Body: <p>Does anybody know of a C/C++ based implementation of the Louvain or Leiden algorithms that will take gene expression looking csv input files, with the genes in columns and the samples in rows, and perform community clustering on it? Something like
  @lh3lh3 <a href="https://github.com/lh3/bhtsne" rel="nofollow noreferrer">https://github.com/lh3/bhtsne</a> but for the community clustering algorithms.</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2023-06-27T10:03:54.893Z
Comments.Text: igraph does Leiden and Louvain clustering. It is a C/C++ library and used in R or Python.
Comments.UserDisplayName: M__
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2023-06-28T11:09:16.250Z
Comments.Text: Thanks, I looked at the igraph library but couldn't find out how to turn the matrix of input data (e.g. the 28x28 pixel data from mnist) into an input graph to run the community clustering method.
Comments.UserDisplayName: 719016
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2023-06-28T11:25:23.637Z
Comments.Text: I see. Personally I wouldn't use unsupervised learning for images (e.g. the MNIST data set), I'd use supervised learning: XGBoost is really cool for this BTW. Thus I dunno.
Comments.UserDisplayName: M__
Tags: <gene-expression><clustering>
Title: Louvain/Leiden community clustering implementation in C/C++ for gene expression data
ThreadText: # Louvain/Leiden community clustering implementation in C/C++ for gene expression data
  
  (Asked by: username_0 on 2023-06-27)
  
  Does anybody know of a C/C++ based implementation of the Louvain or Leiden algorithms that will take gene expression looking csv input files, with the genes in columns and the samples in rows, and perform community clustering on it? Something like
  @lh3lh3 <https://github.com/lh3/bhtsne> but for the community clustering algorithms.
  
  **Tags:** gene-expression, clustering
  
  > **Comments:**
  > **username_1**: igraph does Leiden and Louvain clustering. It is a C/C++ library and used in R or Python.  
  > **username_0**: Thanks, I looked at the igraph library but couldn't find out how to turn the matrix of input data (e.g. the 28x28 pixel data from mnist) into an input graph to run the community clustering method.  
  > **username_1**: I see. Personally I wouldn't use unsupervised learning for images (e.g. the MNIST data set), I'd use supervised learning: XGBoost is really cool for this BTW. Thus I dunno.  
  
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  ## 0 answers
  
  