continous variable and limma
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@grammatcsduocgr-4751
Last seen 9.6 years ago
Hello All, I have an dataset like the one below: S1.CEL S2.CEL S3.CEL S4.CEL S5.CEL S6.CEL S7.CEL S8.CEL S9.CEL S10.CEL S11.CEL 1415670_at 3.147518 3.173544 3.169437 3.136441 3.143318 3.149240 3.164243 3.058996 3.113238 3.189297 3.132998 1415671_at 3.416794 3.359792 3.355241 3.348604 3.386615 3.370229 3.370467 3.377304 3.431597 3.378310 3.382426 1415672_at 3.387410 3.398707 3.417004 3.423049 3.380673 3.397461 3.432254 3.421259 3.381972 3.395363 3.429707 1415673_at 3.122923 2.837839 3.024192 2.843976 3.057093 2.912823 3.029993 2.878526 3.075537 2.897501 3.019125 1415674_a_at 3.233006 3.263457 3.257603 3.231753 3.200804 3.177175 3.202201 3.231453 3.200878 3.222942 3.215434 1415675_at 3.097188 3.115366 3.162549 3.124800 3.080499 3.057393 3.137030 3.136152 3.054494 3.083940 3.115158 and an index X genotype Orgaan tijdspunt 1 S1.CEL WT kidney 13 2 S2.CEL WT liver 13 3 S3.CEL WT spleen 13 4 S4.CEL WT lung 13 5 S5.CEL WT kidney 13 6 S6.CEL WT liver 13 ... Actually the design of my study is a little bit more complex: I have more than 2 time points and i want to model time as a continous variable. I have 4 tissues and 2 mouse types. Questions: 1. How could I find the the genes that significantly change over time separately in each tissue? 2. How could I statistically compare the slopes over time of the same gene between 2 or more tissue?
Kidney Lung Kidney Lung • 671 views
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