Question: Differential analysis of multiple samples with different time points
0
6 months ago by
Firas0
Firas0 wrote:

Hello,

I have the following samples, with three replicates in each of them:

Time point Population Genotype1 Genotype2
00h Precursor WT KO
06h Subset A WT KO
18h Subset A WT KO
72h Subset A WT KO
06h Subset B WT KO
18h Subset B WT KO
72h Subset B WT KO

My biological setup:

• I started with 2 samples of Precursor (considered also as 00h): KO or WT.
• Then differentiated them under two different conditions (Subset A and Subset B).
• The samples at different time points are collected from separated wells.

What I would like to analyse:

• the effect of WT vs KO across all samples
• taking the WT alone, the effects of Subset A vs Subset B
• taking the WT alone, the effects of Precursor vs Subset A or Subset B

I would like to get some help on how to set up contrasts for this experiment.

Many thanks

diffbind R atac-seq • 266 views
modified 6 months ago by Rory Stark2.8k • written 6 months ago by Firas0
Answer: Differential analysis of multiple samples with different time points
3
6 months ago by
Rory Stark2.8k
CRUK, Cambridge, UK
Rory Stark2.8k wrote:

If you want to track the differences across time between two groups in a single comparison, DiffBind is not really set up to do that. You'd need to use one of the underlying analysis methods, like DESeq2, directly. There are a number of threads discussing how to set up time series analyses in DESeq2

There are several things you can do in DiffBind, provided you set up the metadata in a useful way.For example, if you set:

• DBA_TISSUE to be Precursor, SubsetA, or SubsetB
• DBA_CONDITION to be WT or KO (you can rename it Genotype for display purposes)
• DBA_TREATMENT to be T00, T06, T18, or T72 (you can rename it Timepoint for display purposes)
• DBA_REPLICATE to be 1, 2, or 3

then you can compare:

• Overall differences between WT and KO, across all time points but independent of genotype:
dba.contrast(myDBA, group1=myDBA$masks$WT, group2=myDBA$masks$KO,
block=DBA_TISSUE)
• Overall differences between WT and KO, across either genotype but independent of time:
dba.contrast(myDBA, group1=myDBA$masks$WT, group2=myDBA$masks$KO,
block=DBA_TREATMENT)
• Differences between Genotypes A and B in WT, independent of time point:
dba.contrast(myDBA, group1=myDBA$masks$WT&myDBA$masks$SubsetA,
group2=myDBA$masks$WT&myDBA$masks$SubsetB,
block=DBA_TREATMENT)
• Differences between Genotypes A and B in WT at a specific timepoint:
dba.contrast(myDBA, group1=myDBA$masks$WT&myDBA$masks$SubsetA&myDBA$masks$T18,
group2=myDBA$masks$WT&myDBA$masks$SubsetB&myDBA$masks$T18)
• Differences between Precursor and each of the Genotypes in WT, independent of time point:
dba.contrast(myDBA, group1=myDBA$masks$WT&myDBA$masks$Precursor,
group2=myDBA$masks$WT&myDBA$masks$SubsetA,
block=DBA_TREATMENT)
dba.contrast(myDBA, group1=myDBA$masks$WT&myDBA$masks$Precursor,
group2=myDBA$masks$WT&myDBA$masks$SubsetB,
block=DBA_TREATMENT)
• And at a specific timepoint:
dba.contrast(myDBA, group1=myDBA$masks$WT&myDBA$masks$Precursor&
myDBA$masks$T18,
group2=myDBA$masks$WT&myDBA$masks$SubsetA&
myDBA$masks$T18)