I am currently working with single cell data from human and zebrafish both from brain tissue! My assignment is to integrate them! So the steps I have followed until now :
Find human orthologs for zebrafish genes in biomart
kept only the one2one
subset the zebrafish Seurat object based on the orthlogs and replace the names with the human gene names
Create an new Object for zebrafish and run Normalization anad FindVariableFeatures
Then use this object with my human object for integration
Human object: 20620 features across 2989 samples
Zebrafish object: 6721 features across 6036 samples
features <- SelectIntegrationFeatures(object.list = double.list)
anchors <- FindIntegrationAnchors(object.list = double.list,
anchor.features = features,
normalization.method="LogNormalize",
nn.method="rann")
This identifies 2085 anchors! I used nn.method="rann" because if I use the default I have this error
Error: C stack usage 7973252 is too close to the limit
Then I am running the integration like this
ZF_HUMAN.combined <- IntegrateData(anchorset = anchors,
new.assay.name = "integrated")
and the error I am receiving is like this
Scaling features for provided objects
|++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s
Finding all pairwise anchors
| | 0 % ~calculating Running CCA
Merging objects
Finding neighborhoods
Finding anchors
Found 9265 anchors
Filtering anchors
Retained 2085 anchors
|++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=22s
To solve this I tried to play around with the arguments in FindIntegrationAnchors e.g i used l2.norm=F! The only things that changed is the number of anchors which decreased
I am wondering if the usage of nn.method="rann" at FindIntegrationAnchors messing things up ANY help will be appreciated because I am struggling for a long time with that, I don't know what else to do
