From bb9d93322abf825368dedaafc2376ef8fdfc1e2f Mon Sep 17 00:00:00 2001 From: ziejd2 Date: Mon, 28 Jan 2019 16:31:54 -0600 Subject: Jan 28 2019 update --- sourcecodes/BNW_workflow_sci.htm | 12 +++--------- 1 file changed, 3 insertions(+), 9 deletions(-) (limited to 'sourcecodes/BNW_workflow_sci.htm') diff --git a/sourcecodes/BNW_workflow_sci.htm b/sourcecodes/BNW_workflow_sci.htm index 8adbc7b7..1e56bb11 100644 --- a/sourcecodes/BNW_workflow_sci.htm +++ b/sourcecodes/BNW_workflow_sci.htm @@ -315,22 +315,16 @@ ul
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-**Recent updates to BNW may result in slight differences between what is described/shown below and what would currently be experienced in BNW.** -

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1. A genetic network linking genotype and phenotype

In this example, we will use the structural constraint interface to create a genetic network linking a genotype with gene expression traits and a higher-order phenotype. There are 5 nodes in the network: Genotype, Gene1, Gene2, Gene3, and Phenotype. The input datafile is available here. To begin, select Learn a network model from data on the BNW homepage and load the data file, displaying what is shown below:

+line-height:115%;font-family:"Arial","sans-serif"'>In this example, we will use the structural constraint interface to create a genetic network linking a genotype with gene expression traits and a higher-order phenotype. There are 5 nodes in the network: Genotype, Gene1, Gene2, Gene3, and Phenotype. The input data file is available here. To begin, select Learn a network model from data on the BNW homepage and load the data file, displaying what is shown below:

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The third section of the 0in;margin-left:0in;margin-bottom:.0001pt'>
In this example, we will not specify any additional constraints in the fourth section of the structural constraint interface, and we can click Perform Bayesian network modeling on the upper left corner of the page. The figure below shows the network with the model average network of the 1000 highest scoring networks and this network is available here. Genotype directly influences two of the genes (Gene1 and Gene3), and two of the genes (Gene2 and Gene3) directly influence the Phenotype. In this case, although we did not prevent the Genotype from directly influencing the Phenotype, the highest scoring networks did not include this directed edge. The right side of the figure shows the predictions of the network with Genotype=1 used as evidence. If Genotype is known to be in state 1, the values of all other variables in the network are expected to decrease compared to the distributions learned using all phenotypes. A more complete description of using BNW to make predictions with network models can be found in a separate tutorial.

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