Hi everybody !
I'm a PhD student trying to analyse Chip-seq data generated in my project but I'm loosing it to use properly DiffBind package even if I read several times the manual.
To illustrate my work :
Chip-seq on flies:
- 3 Lineages (A, B and C) x 3 treatments control included (CT, PQ, CO) x 2 histones mark K4 and K9 x 2 replicas per conditions (ov1 and ov2)
= 36 samples analyzed, 18 for K4 and 18 for K9.
My questions are :
- Effect of treatments per lineage ?:
In lineage A i want to contrast control (CT) against CO or PQ and the same thing for other lineages
- Effect of lineages per treatment? :
In treatment CO, difference between A and B , B and C...
If I understand the Diffbind package usage :
- I imported data in a csv format with .bam file for sequence informations, and peak caller data obtained from Peak ranger software
I used to import :
samples_k4 <- read.table(data-sheet) chip_k4 <- dba(sampleSheet =samples_k4)
Then I used the count option which count peaks in the peak caller datasif I understand but I didn't understand if it use information of input data given
chip_k4_count <- dba.count(chip_k4, summits = 250, bParallel = F)
After counting I used the option to generate contrast
chip_k4_contrast <- dba.contrast(chip_k4_count, categories = c(DBA_CONDITION, DBA_TISSUE)
To show contrast possibility I used
dba.show(chip_k4_contrast, bcontrast = T)
And now problems...
For example the contrast between lineages, group1 = A vs group2 = B take all sample of the lineage A and B so control and other treatment together...
But I want group1 = A:CT vs group2= B:CT How to use a fixed factor as the treatment, I tried with block option without success.
How work Diffbind with replicas ? Because I want to made Ven Graph after and when i tried, I obtained graph with specific replicas and no a global effect.
Thanks for every effort to help me !