutionarily conserved genes across species in development. Furthermore, we applied ManiNetCluster to time series transcriptome data measured in the green alga Chlamydomonas reinhardtii to discover the genomic functions linking various metabolic processes between the light and dark periods of a diurnally cycling culture. We identified a number of genes putatively regulating processes across each lighting regime. CONCLUSIONS:ManiNetCluster provides a novel computational tool to uncover the genes linking various functions from different networks, providing new insight on how gene functions coordinate acrossmore » different conditions. ManiNetCluster is publicly available as an R package at https://github.com/daifengwanglab/ManiNetCluster.« less

Authors:
 [1]; ORCiD logo [2];  [3]
  1. Stony Brook Univ., NY (United States)
  2. Brookhaven National Lab. (BNL), Upton, NY (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  3. Univ. of Wisconsin, Madison, WI (United States)
Publication Date:
Research Org.:
Brookhaven National Laboratory (BNL), Upton, NY (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1597250
Alternate Identifier(s):
OSTI ID: 1591857
Report Number(s):
BNL-213599-2020-JAAM
Journal ID: ISSN 1471-2164
Grant/Contract Number:  
SC0012704; AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
BMC Genomics
Additional Journal Information:
Journal Volume: 20; Journal Issue: S12; Conference: The International Conference on Intelligent Biology and Medicine (ICIBM) 2019, Columbus, OH (United States), 9-11 Jun 2019; Journal ID: ISSN 1471-2164
Publisher:
Springer
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; Manifold learning; Manifold regularization; Clustering; Multiview learning; Functional genomics; Comparative network analysis; Comparative genomics; Biofuel

Citation Formats

Nguyen, Nam D., Blaby, Ian K., and Wang, Daifeng. ManiNetCluster: a novel manifold learning approach to reveal the functional links between gene networks. United States: N. p., 2019. Web. doi:10.1186/s12864-019-6329-2.
Nguyen, Nam D., Blaby, Ian K., & Wang, Daifeng. ManiNetCluster: a novel manifold learning approach to reveal the functional links between gene networks. United States. https://doi.org/10.1186/s12864-019-6329-2
Nguyen, Nam D., Blaby, Ian K., and Wang, Daifeng. Mon . "ManiNetCluster: a novel manifold learning approach to reveal the functional links between gene networks". United States. https://doi.org/10.1186/s12864-019-6329-2. https://www.osti.gov/servlets/purl/1597250.
@article{osti_1597250,
title = {ManiNetCluster: a novel manifold learning approach to reveal the functional links between gene networks},
author = {Nguyen, Nam D. and Blaby, Ian K. and Wang, Daifeng},
abstractNote = {BACKGROUND:The coordination of genomic functions is a critical and complex process across biological systems such as phenotypes or states (e.g., time, disease, organism, environmental perturbation). Understanding how the complexity of genomic function relates to these states remains a challenge. To address this, we have developed a novel computational method, ManiNetCluster, which simultaneously aligns and clusters gene networks (e.g., co-expression) to systematically reveal the links of genomic function between different conditions. Specifically, ManiNetCluster employs manifold learning to uncover and match local and non-linear structures among networks, and identifies cross-network functional links. RESULTS:We demonstrated that ManiNetCluster better aligns the orthologous genes from their developmental expression profiles across model organisms than state-of-the-art methods (p-value <2.2×10-16). This indicates the potential non-linear interactions of evolutionarily conserved genes across species in development. Furthermore, we applied ManiNetCluster to time series transcriptome data measured in the green alga Chlamydomonas reinhardtii to discover the genomic functions linking various metabolic processes between the light and dark periods of a diurnally cycling culture. We identified a number of genes putatively regulating processes across each lighting regime. CONCLUSIONS:ManiNetCluster provides a novel computational tool to uncover the genes linking various functions from different networks, providing new insight on how gene functions coordinate across different conditions. ManiNetCluster is publicly available as an R package at https://github.com/daifengwanglab/ManiNetCluster.},
doi = {10.1186/s12864-019-6329-2},
journal = {BMC Genomics},
number = S12,
volume = 20,
place = {United States},
year = {Mon Dec 30 00:00:00 EST 2019},
month = {Mon Dec 30 00:00:00 EST 2019}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Citation Metrics:
Cited by: 6 works
Citation information provided by
Web of Science

Save / Share:

Works referenced in this record:

Gene co-expression network topology provides a framework for molecular characterization of cellular state
journal, May 2004


WGCNA: an R package for weighted correlation network analysis
journal, December 2008


Large-scale prediction of long non-coding RNA functions in a coding–non-coding gene co-expression network
journal, January 2011

  • Liao, Qi; Liu, Changning; Yuan, Xiongying
  • Nucleic Acids Research, Vol. 39, Issue 9
  • DOI: 10.1093/nar/gkq1348

Gene co-expression network analysis reveals common system-level properties of prognostic genes across cancer types
journal, February 2014

  • Yang, Yang; Han, Leng; Yuan, Yuan
  • Nature Communications, Vol. 5, Issue 1
  • DOI: 10.1038/ncomms4231

