Data Science and Bioinformatics

Oluwasegun Daramola

Data Scientist

Data Visualizer

GitHub

Python

gaia - Geographic AI for Soil Assessment

App Link

streamlit

streamlit-option-menu

pandas

numpy

scikit-learn==1.2.2

joblib

catboost

plotly

The Land Use / Cover Area frame statistical Survey Soil (LUCAS Soil) dataset which is a European Union effort to survey European topsoil characteristics and Microbiome sequence data from the LUCAS Soil Survey for prokaryotes, fungi, and microeukaryotes. Avalaible here:

https://doi.plutof.ut.ee/doi/10.15156/BIO/2263453

Microbiome Bioinformatics Analysis

Set Up Qiime2 Environment Set up your Qiime2 environment by following the instructions from Qiime2 Documentation

Create Directories for Analysis Create two new directories: one for bacteria analysis and another for fungi analysis.

Organize Relevant Files Move all relevant files to their respective directories. Ensure that reference files from the respective databases (SILVA 138 for bacteria and UNITE QIIME release version 9.0 for fungi) are saved in their respective folders.

Download Files In each directory, use the following command to download the files specified in the _download_links.txt:

Create Manifest Files Use the provided manifest.sh files to generate the manifest files required for Qiime2 import.

Run Analysis Scripts Navigate to each directory and execute the analysis.sh files. Before running, review the content of these files to ensure that all necessary files are accounted for and modify the scripts as needed to suit your specific analysis requirements.

Info

Land Use / Cover Area frame statistical Survey Soil (LUCAS Soil) Dataset

LUCAS Interactive Maps

Global Soil Mycobiome consortium (GSMc) Dataset

Authors

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Posted Jun 15, 2024

To visualize geographical distributions of features and predictions as well as visualizations that provide informative summaries of the model data.

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Data Science and Bioinformatics

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