microarray differential analysis - P value histogram

Question

[bioinformatics]

Hi,

I have performed microarray differential expression analysis in R and generated the table below.

head(res)
                logFC AveExpr   t  P.Value adj.P.Val   B
207783_x_at        14      14 893 5.8e-183  5.8e-183 388
212869_x_at        14      14 801 1.3e-178  1.3e-178 381
AFFX-hum_alu_at    15      15 799 1.6e-178  1.6e-178 381
213477_x_at        14      14 724 1.5e-174  1.5e-174 375
212284_x_at        14      14 696 5.6e-173  5.6e-173 373
208834_x_at        14      14 688 1.6e-172  1.6e-172 372

I have tried to create a histogram of the p values using the following commands in R:

hist(res$P.Value, col = brewer.pal(3, name = "Set2")[2],    main = "DDLPS vs WDLPS - Liposarcoma", xlab = "p-values")

I ended up with graph below:

My question is this graph correct? Thanks for your help.

[ATpoint]

Is this that here again? microarray differential expression analyses

Which contrast are you testing? This graph makes no sense, as all probes would be DE. Code please.

[ATpoint]

I guess this is your code: microarray analysis - gene upregulation/downregulation

As in my original comment from a week ago, you are testing the wrong contrast, coef=1 tests an intercept which has no meaning in this context. If you do not take suggestions from previous posts then there is no point posting questions or responding to it. Please stop opening identical questions, follow up on the original one.

[bioinformatics]

I did change the coef= 1 but had no significant value for a known DEG. So I decided to leave it as it was before. Yes that is the r script. I created the graph using command from this workflow: https://bioconductor.org/packages/release/workflows/vignettes/maEndToEnd/inst/doc/MA-Workflow.htm But my graph ended up looking a bit different to theirs

[ATpoint]

So I decided to leave it as it was before.

...you are testing a technical parameter with no meaning, all results are pointless with that parameter. I will withdraw at this point, your choice to either continue with this wrong analysis or to use given advise.

[bioinformatics]

Ok thanks for help. I will re-try the analysis with your suggestions. I used an r script from a tutorial so I thought it would be good to follow.

[bioinformatics]

I just tried with coef= 2 and have no significant values (less than 0.05). Do know why this might have occurred?