Construction of citrus gene coexpression networks from microarray data using random matrix theory
Identifieur interne : 000558 ( Pmc/Checkpoint ); précédent : 000557; suivant : 000559Construction of citrus gene coexpression networks from microarray data using random matrix theory
Auteurs : Dongliang Du [États-Unis] ; Nidhi Rawat [États-Unis] ; Zhanao Deng [États-Unis] ; Fred G. Gmitter [États-Unis]Source :
- Horticulture Research [ 2052-7276 ] ; 2015.
Abstract
After the sequencing of citrus genomes, gene function annotation is becoming a new challenge. Gene coexpression analysis can be employed for function annotation using publicly available microarray data sets. In this study, 230 sweet orange (
Url:
DOI: 10.1038/hortres.2015.26
PubMed: 26504573
PubMed Central: 4595991
Affiliations:
Links toward previous steps (curation, corpus...)
Links to Exploration step
PMC:4595991Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Construction of citrus gene coexpression networks from microarray data using random matrix theory</title><author><name sortKey="Du, Dongliang" sort="Du, Dongliang" uniqKey="Du D" first="Dongliang" last="Du">Dongliang Du</name><affiliation wicri:level="1"><nlm:aff id="aff1"><institution>Citrus Research and Education Center, Institute of Food and Agricultural Sciences, University of Florida</institution>, Lake Alfred, FL 33850,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Rawat, Nidhi" sort="Rawat, Nidhi" uniqKey="Rawat N" first="Nidhi" last="Rawat">Nidhi Rawat</name><affiliation wicri:level="1"><nlm:aff id="aff2"><institution>Gulf Coast Research and Education Center, Institute of Food and Agricultural Sciences, University of Florida</institution>, Wimauma, FL 33598,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Deng, Zhanao" sort="Deng, Zhanao" uniqKey="Deng Z" first="Zhanao" last="Deng">Zhanao Deng</name><affiliation wicri:level="1"><nlm:aff id="aff2"><institution>Gulf Coast Research and Education Center, Institute of Food and Agricultural Sciences, University of Florida</institution>, Wimauma, FL 33598,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Gmitter, Fred G" sort="Gmitter, Fred G" uniqKey="Gmitter F" first="Fred G." last="Gmitter">Fred G. Gmitter</name><affiliation wicri:level="1"><nlm:aff id="aff1"><institution>Citrus Research and Education Center, Institute of Food and Agricultural Sciences, University of Florida</institution>, Lake Alfred, FL 33850,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">26504573</idno><idno type="pmc">4595991</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4595991</idno><idno type="RBID">PMC:4595991</idno><idno type="doi">10.1038/hortres.2015.26</idno><date when="2015">2015</date><idno type="wicri:Area/Pmc/Corpus">000440</idno><idno type="wicri:Area/Pmc/Curation">000439</idno><idno type="wicri:Area/Pmc/Checkpoint">000558</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Construction of citrus gene coexpression networks from microarray data using random matrix theory</title><author><name sortKey="Du, Dongliang" sort="Du, Dongliang" uniqKey="Du D" first="Dongliang" last="Du">Dongliang Du</name><affiliation wicri:level="1"><nlm:aff id="aff1"><institution>Citrus Research and Education Center, Institute of Food and Agricultural Sciences, University of Florida</institution>, Lake Alfred, FL 33850,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Rawat, Nidhi" sort="Rawat, Nidhi" uniqKey="Rawat N" first="Nidhi" last="Rawat">Nidhi Rawat</name><affiliation wicri:level="1"><nlm:aff id="aff2"><institution>Gulf Coast Research and Education Center, Institute of Food and Agricultural Sciences, University of Florida</institution>, Wimauma, FL 33598,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Deng, Zhanao" sort="Deng, Zhanao" uniqKey="Deng Z" first="Zhanao" last="Deng">Zhanao Deng</name><affiliation wicri:level="1"><nlm:aff id="aff2"><institution>Gulf Coast Research and Education Center, Institute of Food and Agricultural Sciences, University of Florida</institution>, Wimauma, FL 