A General Framework for Weighted Gene Co-Expression Network Analysis
journal, January 2005

  • Zhang, Bin; Horvath, Steve
  • Statistical Applications in Genetics and Molecular Biology, Vol. 4, Issue 1
  • DOI: 10.2202/1544-6115.1128

On the selection of appropriate distances for gene expression data clustering
journal, January 2014

  • Jaskowiak, Pablo A.; Campello, Ricardo JGB; Costa, Ivan G.
  • BMC Bioinformatics, Vol. 15, Issue S2
  • DOI: 10.1186/1471-2105-15-S2-S2

Cross-Disciplinary Network Comparison: Matchmaking between Hairballs
journal, March 2016


Gene network interconnectedness and the generalized topological overlap measure
journal, January 2007


OrthoClust: an orthology-based network framework for clustering data across multiple species
journal, January 2014


OrthoCluster: a new tool for mining synteny blocks and applications in comparative genomics
conference, January 2008

  • Zeng, Xinghuo; Nesbitt, Matthew J.; Pei, Jian
  • Proceedings of the 11th international conference on Extending database technology Advances in database technology - EDBT '08
  • DOI: 10.1145/1352431.1352511

A human B‐cell interactome identifies MYB and FOXM1 as master regulators of proliferation in germinal centers
journal, January 2010

  • Lefebvre, Celine; Rajbhandari, Presha; Alvarez, Mariano J.
  • Molecular Systems Biology, Vol. 6, Issue 1
  • DOI: 10.1038/msb.2010.31

A global view of genomic information – moving beyond the gene and the master regulator
journal, January 2010


Simultaneous Clustering of Multiple Gene Expression and Physical Interaction Datasets
journal, April 2010


MAGNA: Maximizing Accuracy in Global Network Alignment
journal, July 2014


MAGNA++: Maximizing Accuracy in Global Network Alignment via both node and edge conservation
journal, March 2015


PrimAlign: PageRank-inspired Markovian alignment for large biological networks
journal, June 2018


IsoRankN: spectral methods for global alignment of multiple protein networks
journal, May 2009


Global alignment of multiple protein interaction networks with application to functional orthology detection
journal, August 2008

  • Singh, R.; Xu, J.; Berger, B.
  • Proceedings of the National Academy of Sciences, Vol. 105, Issue 35
  • DOI: 10.1073/pnas.0806627105

An RKHS for multi-view learning and manifold co-regularization
conference, January 2008

  • Sindhwani, Vikas; Rosenberg, David S.
  • Proceedings of the 25th international conference on Machine learning - ICML '08
  • DOI: 10.1145/1390156.1390279

REGAL: Representation Learning-based Graph Alignment
conference, January 2018

  • Heimann, Mark; Shen, Haoming; Safavi, Tara
  • Proceedings of the 27th ACM International Conference on Information and Knowledge Management - CIKM '18
  • DOI: 10.1145/3269206.3271788

Representation Learning: A Review and New Perspectives
journal, August 2013

  • Bengio, Y.; Courville, A.; Vincent, P.
  • IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 35, Issue 8
  • DOI: 10.1109/TPAMI.2013.50

Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
journal, June 2003


Alignment of single-cell trajectories to compare cellular expression dynamics
journal, March 2018

  • Alpert, Ayelet; Moore, Lindsay S.; Dubovik, Tania
  • Nature Methods, Vol. 15, Issue 4
  • DOI: 10.1038/nmeth.4628

MATCHER: manifold alignment reveals correspondence between single cell transcriptome and epigenome dynamics
journal, July 2017


Testing the manifold hypothesis
journal, February 2016

  • Fefferman, Charles; Mitter, Sanjoy; Narayanan, Hariharan
  • Journal of the American Mathematical Society, Vol. 29, Issue 4
  • DOI: 10.1090/jams/852

Recovering the number of clusters in data sets with noise features using feature rescaling factors
journal, December 2015


The Application of Cluster Analysis in Strategic Management Research: an Analysis and Critique
journal, June 1996


Unlocking the secrets of the genome
journal, June 2009

  • Celniker, Susan E.; Dillon, Laura A. L.; Gerstein, Mark B.
  • Nature, Vol. 459, Issue 7249
  • DOI: 10.1038/459927a

Skeletal representations of orthogonal shapes
journal, July 2013


Proteomic analysis of a eukaryotic cilium
journal, July 2005

  • Pazour, Gregory J.; Agrin, Nathan; Leszyk, John
  • The Journal of Cell Biology, Vol. 170, Issue 1
  • DOI: 10.1083/jcb.200504008

The GreenCut: re-evaluation of physiological role of previously studied proteins and potential novel protein functions
journal, July 2013


The GreenCut2 Resource, a Phylogenomically Derived Inventory of Proteins Specific to the Plant Lineage
journal, April 2011

  • Karpowicz, Steven J.; Prochnik, Simon E.; Grossman, Arthur R.
  • Journal of Biological Chemistry, Vol. 286, Issue 24
  • DOI: 10.1074/jbc.M111.233734

