Hello everyone,
Basically I have two files (healthy VS cancer tissu) containing TE (transposable) elements and their sub-classes.
After I have done a counting for one type of class LTR for example in the two files separately, found out that their were more present in cancer than in healthy tissue, so my question is:
- How can I do a fisher test to say that maybe the presence of LTR is related to cancer, whether it is significant or not?
Thank you for any answer or thought I can get from you.
Jas
E sub_classes TE classes
1 HAL1 LINE
2 HAL1 LINE
3 HAL1 LINE
4 L1M4 LINE
5 (CACCC)n Simple_repeat
6 L1M4 LINE
7 MSTD LTR
8 AluYc SINE
9 GC_rich Low_complexity
10 GC_rich Low_complexity
11 GC_rich Low_complexity
12 GC_rich Low_complexity
13 L2a LINE
14 (CCCCG)n Simple_repeat
15 GC_rich Low_complexity
16 (CCCA)n Simple_repeat
17 GC_rich Low_complexity
18 MLT1G1 LTR
19 MLT1H LTR
20 AluJb SINE
21 MLT1C LTR
1 answer
The four numbers you would need for a fishers test are:
- number of genes with TEs in healthy tissue
- number of genes without TEs in healthy tissue
- number of genes with TEs in cancerous tissue
- number of genes without TEs in cancerous tissue.
You can then make a matrix of that. You could alternatively count the number of TEs in genes or not in genes in both datasets and use that. Both are fine, but answer slightly different questions (the latter method is much less interesting if there's just a huge increase in TEs in one gene...).
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