[dpryan]

Swapping Healthy/Diabetic will just change the sign on the fold changes. With the updated version of "status", Normal/timepoint 1 is the baseline for all of the comparisons, which is how I expect you and others would want to think about the experiment. Previously it was Diabetic/timepoint 1.

Regarding the error message, just change the "maxit" option to something bigger to see if that goes away. The model is now rather more complicated, so I'm not surprised that it takes more iterations to fit. If you still have things not fitting, then see which rows they are and don't trust the results from them (the other 30,000 or so rows should be fine, however). The results should be from a paired-analysis then.

[sindrle]

Very good!
Ill start reading up on EdgeR later, the manual there had some nice sections on design.

Thank you again, have a nice weekend.

[nbahlis]

Hi Ryan,

DESeq2 question
Is the script below the correct way to set up a comparison between paired samples pre- and post treatment?
thank you
> sampleFiles <- list.files(path="~/Desktop/Realigned_to_human_g1K_v37/Cuffdiff_IMIDS_Nov/HTSeq/HTseq_gene_counts" , pattern="*.counts")
> Table3 <- data.frame(
+ row.names = c( "P110", "P124", "P149", "P185", "P189", "P192", "P218", "P227", "P235", "P280", "P308", "P351", "P357", "P367", "P377", "P384", "P426", "P543", "P584", "P590", "P594", "P610" ),
+
> sampleFiles <- list.files(path="~/Desktop/Realigned_to_human_g1K_v37/Cuffdiff_IMIDS_Nov/HTSeq/HTseq_gene_counts" , pattern="*.counts")
> Table3 <- data.frame(
+ sampleName = sampleFiles, fileName = sampleFiles,
+ condition = c( "pre", "pre", "pre", "pre", "pre", "pre", "pre", "pre", "pre", "post", "pre", "post", "post", "post", "post", "post", "post", "post", "post", "post" ),
+ libType = c( "pair8", "pair10", "pair9", "pair1", "pair7", "pair11", "pair2", "pair3", "pair4", "pair5", "pair5", "pair6", "pair7", "pair1", "pair3", "pair4", "pair11", "pair2", "pair6", "pair10", "pair9", "pair8" ) )
Error in data.frame(sampleName = sampleFiles, fileName = sampleFiles, :
arguments imply differing number of rows: 22, 20
> Table3 <- data.frame(
+ sampleName = sampleFiles, fileName = sampleFiles,
+ condition = c( "pre", "pre", "pre", "pre", "pre", "pre", "pre", "pre", "pre", "pre", "post", "pre", "post", "post", "post", "post", "post", "post", "post", "post", "post", "post" ),
+ libType = c( "pair8", "pair10", "pair9", "pair1", "pair7", "pair11", "pair2", "pair3", "pair4", "pair5", "pair5", "pair6", "pair7", "pair1", "pair3", "pair4", "pair11", "pair2", "pair6", "pair10", "pair9", "pair8" ) )
> directory <- c("~/Desktop/Realigned_to_human_g1K_v37/Cuffdiff_IMIDS_Nov/HTSeq/HTseq_gene_counts/")
> design <- formula(~ libType + condition)
> ddsHTSeq <- DESeqDataSetFromHTSeqCount(sampleTable= Table3, directory= directory, design= design)
> Table3
sampleName fileName condition libType
1 P110.counts P110.counts pre pair8
2 P124.counts P124.counts pre pair10
3 P149.counts P149.counts pre pair9
4 P185.counts P185.counts pre pair1
5 P189.counts P189.counts pre pair7
6 P192.counts P192.counts pre pair11
7 P218.counts P218.counts pre pair2
8 P227.counts P227.counts pre pair3
9 P235.counts P235.counts pre pair4
10 P280.counts P280.counts pre pair5
11 P308.counts P308.counts post pair5
12 P351.counts P351.counts pre pair6
13 P357.counts P357.counts post pair7
14 P367.counts P367.counts post pair1
15 P377.counts P377.counts post pair3
16 P384.counts P384.counts post pair4
17 P426.counts P426.counts post pair11
18 P543.counts P543.counts post pair2
19 P584.counts P584.counts post pair6
20 P590.counts P590.counts post pair10
21 P594.counts P594.counts post pair9
22 P610.counts P610.counts post pair8

Many thanks

[dpryan]

That appears to be correct. That doesn't look for any pair:treatment interaction, but that's likely not of interest (and would really suck up the degrees of freedom).

[nbahlis]

thank you for the quick reply. I am attempting to identify genes involved in resistance to treatment "X". RNAseq were done on samples collected from individual patients pre-treatment and at the time of clinical progression (resistant). Therefore I think I need to account for pair:treatment interaction, no? I am not sure how to account for this interaction in my script. Greatly appreciate your advice.

[dpryan]

If the patients were similarly responsive, then accounting for an interaction is probably overkill. Otherwise you just need to change the design to "design~libType*condition".

[nbahlis]

thank you, I will give this a try and see if the results differ significantly

[emma009]

Thanks!

Thanks for the help - worked once I sorted out my typos...