33598,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Gmitter, Fred G" sort="Gmitter, Fred G" uniqKey="Gmitter F" first="Fred G." last="Gmitter">Fred G. Gmitter</name><affiliation wicri:level="1"><nlm:aff id="aff1"><institution>Citrus Research and Education Center, Institute of Food and Agricultural Sciences, University of Florida</institution>, Lake Alfred, FL 33850,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author></analytic><series><title level="j">Horticulture Research</title><idno type="eISSN">2052-7276</idno><imprint><date when="2015">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>After the sequencing of citrus genomes, gene function annotation is becoming a new challenge. Gene coexpression analysis can be employed for function annotation using publicly available microarray data sets. In this study, 230 sweet orange (<italic>Citrus sinensis</italic>) microarrays were used to construct seven coexpression networks, including one condition-independent and six condition-dependent (Citrus canker, Huanglongbing, leaves, flavedo, albedo, and flesh) networks. In total, these networks contain 37 633 edges among 6256 nodes (genes), which accounts for 52.11% measurable genes of the citrus microarray. Then, these networks were partitioned into functional modules using the Markov Cluster Algorithm. Significantly enriched Gene Ontology biological process terms and KEGG pathway terms were detected for 343 and 60 modules, respectively. Finally, independent verification of these networks was performed using another expression data of 371 genes. This study provides new targets for further functional analyses in citrus.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct></listBibl></div1></back></TEI><pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Hortic Res</journal-id><journal-id journal-id-type="iso-abbrev">Hortic Res</journal-id><journal-title-group><journal-title>Horticulture Research</journal-title></journal-title-group><issn pub-type="epub">2052-7276</issn><publisher><publisher-name>Nature Publishing Group</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">26504573</article-id><article-id pub-id-type="pmc">4595991</article-id><article-id pub-id-type="pii">hortres201526</article-id><article-id pub-id-type="doi">10.1038/hortres.2015.26</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Construction of citrus gene coexpression networks from microarray data using random matrix theory</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Du</surname><given-names>Dongliang</given-names></name><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author"><name><surname>Rawat</surname><given-names>Nidhi</given-names></name><xref ref-type="aff" rid="aff2">2</xref></contrib><contrib contrib-type="author"><name><surname>Deng</surname><given-names>Zhanao</given-names></name><xref ref-type="aff" rid="aff2">2</xref></contrib><contrib contrib-type="author"><name><surname>Gmitter</surname><given-names>Fred G.</given-names><suffix>Jr.</suffix></name><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="corresp" rid="caf1">*</xref></contrib><aff id="aff1"><label>1</label><institution>Citrus Research and Education Center, Institute of Food and Agricultural Sciences, University of Florida</institution>, Lake Alfred, FL 33850,<country>USA</country></aff><aff id="aff2"><label>2</label><institution>Gulf Coast Research and Education Center, Institute of Food and Agricultural Sciences, University of Florida</institution>, Wimauma, FL 33598,<country>USA</country></aff></contrib-group><author-notes><corresp id="caf1"><label>*</label> (<email>fgmitter@ufl.edu</email>)</corresp></author-notes><pub-date pub-type="epub"><day>10</day><month>06</month><year>2015</year></pub-date><pub-date pub-type="collection"><year>2015</year></pub-date><volume>2</volume><fpage>15026</fpage><lpage></lpage><history><date date-type="received"><day>30</day><month>03</month><year>2015</year></date><date date-type="rev-recd"><day>29</day><month>04</month><year>2015</year></date><date date-type="accepted"><day>04</day><month>05</month><year>2015</year></date></history><permissions><copyright-statement>Copyright © 2015 Nanjing Agricultural University</copyright-statement><copyright-year>2015</copyright-year><copyright-holder>Nanjing Agricultural University</copyright-holder><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by-nc-sa/3.0/"><pmc-comment>author-paid</pmc-comment>
