Hi,
My question refers to the multiple comparison done by LRT test. I though that this test would compare all the levels of a factor between them, but if I'm not mismatching...it is only comparing all the levels with the one I'm considering the "control" group. This is my experimental design:
Condition | Replicate | SampleName |
Control | R1 | AB3131 |
0.03ppm | R1 | AB3132 |
0.3ppm | R1 | AB3133 |
1ppm | R1 | AB3134 |
Control | R2 | AB3139 |
0.03ppm | R2 | AB3140 |
0.3ppm | R2 | AB3141 |
1ppm | R2 | AB3142 |
Control | R3 | AB3143 |
0.03ppm | R3 | AB3144 |
0.3ppm | R3 | AB3145 |
1ppm | R3 | AB3146 |
I run dds as follows:
dds <- DESeqDataSet(se, design = ~ Replicate + Condition) dds$Condition <- relevel(dds$Condition, "Control") ddsLRT <- DESeq(dds, test="LRT", full= ~ Replicate + Condition, reduced = ~ Replicate)
and this are the results:
resLRT <- results (ddsLRT)
log2 fold change (MLE): Condition 1ppm vs Control
LRT p-value: '~ Replicate + Condition' vs '~ Replicate'
DataFrame with 26873 rows and 6 columns
Now i'm interested to extract all the Log2FC of all comparisons, so I checked the results names to see the comparisons done by dds
resultsNames(ddsLRT)
I get the following:
[1] "Intercept" "Replicate_R2_vs_R1" "Replicate_R3_vs_R1"
[4] "Condition_0.03ppm_vs_Control" "Condition_0.3ppm_vs_Control" "Condition_1ppm_vs_Control"
so does that mean that the test did not compared for example condition 1ppm? vs 0.3ppm?
Hi Mike,
First of all thanks for all your patience and time dedicated to us. I think I have been mistaken these tests all the time. I have an appointment with a local statistician hoping to help me on this...but I had in my mind that doing the Walt test was similar to a t-test, and doing a LRT was similar to do an ANOVA. So is this statement wrong? I guess all the confusion comes from here...