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Old 08-18-2014, 02:27 PM   #1
PabloV
Junior Member
 
Location: Santiago,Chile

Join Date: Aug 2014
Posts: 1
Default Help with induced genes using a two-factor model

Hi.

We would like to know which genes are induced for a model with 2 genotypes (Ga and Gb) and 2 treatments (T1 and T2). We are searching for genes induced in Ga under T2 treatment.

MODEL:
____| T1 | T2 |
Ga |3 rep.|2 rep.|
Gb |3 rep. |2 rep.|

DATA ANALYSIS:
Using DESeq2 we performed the following analysis:

counts: alignment and count from Rsubread

coldata:
condition genotype
M3_C1 T1 Gb
M3_C2 T1 Gb
M3_C3 T1 Gb
S3_C1 T2 Gb
S3_C2 T2 Gb
M3_W1 T1 Ga
M3_W2 T1 Ga
M3_W3 T1 Ga
S3_W2 T2 Ga
S3_W3 T2 Ga

Code:
#DESeq2 pipeline

dds <-DESeqDataSetFromMatrix(countData=counts,
colData=coldata,
design=~condition+genotype+condition:genotype)

dds <-DESeq(dds)

resultsNames(dds)
[1] "Intercept"                   "condition_T2_vs_T1"
[3] "genotype_Ga_vs_Gb"       "conditionT2.genotypeGa"
Extracting "conditionT2.genotypeGa" with the function results (dds) give us a set of genes. After selecting genes with padj<0.05 and log2foldchange>1.5, there are some genes induced more in T1 than T2. Other genes are more induced more in Gb than Ga.

So, I tried the next analysis:
Code:
resG <-results(ddsR,contrast=list("conditionT2.genotypeGa","genotype_Ga_vs_Gb"))
resT <-results(ddsR,contrast=list("conditionT2.genotypeGa","condition_T2_vs_T1"))
From resG and resT we selected only padj<0.05 and log2foldchange>1.5 genes

resG included some genes induces in T1 while resT included some genes induces in Gb. We identified genes which are present in both gene lists expecting genes induced in Ga under T2.

QUESTIONS:

Now we would like to know whether the data analysis was performed correctly.
Is there a better way to carry out the data analysis?

Thank you
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Old 08-25-2014, 01:38 AM   #2
Michael Love
Senior Member
 
Location: Boston

Join Date: Jul 2013
Posts: 333
Default

I'll just spell out what these results tables contain:

Code:
res1 = results(dds, name="conditionT2.genotypeGa")
are the genes for which there is a different treatment effect for the two genotypes (or equivalently, a different genotype effect for the two treatments)

Code:
res2 = results(dds,contrast=list("conditionT2.genotypeGa","genotype_Ga_vs_Gb"))
is the genotype effect for the treatment 2 group

Code:
res3 = results(dds,contrast=list("conditionT2.genotypeGa","condition_T2_vs_T1"))
is the treatment effect for the genotype Ga group

Quote:
We are searching for genes induced in Ga under T2 treatment.
These genes are contained in res2.
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conditions, deseq2, genotypes, induced genes, two factors

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