<license-p>This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by-nc-sa/3.0/">http://creativecommons.org/licenses/by-nc-sa/3.0/</ext-link></license-p></license></permissions><abstract><p>After the sequencing of citrus genomes, gene function annotation is becoming a new challenge. Gene coexpression analysis can be employed for function annotation using publicly available microarray data sets. In this study, 230 sweet orange (<italic>Citrus sinensis</italic>) microarrays were used to construct seven coexpression networks, including one condition-independent and six condition-dependent (Citrus canker, Huanglongbing, leaves, flavedo, albedo, and flesh) networks. In total, these networks contain 37 633 edges among 6256 nodes (genes), which accounts for 52.11% measurable genes of the citrus microarray. Then, these networks were partitioned into functional modules using the Markov Cluster Algorithm. Significantly enriched Gene Ontology biological process terms and KEGG pathway terms were detected for 343 and 60 modules, respectively. Finally, independent verification of these networks was performed using another expression data of 371 genes. This study provides new targets for further functional analyses in citrus.</p></abstract></article-meta></front><floats-group><fig id="fig1"><label>Figure 1</label><caption><p>Work flow used for networks construction and clustering in the present study.</p></caption><graphic xlink:href="hortres201526-f1"></graphic></fig><fig id="fig2"><label>Figure 2</label><caption><p>Layout of the citrus “all data” coexpression network. The most overrepresented GO terms were shown for the 12 largest color-coded modules.</p></caption><graphic xlink:href="hortres201526-f2"></graphic></fig><fig id="fig3"><label>Figure 3</label><caption><p>Graph showing coexpressed genes of the C. clementina homolog of citrus LOB1 (Ciclev10033956m) and SWEET1 (Ciclev10002276m) in canker-module 1.</p></caption><graphic xlink:href="hortres201526-f3"></graphic></fig><fig id="fig4"><label>Figure 4</label><caption><p>Genes and edges in canker-module 25.</p></caption><graphic xlink:href="hortres201526-f4"></graphic></fig><fig id="fig5"><label>Figure 5</label><caption><p>Genes and edges in flesh-module 19.</p></caption><graphic xlink:href="hortres201526-f5"></graphic></fig><fig id="fig6"><label>Figure 6</label><caption><p>Genes and edges in HLB-module 6.</p></caption><graphic xlink:href="hortres201526-f6"></graphic></fig><fig id="fig7"><label>Figure 7</label><caption><p>Distribution of absolute value of correlation coefficients.</p></caption><graphic xlink:href="hortres201526-f7"></graphic></fig><table-wrap id="tbl1"><label>Table 1</label><caption><title>Composition of the 230 microarrays according to the experiment conditions and organs.</title></caption><table frame="hsides" rules="groups" border="1"><colgroup><col align="left"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col></colgroup><thead valign="bottom"><tr><th align="left" valign="top" charoff="50"> </th><th align="center" valign="top" charoff="50">Epicotyls</th><th align="center" valign="top" charoff="50">Root</th><th align="center" valign="top" charoff="50">Stem</th><th align="center" valign="top" charoff="50">Leaves</th><th align="center" valign="top" charoff="50">Flower</th><th align="center" valign="top" charoff="50">Peel</th><th align="center" valign="top" charoff="50">Flavedo</th><th align="center" valign="top" charoff="50">Albedo</th><th align="center" valign="top" charoff="50">Vascular core</th><th align="center" valign="top" charoff="50">Flesh</th><th align="center" valign="top" charoff="50">Seed</th><th align="center" valign="top" charoff="50">Total</th></tr></thead><tbody valign="top"><tr><td