What color is assigned in heatmap for time series analysis
2
0
Entering edit mode
rahel14350 ▴ 10
@rahel14350-8472
Last seen 2.5 years ago
United States

Dear all,

can anyone help me with this question which I added in Biostar (https://www.biostars.org/p/197038/)

I pasted here to make it easier:

I did DEG analysis for two condition with 5 time points using deseq2. In heatmap I have one colour for each DEG with lowest p- value which represent log2 fold change (wald test) for each deg in time 0. My question is that I have 4 sample in time point 1 vs 4 sample in time 0. But I see only one colour for all, as time0-vs-1. Is this colour from mean or median of all LFCs of 4 samples? Or there is an algorithm behind that in heatmap? Many thank in advance for your help, Cheers, Rahel

deseq2 time course heatmap • 983 views
ADD COMMENT
0
Entering edit mode
@mikelove
Last seen 1 day ago
United States

You'll need to post your code, specifically the design of the dds, how you ran DESeq(), how you created the heatmap, and it's also useful for me to see the structure of the colData.

as.data.frame(colData)

Also you should as habit include the sessionInfo() when posting to Bioconductor support site.

ADD COMMENT
0
Entering edit mode

Dear Michael,

Many thanks for your reply. I have two treatment response (R, NR) and 7 time points. I want to see DEGs in responses to treatment over time courses. Here is the Deseq2 comment:

> ddsTC<-DESeqDataSetFromHTSeqCount(sampleTable=sampleTable, directory=directory, design=~IFX_response+time+ IFX_response:time)

> ddsTC <- DESeq(ddsTC, test="LRT", reduced = ~IFX_response + time)

> colData(ddsTC)
DataFrame with 61 rows and 4 columns
time IFX_response sizeFactor replaceable
<factor>     <factor>  <numeric>   <logical>
01_0h_IFX_NR_P21_F02312.txt    01_0h       IFX_NR   1.206895       FALSE
01_0h_IFX_NR_P23_F02269.txt    01_0h       IFX_NR   1.024494       FALSE
...                              ...          ...        ...         ...
07_14w_IFX_R_P13_E02898.txt   07_14w        IFX_R  0.7851559        TRUE
07_14w_IFX_R_P14_E02900.txt   07_14w        IFX_R  1.0228529        TRUE

> resTC <- results(ddsTC)

> betas <- coef(ddsTC)

> colnames(betas)

But when I make the pheatmap with exact command from Deseq2:

> topGenes <- head(order(resTC\$padj),50)

> mat <- betas[topGenes, -c(1,2)]

> thr <- 3

> mat[mat < -thr] <- -thr

> mat[mat > thr] <- thr

> pheatmap(mat,breaks=seq(from=-thr, to=thr, length=101),border_color="NA",cluster_col=FALSE)

I get one color bulk for each of time point in comparison to time 0.

http://i.imgur.com/PqrnJQY.jpg

My question is that how from 4 replicate per time point, I got one colour bulk per time point? Is that correct to the genes are picked by p-value, colored by LFC and each bulk is presenting the mean normalized rad count of 4 samples?
I hope I made it clear.
Cheers,
Rahel

ADD REPLY
0
Entering edit mode

Yes, in the code above you picked genes by adjusted p value, and the color is the log2 fold change.

But, no, the color in the cell is not the mean normalized read count of the 4 samples.

The color is the log2 fold change estimated by comparing the 4 samples with the other 4 samples. The log2 fold change is a parameter estimated by DESeq2. The details on how this is estimated can be found in the vignette or for full details you can read the DESeq2 paper.

ADD REPLY
0
Entering edit mode

Many many thanks for your prompt reply, and also for such an amazing program which helped me a lot through my work. I get my answer and I will read your paper before sending the next question ...

Cheers,

Rahel

ADD REPLY
0
Entering edit mode
EagleEye ▴ 10
@eagleeye-9825
Last seen 4.2 years ago

It will be nice to use,

1. RPKM/FPKM values or any normalized expression values

2. Calculate z-score

3. Use pheatmap to see clear picture of your time-series data.

ADD COMMENT

Login before adding your answer.

Traffic: 162 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6