Hi all,

I hope some of you can shed light on this conundrum i have been having for a while. So, i have 8 studies downloaded from GEO including macrophages derived from different mouse tissues as the table shows:

```
Batch Subtype
1 BMDM
1 BMDM
1 BMDM
1 liver
1 liver
1 liver
1 lung
1 lung
1 lung
1 monocyte
1 monocyte
1 monocyte
1 monocyte
1 monocyte
1 monocyte
1 monocyte
1 monocyte
1 monocyte
1 monocyte
1 monocyte
1 monocyte
1 monocyte
1 monocyte
1 monocyte
1 monocyte
1 peritoneal
1 peritoneal
1 peritoneal
1 peritoneal
1 peritoneal
1 peritoneal
1 peritoneal
1 peritoneal
1 peritoneal
2 monocyte
2 monocyte
2 monocyte
2 TAM
2 TAM
2 TAM
2 TAM
2 TAM
3 peritoneal
3 peritoneal
3 peritoneal
3 peritoneal
3 peritoneal
3 peritoneal
3 peritoneal
3 peritoneal
4 peritoneal
4 peritoneal
4 peritoneal
4 peritoneal
4 peritoneal
4 peritoneal
4 peritoneal
4 peritoneal
5 BMDM
5 BMDM
5 BMDM
5 BMDM
5 BMDM
6 BMDM
6 BMDM
6 BMDM
7 BMDM
7 BMDM
7 BMDM
7 BMDM
7 BMDM
7 BMDM
8 TAM
8 TAM
8 TAM
```

I had removed many samples in order to be able to run the batch correction with ComBat. In specific, i had to remove every biological group which was not represented by at least 2 batches (I think) otherwise it throws an error. However the liver and lung samples are only in batch one and still the file was ok so i wonder how these samples were treated?. Ultimately my question is what is supposed to be a sensible setting to run through a batch correction algorithm? Is this one above a sensible one or not?

Thanks a lot

thanks for the answers. the samples are all of the same microaaray platform. I'm not sure anyway about all the strategy I did to be fair now. for example if I check there are no batch effect within every study but combining these together they show different average intensity which should be the way to go? could i first normalise for each study and then normalise again for all the study together? the PCA of the batch corrected arrays above in facts shows liver and lungs close together with the other monocytes for the same study meaning what you actually pointed out. Uhm...