Calculate p-values and corresponding FDR for all genes in the dataset

Question

[mohammedtoufiq91]

Hi,

I have the normalized data with approximately 300 genes and 50 paired samples (Before vs After metabolite levels). In addition, I have the another column with the Group A, B, and C grouped or assigned based on the metabolite level. I am interested to perform t-test between the two groups (Before vs After) and 1-way ANOVA to compare the groups A vs B vs C. When I perform the statistical test between Before vs After or ANOVA between A vs B vs C, the output displays one p-value, however, I am interested in obtaining p-values for all the genes with the FDR for my datasets. I used the below functions in R to perform the same. Is there specific package to perform this?

pairwise.t.test()
oneway.test()
  

Example of the data grouping.

Samples Metabolite_Level    Group
Sample_1    Before  A
Sample_2    Before  B
Sample_3    Before  A
Sample_4    Before  B
Sample_5    Before  B
Sample_5    Before  B
Sample_6    Before  A
Sample_7    Before  C
Sample_8    Before  C
Sample_9    Before  C
Sample_10   Before  A
2_Sample_1  After   A
2_Sample_2  After   B
2_Sample_3  After   A
2_Sample_3  After   A
2_Sample_4  After   B
2_Sample_5  After   B
2_Sample_6  After   A
2_Sample_7  After   C
2_Sample_8  After   C
2_Sample_9  After   C
2_Sample_10 After   A

Thank you,

Toufiq

[i.sudbery]

I suggest you take a look at the broom pacakge.

[ATpoint]

Is this RNA-seq or any kind of targeted approach?

[mohammedtoufiq91]

Hi @ATpoint

Thank you for the reply.

Yes, this is a targeted approach. qRT-PCR data from Fluidigm platform.