Module 190 -- IGFBPs

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General Properties
Below we list the number of gene sets from which the module was composed was originally composed, and the number of genes and experiments that it contains. Clicking on the number of genes will display a detailed list of all the genes in the module. Clicking on the number of experiments will display a detailed list of all the experiments in the module.
Num gene sets: 2
Num genes: 12 (see 1776 additional genes for this module)
Num experiments: 303 (123 induced, 180 repressed)
Parent module: 474
Children modules: None


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Gene sets
Below we list the gene sets from which the module was originally composed. Clicking on a gene set will display all the genes associated with that gene set. Also listed are all the other modules in which the gene set participates.
insulin_like growth factor binding
growth factor binding


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Enriched clinical annotations
For each of the clinical annotations, we tested whether it was enriched in the set of arrays in which the module is significantly induced (or repressed). Below we list all such annotations that were enriched in this module with an FDR corrected p-value of 0.05 ('P-value' column), along with the number ('Hits' column) of induced (or repressed) module's arrays in which they appear. We also show the fraction of the module's induced (or repressed) arrays with the given annotation ('Hits (%)' column). For completeness, we also list the total number of relevant induced arrays in the module ('Module hits in category' column), total number of arrays in the compendium in which the corresponding annotation is present ('Arrays in annotation' column), and the total number of relevant arrays in the compendium ('Arrays' column). Note that the 'relevant' arrays may be different for each annotation, since it includes only arrays in which the annotation was relevant (i.e., present or not present) and excludes arrays where the value of the annotation was not known. Rows that correspond to annotations that were enriched in the induced arrays of the module have a red background, while rows corresponding to annotations enriched in the repressed arrays have a green background. For each annotation, we also list the other modules in which it was enriched.
Clinical annotation Category P-value Hits Hits(%) Module hits in category Arrays in annotation Arrays
Liver tissue (Liver cancer*) Liver cancer* 1.8e-17 45 36.5 123 187 1945
Liver tissue, cancer or cell line (Liver cancer*) Liver cancer* 1.7e-16 45 36.5 123 197 1945
CNS tissue, cancer or cell line (Neuro tumors*) Neuro tumors* 1.2e-12 31 17.3 179 85 1945
Hepatitis infected liver (Liver cancer*) Liver cancer* 1.1e-11 34 27.6 123 156 1945
Non-tumor liver tissue (Liver cancer) Liver cancer 7.0e-11 36 78.2 46 76 207
Cancer and cell line (Neuro tumors*) Neuro tumors* 7.2e-11 29 16.2 179 86 1945
Cancer (Neuro tumors*) Neuro tumors* 7.2e-11 29 16.2 179 86 1945
CNS cancer or cell line (Neuro tumors*) Neuro tumors* 4.8e-10 27 15.0 179 81 1945
CNS tumor (Neuro tumors*) Neuro tumors* 4.8e-10 27 15.0 179 81 1945
Cancer and cell line (Liver cancer) Liver cancer 1.1e-08 33 100 33 126 207
Hepatocellular carcinoma (Liver cancer) Liver cancer 1.0e-07 30 90.9 33 104 207
Cancer and cell line (Lung cancer*) Lung cancer* 1.1e-07 48 26.8 179 252 1945
Cancer (Lung cancer*) Lung cancer* 1.1e-07 48 26.8 179 252 1945
Adenocarcinoma (Liver cancer) Liver cancer 1.3e-07 29 87.8 33 97 207
Cancer (Liver cancer) Liver cancer 2.2e-07 31 93.9 33 115 207
Lung tissue, cancer or cell line (Lung cancer*) Lung cancer* 8.4e-07 49 27.3 179 276 1945
Lung cancer (Lung cancer*) Lung cancer* 1.1e-06 44 24.5 179 238 1945
Lung cancer or cell line (Lung cancer*) Lung cancer* 1.1e-06 44 24.5 179 238 1945
Normal female hormonal tissue and cells (Various tumors) Various tumors 4.4e-06 5 62.5 8 8 154
Normal female hormonal tissue (Various tumors) Various tumors 4.4e-06 5 62.5 8 8 154
Female hormonal tissue, cancer or cell line (Various tumors) Various tumors 3.8e-05 6 75 8 19 154
Female hormonal tissue or cancer (Various tumors) Various tumors 3.8e-05 6 75 8 19 154
Non small cell lung cancer and cell line (Lung cancer*) Lung cancer* 0.0002 34 18.9 179 205 1945
Non small cell lung cancer (Lung cancer*) Lung cancer* 0.0002 34 18.9 179 205 1945


Jump to: Home | General properties | Gene sets | Enriched clinical annotations | Enriched Go annotations | Visual display
Enriched GO annotations
For each GO annotation, we tested whether it was enriched in the set of genes of the module. Below we list all such annotations that were enriched in this module with an FDR corrected p-value of 0.05 ('P-value' column), along with the number ('Hits' column) of the module's genes in which they appear. We also show the fraction of the module's genes with the given GO annotation that are included in this module ('Hits (%)' column). For completeness, we also list the total number of genes in the module ('Module genes' column), total number of genes in the compendium in which the corresponding annotation is present ('Genes in annotation' column), and the total number of genes in the compendium ('Genes' column).
GO annotation P-value Hits Hits(%) Module genes Genes in annotation Genes
growth factor binding 5.9e-36 12 100 12 12 4566
insulin-like growth factor binding 2.6e-32 11 91.6 12 11 4566
regulation of cell growth 1.1e-25 11 91.6 12 25 4566
protein binding 1.2e-14 12 100 12 322 4566
response to extracellular stimulus 2.6e-10 11 91.6 12 500 4566
binding 3.7e-08 12 100 12 1103 4566
extracellular space 2.7e-07 7 58.3 12 212 4566
cell communication 7.0e-07 11 91.6 12 1030 4566


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Visual display
Below is a visual display of the module. Shown are those arrays in which the module's genes significantly change, and the direction of change (induction/repression) in each array is indicated (middle, labeled 'Module changes'; red/green row). The arrays that correspond to the significant clinical attributes are also shown (top; brown rows). The gene sets that compose the module are also shown (left) along with an indication of the membership of the module genes in these gene sets.
You can also view the images within GeneXPress by loading the module gxp file file.
 
 





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