align="left" valign="top" charoff="50">Citrus canker</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">30</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">30</td></tr><tr><td align="left" valign="top" charoff="50">Huanglongbing</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">3</td><td align="center" valign="top" charoff="50">3</td><td align="center" valign="top" charoff="50">12</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">12</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">12</td><td align="center" valign="top" charoff="50">12</td><td align="center" valign="top" charoff="50">4</td><td align="center" valign="top" charoff="50">58</td></tr><tr><td align="left" valign="top" charoff="50">Other treatments</td><td align="center" valign="top" charoff="50">12</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">2</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">6</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">20</td></tr><tr><td align="left" valign="top" charoff="50">Control</td><td align="center" valign="top" charoff="50">0</td><td align="center" valign="top" charoff="50">3</td><td align="center" valign="top" charoff="50">3</td><td align="center" valign="top" charoff="50">19</td><td align="center" valign="top" charoff="50">9</td><td align="center" valign="top" charoff="50">12</td><td align="center" valign="top" charoff="50">22</td><td align="center" valign="top" charoff="50">12</td><td align="center" valign="top" charoff="50">7</td><td align="center" valign="top" charoff="50">31</td><td align="center" valign="top" charoff="50">4</td><td align="center" valign="top" charoff="50">122</td></tr><tr><td align="left" valign="top" charoff="50">Total</td><td align="center" valign="top" charoff="50">12</td><td align="center" valign="top" charoff="50">6</td><td align="center" valign="top" charoff="50">6</td><td align="center" valign="top" charoff="50">63</td><td align="center" valign="top" charoff="50">9</td><td align="center" valign="top" charoff="50">12</td><td align="center" valign="top" charoff="50">40</td><td align="center" valign="top" charoff="50">12</td><td align="center" valign="top" charoff="50">19</td><td align="center" valign="top" charoff="50">43</td><td align="center" valign="top" charoff="50">8</td><td align="center" valign="top" charoff="50">230</td></tr></tbody></table></table-wrap><table-wrap id="tbl2"><label>Table 2</label><caption><title>Topological characteristics of seven coexpression networks</title></caption><table frame="hsides" rules="groups" border="1"><colgroup><col align="left"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col></colgroup><thead valign="bottom"><tr><th align="left" valign="top" charoff="50"> </th><th align="center" valign="top" charoff="50">Arrays</th><th align="center" valign="top" charoff="50">RT</th><th align="center" valign="top" charoff="50">Nodes</th><th align="center" valign="top" charoff="50">Edges</th><th align="center" valign="top" charoff="50">AD</th><th align="center" valign="top" charoff="50">ND</th><th align="center" valign="top" charoff="50">NCC</th><th align="center" valign="top" charoff="50">NBC</th><th align="center" valign="top" charoff="50">EBC</th><th align="center" valign="top" charoff="50">APL</th><th align="center" valign="top" charoff="50">DE</th><th align="center" valign="top" charoff="50">CC</th></tr></thead><tbody valign="top"><tr><td align="left" valign="top" charoff="50">All data</td><td align="center" valign="top" charoff="50">230</td><td align="center" valign="top" charoff="50">0.882</td><td align="center" valign="top" charoff="50">1391</td><td align="center" valign="top" charoff="50">10 220</td><td align="center" valign="top" charoff="50">14.69</td><td align="center" valign="top" charoff="50">0.011</td><td align="center" valign="top" charoff="50">104</td><td align="center" valign="top" charoff="50">1046</td><td align="center" valign="top" charoff="50">9878</td><td align="center" valign="top" charoff="50">7.62</td><td align="center" valign="top" charoff="50">1.13</td><td