rvida034 wrote:The following data is focused on different zinc transporter genes and some metallothionein genes. There are different GSE series under investigation in which the wild type and PiZ mutation are compared via the following calculation: "t-Test: Paired Two Sample for Means".
rvida034 wrote:Hi Samantha:
Could you please provide the Bayesian Network for the GEO DataSet series GSE141593 for only the 6-week old mice so that I may interpret it?
The genes of focus are as follows: SLC30A1, SLC30A2, SLC30A3, SLC30A4, SLC30A5, SLC30A6, SLC30A7, SLC30A8, SLC30A9, SLC39A1, SLC39A2, SLC39A3, SLC39A4, SLC39A5, SLC39A6, SLC39A7, SLC39A8, SLC39A9, SLC39A10, SLC39A11, SLC39A12, SLC39A13, SLC39A14, MTF1, MT1, MT2, MT3, and MT4.
Please let me know if you have any questions. Thank you so much!
samanthagonzales wrote:Here is the full project folder for the initial Bayesian analysis on GSE141593, and the resulting network.
Please let me know if you have questions!
cwyoo wrote:samanthagonzales wrote:Here is the full project folder for the initial Bayesian analysis on GSE141593, and the resulting network.
Please let me know if you have questions!
Appreciate it, Samantha. Rebecca, could you please document here the data analysis process leading to the result? Typically, after cleaning RNAseq data, we start by creating a dataset containing genes with significant fold changes and genes of interest. Subsequently, we discretize the dataset using z-scores and identify the best-fitting Bayesian Networks.
For now, Dr. Luizzi and I have some comments and questions:
1. Kindly utilize gene names for the final network.
2. Are the genes showing significant fold changes included in this analysis?
3. Could you provide more details on the approach employed to identify the best-fitting Bayesian Networks? For instance, could you specify the duration and the number of runs conducted? Additionally, what criteria guided the decision to conclude the search?
samanthagonzales wrote:cwyoo wrote:samanthagonzales wrote:Here is the full project folder for the initial Bayesian analysis on GSE141593, and the resulting network.
Please let me know if you have questions!
Appreciate it, Samantha. Rebecca, could you please document here the data analysis process leading to the result? Typically, after cleaning RNAseq data, we start by creating a dataset containing genes with significant fold changes and genes of interest. Subsequently, we discretize the dataset using z-scores and identify the best-fitting Bayesian Networks.
For now, Dr. Luizzi and I have some comments and questions:
1. Kindly utilize gene names for the final network.
2. Are the genes showing significant fold changes included in this analysis?
3. Could you provide more details on the approach employed to identify the best-fitting Bayesian Networks? For instance, could you specify the duration and the number of runs conducted? Additionally, what criteria guided the decision to conclude the search?
1. Kindly utilize gene names for the final network.Can do!
2. Are the genes showing significant fold changes included in this analysis?
Only the genes of interest are included in this network, but I did write in the script the option to include top N differentially expressed genes. I can update the network to include those genes and post it here.
3. Could you provide more details on the approach employed to identify the best-fitting Bayesian Networks? For instance, could you specify the duration and the number of runs conducted? Additionally, what criteria guided the decision to conclude the search?I tried different algorithms available to bnlearn, and hill-climbing was the only one to give me a completely directed network. I used the command `pzm.hc <- hc(pizmice.counts, restart = 500)` to generate the network.
hc() is the hill-climbing function provided by bnlearn. The default scoring is BIC, but it can be changed to BDE if that is preferred. Would it be better to run a for loop to create several structures, then choose the one with the best score (possibly with varying restart values)?
Let me know if you have further questions! I will include differentially expressed genes in the network and update the gene names in the meantime. Thanks!
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