I have a dataset associated with two factors(Stage and Form). Stage has 4 conditions and Form has two conditions:
Stage Form
DS1_Wr60 Wr60 DS
DS2_Wr60 Wr60 DS
DS3_Wr60 Wr60 DS
DS4_Wr60 Wr60 DS
WS1_Wr60 Wr60 WS
WS2_Wr60 Wr60 WS
WS3_Wr60 Wr60 WS
WS4_Wr60 Wr60 WS
DS1_PP50 PP50 DS
DS2_PP50 PP50 DS
DS3_PP50 PP50 DS
DS4_PP50 PP50 DS
WS1_PP50 PP50 WS
WS2_PP50 PP50 WS
WS3_PP50 PP50 WS
WS4_PP50 PP50 WS
DS1_P15 P15 DS
DS2_P15 P15 DS
DS3_P15 P15 DS
DS4_P15 P15 DS
WS1_P15 P15 WS
WS2_P15 P15 WS
WS3_P15 P15 WS
WS4_P15 P15 WS
DS1_P50 P50 DS
DS2_P50 P50 DS
DS3_P50 P50 DS
DS4_P50 P50 DS
WS1_P50 P50 WS
WS2_P50 P50 WS
WS3_P50 P50 WS
WS4_P50 P50 WS
I performed deseq2 analysis like this:
col_data <- data.frame(row.names = colnames(count_data),Stage,Form)
dds <- DESeqDataSetFromMatrix(countData = count_data,colData = col_data,design = ~ Stage+Form)
> dds_out <- DESeq(dds_filter)
estimating size factors
estimating dispersions
gene-wise dispersion estimates
mean-dispersion relationship
final dispersion estimates
fitting model and testing
> resultsNames(dds_out)
[1] "Intercept" "Stage_P50_vs_P15" "Stage_PP50_vs_P15" "Stage_Wr60_vs_P15" "Form_WS_vs_DS"
I understand the other comparisons made but what about the "Intercept"? What does it indicate?
Hi, thank you for your reply. Could you elaborate more in the context of my specific case? When I look into the intercept result it still shows some genes up and down...What does it mean?
I mean genes are up- or down-regulated in the intercept result. How can I interpret this? What comparison did it make?
> res <- results(dds_out,name = "Intercept")
> summary(res)
out of 19287 with nonzero total read count
adjusted p-value < 0.1
LFC > 0 (up) : 13119, 68%
LFC < 0 (down) : 461, 2.4%
outliers [1] : 161, 0.83%
low counts [2] : 0, 0%
(mean count < 0)
[1] see 'cooksCutoff' argument of ?results
[2] see 'independentFiltering' argument of ?results
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