align="center" valign="top" charoff="50">0.40</td></tr><tr><td align="left" valign="top" charoff="50">HLB</td><td align="center" valign="top" charoff="50">36</td><td align="center" valign="top" charoff="50">0.968</td><td align="center" valign="top" charoff="50">1400</td><td align="center" valign="top" charoff="50">5036</td><td align="center" valign="top" charoff="50">7.19</td><td align="center" valign="top" charoff="50">0.005</td><td align="center" valign="top" charoff="50">91</td><td align="center" valign="top" charoff="50">1040</td><td align="center" valign="top" charoff="50">4379</td><td align="center" valign="top" charoff="50">6.76</td><td align="center" valign="top" charoff="50">1.58</td><td align="center" valign="top" charoff="50">0.29</td></tr><tr><td align="left" valign="top" charoff="50">Citrus canker</td><td align="center" valign="top" charoff="50">30</td><td align="center" valign="top" charoff="50">0.938</td><td align="center" valign="top" charoff="50">1841</td><td align="center" valign="top" charoff="50">5565</td><td align="center" valign="top" charoff="50">6.05</td><td align="center" valign="top" charoff="50">0.003</td><td align="center" valign="top" charoff="50">211</td><td align="center" valign="top" charoff="50">1265</td><td align="center" valign="top" charoff="50">5174</td><td align="center" valign="top" charoff="50">8.79</td><td align="center" valign="top" charoff="50">1.50</td><td align="center" valign="top" charoff="50">0.23</td></tr><tr><td align="left" valign="top" charoff="50">Leaves</td><td align="center" valign="top" charoff="50">63</td><td align="center" valign="top" charoff="50">0.911</td><td align="center" valign="top" charoff="50">2263</td><td align="center" valign="top" charoff="50">11 535</td><td align="center" valign="top" charoff="50">10.19</td><td align="center" valign="top" charoff="50">0.005</td><td align="center" valign="top" charoff="50">158</td><td align="center" valign="top" charoff="50">1862</td><td align="center" valign="top" charoff="50">11 247</td><td align="center" valign="top" charoff="50">10.75</td><td align="center" valign="top" charoff="50">1.47</td><td align="center" valign="top" charoff="50">0.33</td></tr><tr><td align="left" valign="top" charoff="50">Flavedo</td><td align="center" valign="top" charoff="50">40</td><td align="center" valign="top" charoff="50">0.964</td><td align="center" valign="top" charoff="50">1425</td><td align="center" valign="top" charoff="50">2467</td><td align="center" valign="top" charoff="50">3.46</td><td align="center" valign="top" charoff="50">0.002</td><td align="center" valign="top" charoff="50">123</td><td align="center" valign="top" charoff="50">1133</td><td align="center" valign="top" charoff="50">2289</td><td align="center" valign="top" charoff="50">9.63</td><td align="center" valign="top" charoff="50">2.10</td><td align="center" valign="top" charoff="50">0.20</td></tr><tr><td align="left" valign="top" charoff="50">Albedo</td><td align="center" valign="top" charoff="50">31</td><td align="center" valign="top" charoff="50">0.947</td><td align="center" valign="top" charoff="50">1592</td><td align="center" valign="top" charoff="50">3725</td><td align="center" valign="top" charoff="50">4.68</td><td align="center" valign="top" charoff="50">0.003</td><td align="center" valign="top" charoff="50">162</td><td align="center" valign="top" charoff="50">996</td><td align="center" valign="top" charoff="50">2644</td><td align="center" valign="top" charoff="50">6.66</td><td align="center" valign="top" charoff="50">1.80</td><td align="center" valign="top" charoff="50">0.20</td></tr><tr><td align="left" valign="top" charoff="50">Flesh</td><td align="center" valign="top" charoff="50">43</td><td align="center" valign="top" charoff="50">0.948</td><td align="center" valign="top" charoff="50">1137</td><td align="center" valign="top" charoff="50">2431</td><td align="center" valign="top" charoff="50">4.28</td><td align="center" valign="top" charoff="50">0.004</td><td align="center" valign="top" charoff="50">90</td><td align="center" valign="top" charoff="50">911</td><td