Preliminary analysis reveals some NASA Data files produced by the GeneLab analysis team that should be easy to open, combine and visualise. This website was created to practice methods of presenting data analysis using the github to enable more collaboration. Ultimately the Space Biology and AstroBotany.io repo has the goal of making space biology data more FAIR. We aim to provide useful material for integrating Data from NASA Open Science Data Archive into future statistical analysis.
Simple challenges and short-term goals to help you improve and enable new analysis
Help develop the project wikipage
Help develop the project website development road map
Join the conversation here on the repo discussion board
This Google CoLab notebook above pulls data from the GeneLab API, there are mistakes in the python code that prevent it from plotting PCA reduction or viewing expression data on KEGG pathways correctly.
Please help me and see if you can fix the code?
https://github.com/dr-richard-barker/Space-Biology-Education.io/OSDR_API_demo_OSD-37.ipynb
Please consider co-developing this Google CoLab notebook, it is currently designed to pull data from an AstroBotany SpaceFlight experiment from the OSDR.
Solve the challenges feel free to use this notebook and please share your progress by saving it back into this repo!
This Public repo is where the code for this page "lives" and can evolve with your help!
You can push your edited version of the "Google Colab" notebook into this repo to save and share your results with collaborators around the world.
Example questions that can be asked of the meta-data and multi-omics integration
Metadata summary
A. Is there a simple way to sort and summarize the meta-data?
B. Is there a way to quantify the similarity of the accessions based on their metadata?
Multi-Omics data
C. Is there a way to merge normalized counts for heatmaps?
D. Is there a way to merge counts for statistical analysis?
E. Is there a way to merge multi-omics data?
Example questions that we should be able to ask of expression data
F. Is there a simple way to plot the normalized counts as a heat map?
G. Can the .html and other results files be viewed in the CoLab notebook?
H. Is there a way to view the differential expression data on Reactome pathways?
I. Is there a way to perform Geneset enrichment analysis of differentially expressed loci?
J. Is there a way to perform PCA, K-means and T-SNE clustering to identify functionally related co-expression clusters?
This prototype figure was made for artistic merit, it uses data projected onto a KEGG pathway that was then customised using Adobe Photoshop to aid with narrative development related to changes in membrane transport. There are several scientifically relevant data presentation issues with this figure, primarily there isn't a color scale, showing that red is up and blue is down in gene expression. This figure has some blurry text and can't evolve further highlighting how the use of "notebook-embedded" data visualisation synthesis has long-term advantages.