publication . Article . 2013

modeling causality for pairs of phenotypes in system genetics

Neto, Elias Chaibub; Broman, Aimee T.; Keller, Mark P.; Attie, Alan D.; Zhang, Bin; Zhu, Jun; Yandell, Brian S.;
Open Access
  • Published: 03 Jan 2013 Journal: Genetics, volume 193, pages 1,003-1,013 (issn: 0016-6731, eissn: 1943-2631, Copyright policy)
  • Publisher: Genetics Society of America
Abstract
Current efforts in systems genetics have focused on the development of statistical approaches that aim to disentangle causal relationships among molecular phenotypes in segregating populations. Reverse engineering of transcriptional networks plays a key role in the understanding of gene regulation. However, transcriptional regulation is only one possible mechanism, as methylation, phosphorylation, direct protein–protein interaction, transcription factor binding, etc., can also contribute to gene regulation. These additional modes of regulation can be interpreted as unobserved variables in the transcriptional gene network and can potentially affect its reconstruc...
Subjects
free text keywords: Genetics, Gene regulatory network, Biology, Inference, Transcriptional regulation, Model selection, Causality, Phenotype, Regulation of gene expression, Quantitative trait locus, Investigations, Genome and Systems Biology, hypothesis tests, systems genetics, quantitative trait loci
Funded by
NIH| Bayesian Methods for Genome-Wide Interacting QTL Mapping
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01GM069430-09
  • Funding stream: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
,
NIH| Epistatic and Cross Tissue Analysis for Human Gene Expression Traits
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01MH090948-02
  • Funding stream: NATIONAL INSTITUTE OF MENTAL HEALTH
,
NIH| Integrating cancer datasets for predictive model development and training
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5U54CA149237-02
  • Funding stream: NATIONAL CANCER INSTITUTE
37 references, page 1 of 3

Akaike H., 1974 A new look at the statistical model identification.IEEE Trans. Automat. Contr.19: 716–723. [OpenAIRE]

Aten J. E.Fuller T. F.Lusis A. J.Horvath S., 2008 Using genetic markers to orient the edges in quantitative trait networks: the NEO software.BMC Syst. Biol.2: 34.18412962 [OpenAIRE] [PubMed]

Benjamini Y.Hochberg Y., 1995 Controlling the false discovery rate: a practical and powerful approach to multiple testing.J. R. Stat. Soc., B 57: 289–300.

Benjamini Y.Yekutieli D., 2001 The control of the False Discovery Rate in multiple testing under dependency.Ann. Stat.29: 1165–1188. [OpenAIRE]

Brem R.Kruglyak L., 2005 The landscape of genetic complexity across 5,700 gene expression trait in yeast.Proc. Natl. Acad. Sci. USA 102: 1572–1577.15659551 [OpenAIRE] [PubMed]

Broman K.Wu H.Sen S.Churchill G. A., 2003 R/qtl: QTL mapping in experimental crosses.Bioinformatics 19: 889–890.12724300 [PubMed]

Chaibub Neto E.Ferrara C.Attie A. D.Yandell B. S., 2008 Inferring causal phenotype networks from segregating popul ations.Genetics 179: 1089–1100.18505877 [OpenAIRE] [PubMed]

Chaibub Neto E.Keller M. P.Attie A. D.Yandell B. S., 2010 Causal graphical models in system genetics: a unified framework for joint inference of causal network and genetic architecture for correlated phenotypes.Ann. Appl. Stat.4: 320–339.21218138 [OpenAIRE] [PubMed]

Chen L. S.Emmert-Streib F.Storey J. D., 2007 Harnessing naturally randomized transcription to infer regulatory relationships among genes.Genome Biol.8: R219.17931418 [OpenAIRE] [PubMed]

Churchill G. A.Doerge R. W., 1994 Empirical threshold values for quantitative trait mapping.Genetics 138: 963–971.7851788 [OpenAIRE] [PubMed]

Clarke K. A., 2007 A simple distribution-free test for nonnested model selection.Polit. Anal.15: 347–363.

Duarte C. W.Zeng Z. B., 2011 High-confidence discovery of genetic network regulators in expression quantitative trait loci data.Genetics 187: 955–964.21212238 [OpenAIRE] [PubMed]

Dupuis J.Siegmund D., 1999 Statistical methods for mapping quantitative trait loci from a dense set of markers.Genetics 151: 373–386.9872974 [OpenAIRE] [PubMed]

Hageman R. S.Leduc M. S.Korstanje R.Paigen B.Churchill G. A., 2011  A Bayesian framework for inference of the genotype-phenotype map for segregating populations.Genetics 181: 1163–1170.21242536 [OpenAIRE] [PubMed]