align="center" valign="top" charoff="50">2290</td><td align="center" valign="top" charoff="50">7.59</td><td align="center" valign="top" charoff="50">1.86</td><td align="center" valign="top" charoff="50">0.20</td></tr><tr><td align="left" valign="top" charoff="50">Total</td><td align="center" valign="top" charoff="50"> </td><td align="center" valign="top" charoff="50"> </td><td align="center" valign="top" charoff="50">6256</td><td align="center" valign="top" charoff="50">37 633</td><td align="center" valign="top" charoff="50"> </td><td align="center" valign="top" charoff="50"> </td><td align="center" valign="top" charoff="50"> </td><td align="center" valign="top" charoff="50"> </td><td align="center" valign="top" charoff="50"> </td><td align="center" valign="top" charoff="50"> </td><td align="center" valign="top" charoff="50"> </td><td align="center" valign="top" charoff="50"> </td></tr></tbody></table><table-wrap-foot><fn id="t2-tfoot1"><p>RT, RMT threshold; AD, average degree; ND, network density; NCC, number of connected components; NBC, nodes of biggest components; EBC, edges of biggest components; APL, average path length; DE, degree exponent; CC, clustering coefficient.</p></fn></table-wrap-foot></table-wrap><table-wrap id="tbl3"><label>Table 3</label><caption><title>Intersection between edges/nodes (upper/lower triangular) of networks</title></caption><table frame="hsides" rules="groups" border="1"><colgroup><col align="left"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col></colgroup><thead valign="bottom"><tr><th align="left" valign="top" charoff="50"> </th><th align="center" valign="top" charoff="50">All data</th><th align="center" valign="top" charoff="50">HLB</th><th align="center" valign="top" charoff="50">Citrus canker</th><th align="center" valign="top" charoff="50">Leaves</th><th align="center" valign="top" charoff="50">Flavedo</th><th align="center" valign="top" charoff="50">Albedo</th><th align="center" valign="top" charoff="50">Flesh</th></tr></thead><tbody valign="top"><tr><td align="left" valign="top" charoff="50">All data</td><td align="center" valign="top" charoff="50"> </td><td align="center" valign="top" charoff="50">206 (1.35%)</td><td align="center" valign="top" charoff="50">574 (3.64%)</td><td align="center" valign="top" charoff="50">1305 (6%)</td><td align="center" valign="top" charoff="50">158 (1.25%)</td><td align="center" valign="top" charoff="50">45 (0.32%)</td><td align="center" valign="top" charoff="50">28 (0.22%)</td></tr><tr><td align="left" valign="top" charoff="50">HLB</td><td align="center" valign="top" charoff="50">334 (11.97%)</td><td align="center" valign="top" charoff="50"> </td><td align="center" valign="top" charoff="50">26 (0.25%)</td><td align="center" valign="top" charoff="50">29 (0.18%)</td><td align="center" valign="top" charoff="50">14 (0.19%)</td><td align="center" valign="top" charoff="50">28 (0.32%)</td><td align="center" valign="top" charoff="50">15 (0.2%)</td></tr><tr><td align="left" valign="top" charoff="50">Citrus canker</td><td align="center" valign="top" charoff="50">482 (14.91%)</td><td align="center" valign="top" charoff="50">308 (9.5%)</td><td align="center" valign="top" charoff="50"> </td><td align="center" valign="top" charoff="50">1271 (7.43%)</td><td align="center" valign="top" charoff="50">15 (0.19%)</td><td align="center" valign="top" charoff="50">10 (0.11%)</td><td align="center" valign="top" charoff="50">3 (0.04%)</td></tr><tr><td align="left" valign="top" charoff="50">Leaves</td><td align="center" valign="top" charoff="50">665 (18.2%)</td><td align="center" valign="top" charoff="50">274 (7.48%)</td><td align="center" valign="top" charoff="50">925 (22.54%)</td><td align="center" valign="top" charoff="50"> </td><td align="center" valign="top" charoff="50">59 (0.42%)</td><td align="center" valign="top" charoff="50">21 (0.14%)</td><td align="center" valign="top" charoff="50">9 (0.06%)</td></tr><tr><td align="left" valign="top" charoff="50">Flavedo</td><td align="center" valign="top" charoff="50">278 (9.87%)</td><td