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base repository: ctlab/ImmGenOpenSource
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Commits on Jan 14, 2020

  1. Merge pull request #2 from ctlab/master

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    anastasiiaNG authored Jan 14, 2020
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Commits on Feb 8, 2020

  1. adding files for GEO

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Commits on Dec 29, 2022

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2 changes: 1 addition & 1 deletion LICENSE
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MIT License

Copyright (c) 2019 Computer Technologies Laboratory
Copyright (c) 2022 artyomovlab

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
18 changes: 5 additions & 13 deletions README.md
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> GAM-clustering provides metabolic variability within dataset using a novel network-based computational approach that utilizes cellular transcriptional profiles as proxies. The metabolic network of reactions from KEGG database is presented as a graph that has vertices corresponding to metabolites and the edges corresponding to the reactions with the expressed genes. In the graph the method tries to find a set of connected subgraphs, with each corresponding well to a certain gene expression pattern. Curret analysis reveals the major metabolic features associated with different subpopulations and highlights a number of metabolic modules that are specific to individual cell types, tissues of residence, or developmental stages.
To explore data visit the following links:
- [Gene expression heatmap](https://artyomovlab.wustl.edu/phantasus/?preloaded=ImmGen_total_Eduw0mei4)
- [PCA with samples annotation](http://artyomovlab.wustl.edu/publications/supp_materials/Immgen/PCADatasetOverview.html)
- [Heatmap of metabolic modules](https://artyomovlab.wustl.edu/phantasus/?session=x039baa087a35e7)

## Requirments
- [R](https://www.r-project.org/)
- [sgmwcs-solver](https://github.com/ctlab/sgmwcs-solver)
- [KEGG mouse metabolic network](GAM)
To explore data visit the following [interactive browser](https://artyomovlab.wustl.edu/immgen-met/).

## Input data
[Raw counts](Data/OSMNP_unnormalized_genes_count_10_3_18.count_table) are processed by [rawDataProcessing.R]() script and the output object `es.top12k` has the following structure:
[Raw counts](Data/OSMNP_unnormalized_genes_count_10_3_18.count_table) are processed by [`rawDataProcessing.R`](rawDataProcessing.R) script and the output object `es.top12k` has the following structure:

``` r
> load("Data/337_es.top12k.Rda")
@@ -33,15 +25,15 @@ To explore data visit the following links:
```

## Modules deriving
The initial patterns are defined using k-means clustering on gene expression matrix and then are refined in an iterative process using the network connections ([modulesDeriving.R]()).
The initial patterns are defined using k-means clustering on gene expression matrix and then are refined in an iterative process using the network connections ([`modulesDeriving.R`](modulesDeriving.R)).
The final output presents a set of specific subnetworks (also called metabolic modules) that reflect metabolic variability within a given transcriptional dataset.
Each metabolic module is a piece of metabolic network whose gene expression has correlated expression pattern across all dataset. The following graph and heatmap represent network and constituting genes' expression for module 5, correspondingly:
![module5](/readmePics/github.pic.m5.png "network and gene expression heatmap for module 5")
Averaged gene expression of all modules is represented at the following summary heatmap:
![centers](/readmePics/github.m.centers.png "centers heatmap")

## Modules annotation
Functional annotation of obtained modules is based on KEGG and Reactome canonical pathways ([modulesAnnotation.R]()).
Functional annotation of obtained modules is based on KEGG and Reactome canonical pathways ([`modulesAnnotation.R`](modulesAnnotation.R)).
The following example is devoted to module 5 (k - number of module genes in a particular pathway, K - number of genen in a particular pathway):
``` r
> paths <- data.table::fread("Data/m.5.pathways_mod.tsv")
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## 1: R-MMU-191273 1.009604e-48 17 24 1.237774e-45 Cholesterol biosynthesis Hmgcs1 Hmgcr Msmo1 Cyp51 Mvd ...
## 2: R-MMU-8957322 9.801101e-39 17 67 6.008075e-36 Metabolism of steroids Hmgcs1 Hmgcr Msmo1 Cyp51 Mvd ...
## 3: R-MMU-556833 1.406903e-27 18 395 5.749543e-25 Metabolism of lipids Hmgcs1 Hmgcr Msmo1 Cyp51 Aacs ...
```
```