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sally.badawi
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@sallybadawi-16174
Last seen 5.7 years ago
Hi all,
I would like to use DESeq2 to analyze a time series experiment of 6 time points each time point with 8 replicates. 3 time points are made in different time than the others, therefore they have a different batch.
My aim is to detect the genes varying over time in response to the treatment I'm doing.
While trying to include batch in the design its giving the error model matrix not full rank. When analyzing without including batch effect, I get a high number of significant genes and PCA plot is clustering samples based on batch not on time. Any help with this?
| Sample ID | time | batch |
| Sham0.1 | t0 | b1 |
| Sham0.2 | t0 | b1 |
| Sham0.3 | t0 | b1 |
| Sham0.4 | t0 | b1 |
| Sham0.5 | t0 | b1 |
| Sham0.6 | t0 | b1 |
| Sham0.7 | t0 | b1 |
| Sham0.8 | t0 | b1 |
| Sham15I.1 | t1 | b2 |
| Sham15I.2 | t1 | b2 |
| Sham15I.3 | t1 | b2 |
| Sham15I.4 | t1 | b2 |
| Sham15I.5 | t1 | b2 |
| Sham15I.6 | t1 | b2 |
| Sham15I.7 | t1 | b2 |
| Sham15I.8 | t1 | b2 |
| Sham45.1 | t2 | b1 |
| Sham45.2 | t2 | b1 |
| Sham45.3 | t2 | b1 |
| Sham45.4 | t2 | b1 |
| Sham45.5 | t2 | b1 |
| Sham45.6 | t2 | b1 |
| Sham45.7 | t2 | b1 |
| Sham45.8 | t2 | b1 |
| Sham15IR.1 | t3 | b2 |
| Sham15IR.2 | t3 | b2 |
| Sham15IR.3 | t3 | b2 |
| Sham15IR.4 | t3 | b2 |
| Sham15IR.5 | t3 | b2 |
| Sham15IR.6 | t3 | b2 |
| Sham15IR.7 | t3 | b2 |
| Sham15IR.8 | t3 | b2 |
| Sham1hrIR.1 | t4 | b2 |
| Sham1hrIR.2 | t4 | b2 |
| Sham1hrIR.3 | t4 | b2 |
| Sham1hrIR.4 | t4 | b2 |
| Sham1hrIR.5 | t4 | b2 |
| Sham1hrIR.6 | t4 | b2 |
| Sham1hrIR.7 | t4 | b2 |
| Sham1hrIR.8 | t5 | b2 |
| Sham24.1 | t5 | b1 |
| Sham24.2 | t5 | b1 |
| Sham24.3 | t5 | b1 |
| Sham24.4 | t5 | b1 |
| Sham24.5 | t5 | b1 |
| Sham24.6 | t5 | b1 |
| Sham24.7 | t5 | b1 |
| Sham24.8 | t5 | b1 |
design~ batch + time and for deseq function LRT test with reduced~batch
Thank you in advance for the help