align="center" valign="top" charoff="50">257 (9.1%)</td><td align="center" valign="top" charoff="50">276 (8.45%)</td><td align="center" valign="top" charoff="50">361 (9.79%)</td><td align="center" valign="top" charoff="50"> </td><td align="center" valign="top" charoff="50">70 (1.13%)</td><td align="center" valign="top" charoff="50">32 (0.65%)</td></tr><tr><td align="left" valign="top" charoff="50">Albedo</td><td align="center" valign="top" charoff="50">262 (8.78%)</td><td align="center" valign="top" charoff="50">267 (8.92%)</td><td align="center" valign="top" charoff="50">269 (7.84%)</td><td align="center" valign="top" charoff="50">317 (8.22%)</td><td align="center" valign="top" charoff="50">565 (18.73%)</td><td align="center" valign="top" charoff="50"> </td><td align="center" valign="top" charoff="50">40 (0.65%)</td></tr><tr><td align="left" valign="top" charoff="50">Flesh</td><td align="center" valign="top" charoff="50">144 (5.7%)</td><td align="center" valign="top" charoff="50">238 (9.38%)</td><td align="center" valign="top" charoff="50">178 (5.98%)</td><td align="center" valign="top" charoff="50">217 (6.38%)</td><td align="center" valign="top" charoff="50">410 (16%)</td><td align="center" valign="top" charoff="50">382 (14%)</td><td align="center" valign="top" charoff="50"> </td></tr></tbody></table></table-wrap><table-wrap id="tbl4"><label>Table 4</label><caption><title>Network clustering and functional enrichment of modules</title></caption><table frame="hsides" rules="groups" border="1"><colgroup><col align="left"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col></colgroup><tbody valign="top"><tr><td align="left" valign="top" charoff="50"> </td><td align="center" valign="top" charoff="50">Inflation</td><td align="center" valign="top" charoff="50">Efficiency</td><td align="center" valign="top" charoff="50">Mass fraction (%)</td><td align="center" valign="top" charoff="50">Area fraction (%)</td><td align="center" valign="top" charoff="50">Modules</td><td align="center" valign="top" charoff="50">M5</td><td align="center" valign="top" charoff="50">SBM</td><td align="center" valign="top" charoff="50">GO</td><td align="center" valign="top" charoff="50">KEGG</td></tr><tr><td align="left" valign="top" charoff="50">All data</td><td align="center" valign="top" charoff="50">2</td><td align="center" valign="top" charoff="50">0.52</td><td align="center" valign="top" charoff="50">83.63</td><td align="center" valign="top" charoff="50">2.85</td><td align="center" valign="top" charoff="50">285</td><td align="center" valign="top" charoff="50">55</td><td align="center" valign="top" charoff="50">200</td><td align="center" valign="top" charoff="50">39</td><td align="center" valign="top" charoff="50">7</td></tr><tr><td align="left" valign="top" charoff="50">HLB</td><td align="center" valign="top" charoff="50">1.8</td><td align="center" valign="top" charoff="50">0.45</td><td align="center" valign="top" charoff="50">80.93</td><td align="center" valign="top" charoff="50">1.38</td><td align="center" valign="top" charoff="50">267</td><td align="center" valign="top" charoff="50">72</td><td align="center" valign="top" charoff="50">90</td><td align="center" valign="top" charoff="50">47</td><td align="center" valign="top" charoff="50">9</td></tr><tr><td align="left" valign="top" charoff="50">Citrus canker</td><td align="center" valign="top" charoff="50">1.8</td><td align="center" valign="top" charoff="50">0.56</td><td align="center" valign="top" charoff="50">85.90</td><td align="center" valign="top" charoff="50">0.81</td><td align="center" valign="top" charoff="50">447</td><td align="center" valign="top" charoff="50">88</td><td align="center" valign="top" charoff="50">103</td><td align="center" valign="top" charoff="50">58</td><td align="center" valign="top" charoff="50">9</td></tr><tr><td align="left" valign="top" charoff="50">Leaves</td><td align="center" valign="top" charoff="50">1.8</td><td align="center" valign="top" charoff="50">0.46</td><td align="center" valign="top" charoff="50">82.00</td><td