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  • Installation
  • API Guide
    • AggMap
    • AggMapNet
    • Useful Functions
  • Hyperparameters
    • AggMap HPs
      • The important hyperparameters in AggMap feature restructuring
      • Code example of AggMap feature restructuring.
    • AggMapNet HPs
      • The important hyperparameters in AggMapNet
      • Code example of AggMapNet modelling
    • AggMapNet Explainers
      • Code example of AggMapNet model explaination
      • Simply-explainer vs. Shapley-explainer
      • References
  • Examples
    • MNIST reconstruction from pixel random permutation
      • Introduction
      • Step0: Import AggMap and Orignal MNIST data
      • Step1: MNIST pixel random permutation
      • Step2: AggMap pre-fitting on training set
      • Step3: AggMap transformation on training and test test
      • Step4: AggMap visualization
    • Fashion-MNIST reconstruction from pixel random permutation
      • Introduction
      • Step1: MNIST pixel random permutation
      • Step2: AggMap pre-fitting on training set
      • Step3: AggMap transformation on training and test test
    • Pick up stage-specific genes in cell cycle data
      • Introduction
      • Read data and pre-fit on AggMap
      • Transform the data by AggMap
      • Multi-channel Fmaps
      • Single-channel Fmaps
      • Visulization
        • 01.scatter plot
        • 02.grid plot
        • 03.tree plot
    • Metagenomic deep learning and biomarker discovery
      • 1. Introduction
        • 1.1 MEGMA introduction
        • 1.2 Metagenomic cross nation datasets and tasks
        • 1.3 MEGMA fitting and AggMapNet training strategy
      • 2. MEGMA Training & Transformation
        • 2.1 Fitting MEGMA on metagenomic abundance data of all countries
          • 2.1.1 Read and preprocess data for MEGMA
          • 2.1.2 MEGMA initialization, fitting and dump
          • 2.1.3 MEGMA loading and 2D-microbiomeprints transformation
          • 2.1.4 MEGMA 2D-microbiomeprints visulization
          • 2.1.5 Well-trained MEGMA to transform the abundance data of each country
        • 2.2 Fitting MEGMA on metagenomic abundance data of one country only
          • 2.2.1 Read and preprocess data for MEGMA
          • 2.2.2 MEGMA initialization & fitting
          • 2.2.3 MEGMA 2D-microbiomeprints transformation
          • 2.2.4 MEGMA Fmaps visulization
          • 2.2.5 Transform the abandance data of the rest countries by country-specific MEGMA
          • 2.2.6 Fitting country-specific megma for all countries
        • 2.3 Discussions & conclusions on MEGMA 2D-microbiomeprints
      • 3. Training the CRC detection models based on MEGMA Fmaps
        • 3.1 Training and test AggMapNet on overall MEGMA Fmaps
        • 3.2 Training and test AggMapNet on country specific MEGMA Fmaps
        • 3.3 Comparing the STST performance and discussion
      • 4. Important microbial marker identification
        • 4.1 Calculate the global feature importance
          • 4.1.1 GFI for model trained on overall MEGMA Fmaps
          • 4.1.2 GFI for model trained on country specific MEGMA Fmaps
        • 4.2 Generate the explaination saliency map
          • 4.2.1 Saliency map for overall MEGMA Fmaps
          • 4.2.2 Saliency map country specific MEGMA Fmaps
        • 4.3 Global feature importance correlation
        • 4.4 Discussions and conclusions on saliency map
      • 5. Toplogical analyisis on the important microbes
        • 5.1 Plotting the the embedded and arranged microbes
        • 5.2 Plotting the linear assignment of the embedded microbes
        • 5.3 Fetching the optimized toplogical graph and clustering
        • 5.4 Exploring the toplogical relationship of the important microbes
      • 6. Exploring the embedding & grouping in MEGMA
        • 6.1 Microbial embedding
          • 6.1.1 Manifold embedding
          • 6.1.2 Ramdom embedding
        • 6.2 Microbial grouping
          • 6.2.1 Hierarchical clustering tree based grouping
          • 6.2.2 Taxonomic tree based grouping
  • Performances
  • Modules
    • aggmap package
      • Subpackages
        • aggmap.aggmodel package
          • Submodules
          • aggmap.aggmodel.cbks module
          • aggmap.aggmodel.explain_dev module
          • aggmap.aggmodel.explainer module
          • aggmap.aggmodel.loss module
          • aggmap.aggmodel.net module
          • Module contents
        • aggmap.utils package
          • Submodules
          • aggmap.utils.calculator module
          • aggmap.utils.distances module
          • aggmap.utils.gen_nwk module
          • aggmap.utils.logtools module
          • aggmap.utils.matrixopt module
          • aggmap.utils.multiproc module
          • aggmap.utils.summary module
          • aggmap.utils.vismap module
          • Module contents
      • Submodules
      • aggmap.AggMapNet module
      • aggmap.map module
      • aggmap.show module
      • Module contents
    • aggmap.utils package
      • Submodules
      • aggmap.utils.calculator module
      • aggmap.utils.distances module
      • aggmap.utils.gen_nwk module
      • aggmap.utils.logtools module
      • aggmap.utils.matrixopt module
      • aggmap.utils.multiproc module
      • aggmap.utils.summary module
      • aggmap.utils.vismap module
      • Module contents
    • aggmap.aggmodel package
      • Submodules
      • aggmap.aggmodel.cbks module
      • aggmap.aggmodel.explain_dev module
      • aggmap.aggmodel.explainer module
      • aggmap.aggmodel.loss module
      • aggmap.aggmodel.net module
      • Module contents
aggmap
  • Overview: module code

All modules for which code is available

  • aggmap.AggMapNet
  • aggmap.aggmodel.cbks
  • aggmap.aggmodel.explain_dev
  • aggmap.aggmodel.explainer
  • aggmap.aggmodel.loss
  • aggmap.aggmodel.net
  • aggmap.map
  • aggmap.show
  • aggmap.utils.calculator
  • aggmap.utils.distances
  • aggmap.utils.gen_nwk
  • aggmap.utils.logtools
  • aggmap.utils.matrixopt
  • aggmap.utils.multiproc
  • aggmap.utils.summary
  • aggmap.utils.vismap

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