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Refactoring the oncoscape core (14 dec 2015)
These notes propose some simple changes to Oncoscape in order to create a more flexible server. The principal change is the use of [the Factory Pattern](…
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## 🚀 Feature
An incremental version of pca_lowrank - processing a mini-batch of samples in each iteration.
Similar to sklearn.decomposition.IncrementalPCA(), but in GPU.
## Motivation
The curr…
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Hi,
I was eager to run this and see what it produces. I do lots of quantitative phosphoproteomics and have always been dissatisfied with the s/w for analysis. I was hopeful that this might do a bun…
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Hi Florian,
When I was running go-pca.py, I got the following errors:
---------------------------------------------------------------------------------------
Traceback (most recent call last):
…
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- [ X] New analysis tool: A simple analysis tool you have been using and are missing in `sc.tools`?
It may be useful to adopt a PCA option similar to **`multiBatchPCA`** in the R batchelor pack…
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I am getting an error of `Error: Error in analysis(x): object 'splits' not found`
Splits and Features:
```r
splits %
step_normalize(contains("index.num"), contains("date_col_year"))
recip…
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Principal component analysis (PCA) gives a handle to calculate the direction and degree of anisotropy in a 2D scattering image. It can be performed based on a Singular Value Decomposition (SVD) of the…
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As demostrated below:
```
hs3163@node57:/mnt/vast/hpc/csg/snuc_pseudo_bulk/eight_celltypes_analysis$ cat /mnt/vast/hpc/csg/snuc_pseudo_bulk/eight_celltypes_analysis/8_celltypes_script_3 | grep sos …
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Dear all,
I am kind of lost how to deal with the results of ALRA.
When I process a Seurat object with ALRA I get a new assay. How do I then use the ALRA computed data to do a UMAP or TSNE reductio…
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By default, the function normalizes the PCA percent variance explained results around 0 and then selects all positive (above average) components for dimensional analysis. I would like to implement 'st…