Haley C.Knott S., 1992 A simple regression method for mapping quantitative trait loci in line crosses using flanking markers.Heredity 69: 315–324.16718932 [PubMed]

37 references, page 1 of 3
Abstract
Current efforts in systems genetics have focused on the development of statistical approaches that aim to disentangle causal relationships among molecular phenotypes in segregating populations. Reverse engineering of transcriptional networks plays a key role in the understanding of gene regulation. However, transcriptional regulation is only one possible mechanism, as methylation, phosphorylation, direct protein–protein interaction, transcription factor binding, etc., can also contribute to gene regulation. These additional modes of regulation can be interpreted as unobserved variables in the transcriptional gene network and can potentially affect its reconstruc...
Subjects
free text keywords: Genetics, Gene regulatory network, Biology, Inference, Transcriptional regulation, Model selection, Causality, Phenotype, Regulation of gene expression, Quantitative trait locus, Investigations, Genome and Systems Biology, hypothesis tests, systems genetics, quantitative trait loci
Funded by
NIH| Bayesian Methods for Genome-Wide Interacting QTL Mapping
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01GM069430-09
  • Funding stream: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
,
NIH| Epistatic and Cross Tissue Analysis for Human Gene Expression Traits
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01MH090948-02
  • Funding stream: NATIONAL INSTITUTE OF MENTAL HEALTH
,
NIH| Integrating cancer datasets for predictive model development and training
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5U54CA149237-02
  • Funding stream: NATIONAL CANCER INSTITUTE
37 references, page 1 of 3

Akaike H., 1974 A new look at the statistical model identification.IEEE Trans. Automat. Contr.19: 716–723. [OpenAIRE]

Aten J. E.Fuller T. F.Lusis A. J.Horvath S., 2008 Using genetic markers to orient the edges in quantitative trait networks: the NEO software.BMC Syst. Biol.2: 34.18412962 [OpenAIRE] [PubMed]

Benjamini Y.Hochberg Y., 1995 Controlling the false discovery rate: a practical and powerful approach to multiple testing.J. R. Stat. Soc., B 57: 289–300.

Benjamini Y.Yekutieli D., 2001 The control of the False Discovery Rate in multiple testing under dependency.Ann. Stat.29: 1165–1188. [OpenAIRE]

Brem R.Kruglyak L., 2005 The landscape of genetic complexity across 5,700 gene expression trait in yeast.Proc. Natl. Acad. Sci. USA 102: 1572–1577.15659551 [OpenAIRE] [PubMed]

Broman K.Wu H.Sen S.Churchill G. A., 2003 R/qtl: QTL mapping in experimental crosses.Bioinformatics 19: 889–890.12724300 [PubMed]

Chaibub Neto E.Ferrara C.Attie A. D.Yandell B. S., 2008 Inferring causal phenotype networks from segregating popul ations.Genetics 179: 1089–1100.18505877 [OpenAIRE] [PubMed]

Chaibub Neto E.Keller M. P.Attie A. D.Yandell B. S., 2010 Causal graphical models in system genetics: a unified framework for joint inference of causal network and genetic architecture for correlated phenotypes.Ann. Appl. Stat.4: 320–339.21218138 [OpenAIRE] [PubMed]

Chen L. S.Emmert-Streib F.Storey J. D., 2007 Harnessing naturally randomized transcription to infer regulatory relationships among genes.Genome Biol.8: R219.17931418 [OpenAIRE] [PubMed]

Churchill G. A.Doerge R. W., 1994 Empirical threshold values for quantitative trait mapping.Genetics 138: 963–971.7851788 [OpenAIRE] [PubMed]

Clarke K. A., 2007 A simple distribution-free test for nonnested model selection.Polit. Anal.15: 347–363.

Duarte C. W.Zeng Z. B., 2011 High-confidence discovery of genetic network regulators in expression quantitative trait loci data.Genetics 187: 955–964.21212238 [OpenAIRE] [PubMed]

Dupuis J.Siegmund D., 1999 Statistical methods for mapping quantitative trait loci from a dense set of markers.Genetics 151: 373–386.9872974 [OpenAIRE] [PubMed]

Hageman R. S.Leduc M. S.Korstanje R.Paigen B.Churchill G. A., 2011  A Bayesian framework for inference of the genotype-phenotype map for segregating populations.Genetics 181: 1163–1170.21242536 [OpenAIRE] [PubMed]

Haley C.Knott S., 1992 A simple regression method for mapping quantitative trait loci in line crosses using flanking markers.Heredity 69: 315–324.16718932 [PubMed]

37 references, page 1 of 3
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publication . Article . 2013

modeling causality for pairs of phenotypes in system genetics

Neto, Elias Chaibub; Broman, Aimee T.; Keller, Mark P.; Attie, Alan D.; Zhang, Bin; Zhu, Jun; Yandell, Brian S.;