align="center" valign="top" charoff="50">1.40</td><td align="center" valign="top" charoff="50">432</td><td align="center" valign="top" charoff="50">87</td><td align="center" valign="top" charoff="50">144</td><td align="center" valign="top" charoff="50">57</td><td align="center" valign="top" charoff="50">17</td></tr><tr><td align="left" valign="top" charoff="50">Flavedo</td><td align="center" valign="top" charoff="50">1.6</td><td align="center" valign="top" charoff="50">0.48</td><td align="center" valign="top" charoff="50">86.92</td><td align="center" valign="top" charoff="50">0.75</td><td align="center" valign="top" charoff="50">287</td><td align="center" valign="top" charoff="50">86</td><td align="center" valign="top" charoff="50">47</td><td align="center" valign="top" charoff="50">58</td><td align="center" valign="top" charoff="50">12</td></tr><tr><td align="left" valign="top" charoff="50">Albedo</td><td align="center" valign="top" charoff="50">1.8</td><td align="center" valign="top" charoff="50">0.54</td><td align="center" valign="top" charoff="50">83.03</td><td align="center" valign="top" charoff="50">0.84</td><td align="center" valign="top" charoff="50">402</td><td align="center" valign="top" charoff="50">73</td><td align="center" valign="top" charoff="50">102</td><td align="center" valign="top" charoff="50">37</td><td align="center" valign="top" charoff="50">3</td></tr><tr><td align="left" valign="top" charoff="50">Flesh</td><td align="center" valign="top" charoff="50">1.6</td><td align="center" valign="top" charoff="50">0.44</td><td align="center" valign="top" charoff="50">84.90</td><td align="center" valign="top" charoff="50">1.67</td><td align="center" valign="top" charoff="50">218</td><td align="center" valign="top" charoff="50">64</td><td align="center" valign="top" charoff="50">108</td><td align="center" valign="top" charoff="50">47</td><td align="center" valign="top" charoff="50">3</td></tr><tr><td align="left" valign="top" charoff="50">Total</td><td align="center" valign="top" charoff="50"> </td><td align="center" valign="top" charoff="50"> </td><td align="center" valign="top" charoff="50"> </td><td align="center" valign="top" charoff="50"> </td><td align="center" valign="top" charoff="50">2338</td><td align="center" valign="top" charoff="50">525</td><td align="center" valign="top" charoff="50"> </td><td align="center" valign="top" charoff="50">343</td><td align="center" valign="top" charoff="50">60</td></tr></tbody></table><table-wrap-foot><fn id="t4-tfoot1"><p>M5, number of modules containing more than five nodes; SBM, size of biggest module; GO, KEGG: number of modules with significantly enriched GO biological process terms, KEGG pathways.</p></fn></table-wrap-foot></table-wrap></floats-group></pmc><affiliations><list><country><li>États-Unis</li></country></list><tree><country name="États-Unis"><noRegion><name sortKey="Du, Dongliang" sort="Du, Dongliang" uniqKey="Du D" first="Dongliang" last="Du">Dongliang Du</name></noRegion><name sortKey="Deng, Zhanao" sort="Deng, Zhanao" uniqKey="Deng Z" first="Zhanao" last="Deng">Zhanao Deng</name><name sortKey="Gmitter, Fred G" sort="Gmitter, Fred G" uniqKey="Gmitter F" first="Fred G." last="Gmitter">Fred G. Gmitter</name><name sortKey="Rawat, Nidhi" sort="Rawat, Nidhi" uniqKey="Rawat N" first="Nidhi" last="Rawat">Nidhi Rawat</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Bois/explor/OrangerV1/Data/Pmc/Checkpoint
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000558 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Pmc/Checkpoint/biblio.hfd -nk 000558 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Wicri/Bois
|area= OrangerV1
|flux= Pmc
|étape= Checkpoint
|type= RBID
|clé= PMC:4595991
|texte= Construction of citrus gene coexpression networks from microarray data using random matrix theory
}}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/Pmc/Checkpoint/RBID.i -Sk "pubmed:26504573" \
| HfdSelect -Kh $EXPLOR_AREA/Data/Pmc/Checkpoint/biblio.hfd \
| NlmPubMed2Wicri -a OrangerV1
| This area was generated with Dilib version V0.6.25. |  |