The Chlamydomonas Genome Reveals the Evolution of Key Animal and Plant Functions
journal, October 2007

  • Merchant, S. S.; Prochnik, S. E.; Vallon, O.
  • Science, Vol. 318, Issue 5848, p. 245-250
  • DOI: 10.1126/science.1143609

Assembly of the Light-Harvesting Chlorophyll Antenna in the Green Alga Chlamydomonas reinhardtii Requires Expression of the TLA2 - CpFTSY Gene
journal, November 2011

  • Kirst, Henning; García-Cerdán, Jose Gines; Zurbriggen, Andreas
  • Plant Physiology, Vol. 158, Issue 2
  • DOI: 10.1104/pp.111.189910

Evolution of Chlamydomonas reinhardtii ferredoxins and their interactions with [FeFe]-hydrogenases
journal, June 2017


A survey of multi-view machine learning
journal, February 2013


Statistical single cell multi-omics integration
journal, February 2018


Latent periodic process inference from single-cell RNA-seq data
journal, March 2020


Transcriptional profiling of two contrasting genotypes uncovers molecular mechanisms underlying salt tolerance in alfalfa
journal, March 2021


Unlocking the secrets of the genome
text, January 2009

  • P., White, Kevin; Steven, Henikoff,; Fabio, Piano,
  • The University of North Carolina at Chapel Hill University Libraries
  • DOI: 10.17615/aw2c-np04

On the selection of appropriate distances for gene expression data clustering
text, January 2014


A human B-cell interactome identifies MYB and FOXM1 as master regulators of proliferation in germinal centers
text, January 2010


Representation Learning: A Review and New Perspectives
preprint, January 2012


Testing the Manifold Hypothesis
preprint, January 2013


MAGNA: Maximizing Accuracy in Global Network Alignment
preprint, January 2013


REGAL: Representation Learning-based Graph Alignment
text, January 2018


Voluntary exposure to a toxin: the genetic influence on ethanol consumption
journal, December 2017

  • Hoffman, Paula L.; Saba, Laura M.; Vanderlinden, Lauren A.
  • Mammalian Genome, Vol. 29, Issue 1-2
  • DOI: 10.1007/s00335-017-9726-3

A survey of multi-view machine learning
journal, February 2013


The GreenCut: re-evaluation of physiological role of previously studied proteins and potential novel protein functions
journal, July 2013


Evolution of Chlamydomonas reinhardtii ferredoxins and their interactions with [FeFe]-hydrogenases
journal, June 2017


Cross-Disciplinary Network Comparison: Matchmaking between Hairballs
journal, March 2016


Statistical single cell multi-omics integration
journal, February 2018


Skeletal representations of orthogonal shapes
journal, July 2013


Unlocking the secrets of the genome
journal, June 2009

  • Celniker, Susan E.; Dillon, Laura A. L.; Gerstein, Mark B.
  • Nature, Vol. 459, Issue 7249
  • DOI: 10.1038/459927a

Gene co-expression network analysis reveals common system-level properties of prognostic genes across cancer types
journal, February 2014

  • Yang, Yang; Han, Leng; Yuan, Yuan
  • Nature Communications, Vol. 5, Issue 1
  • DOI: 10.1038/ncomms4231

Alignment of single-cell trajectories to compare cellular expression dynamics
journal, March 2018

  • Alpert, Ayelet; Moore, Lindsay S.; Dubovik, Tania
  • Nature Methods, Vol. 15, Issue 4
  • DOI: 10.1038/nmeth.4628

Proteomic analysis of a eukaryotic cilium
journal, July 2005

  • Pazour, Gregory J.; Agrin, Nathan; Leszyk, John
  • The Journal of Cell Biology, Vol. 170, Issue 1
  • DOI: 10.1083/jcb.200504008

Gene co-expression network topology provides a framework for molecular characterization of cellular state
journal, May 2004


IsoRankN: spectral methods for global alignment of multiple protein networks
journal, May 2009


MAGNA++: Maximizing Accuracy in Global Network Alignment via both node and edge conservation
journal, March 2015


Large-scale prediction of long non-coding RNA functions in a coding–non-coding gene co-expression network
journal, January 2011

  • Liao, Qi; Liu, Changning; Yuan, Xiongying
  • Nucleic Acids Research, Vol. 39, Issue 9
  • DOI: 10.1093/nar/gkq1348

mapman: a user-driven tool to display genomics data sets onto diagrams of metabolic pathways and other biological processes
journal, March 2004


Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
journal, June 2003


Gene network interconnectedness and the generalized topological overlap measure
journal, January 2007


WGCNA: an R package for weighted correlation network analysis
journal, December 2008


OrthoClust: an orthology-based network framework for clustering data across multiple species
journal, January 2014


MATCHER: manifold alignment reveals correspondence between single cell transcriptome and epigenome dynamics
journal, July 2017


MAGNA: Maximizing Accuracy in Global Network Alignment
preprint, January 2013


Applying deep learning techniques on medical corpora from the World Wide Web: a prototypical system and evaluation
preprint, January 2015