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hi here, in your tutorial, you did normalize and batch correct before pca. However in most tutorial like seurat and scanpy, we did scale data before find HVGs and pca. As we all know, PCA or any other…
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PCA correlation matrix plot, sorted by similarity, might be good to see which variable has most effect in PC0/PC1. https://www.reneshbedre.com/blog/principal-component-analysis.html#perform-pca-using-…
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Hi Biafra,
We are wondering what exactly are we getting in the traces from the PCA-ICA analysis?
Looking at the traces stored in the PCA-ICA output.mat file we noticed some have negative values. S…
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Illustrate the principal components with top/bottom working group tags.
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## General strategy
- the data warehousing project are usually "beyond just meeting the project requirement" to get good mark. It is recommended to use more than 2 approach to arrive to the same re…
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PCA是機器學習中的一個方法 稱作降維，顧名思義就是降低維度。
PCA 雖然可以用作降維, 不過他的意思是主成分分析吧? Principal components analysis
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**Describe the bug**
Using cuml.PCA with `set_global_device_type` to 'CPU' and 'GPU' produce different results (with `set_global_device_type('CPU')` matching the output of sklearn's PCA).
**Steps/…
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Hi,
I used GAPIT few months ago and it worked perfectly, Now i ran GAPIT functions after getting new data and these errors pops out. I tried using the old data as it is, but same happens. Please H…
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@xiaoyeye great tool! when I run analysis get error like this.
The adata file is a subset of a big file and then merge with the velocyto file.
```
(TFvelo_env) dengzhen@dengzhen-Super-Server:~/co…
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# Primary user story
As a voter,
I want to see myself as well as the candidates and parties plotted on a visual map,
so that I can understand the totality of political options better.
# Supporting u…