I will do transcriptomics data analysis and visualization with r or python

I provide transcriptomics data analysis including RNA-seq expression analysis, statistical testing, visualization (PCA, heatmaps, volcano plots), and basic machine learning modeling for classification and biological interpretation using R or Python.

Transcriptomics Analysis includes:

• RNA-seq data processing (counts / expression matrix)
• Differential expression analysis (basic stats: t-test, DE-style comparisons if data provided)
• Data normalization (basic scaling/log transformation)
• Exploratory analysis:
• PCA plots
• Heatmaps
• Volcano-style plots (if DE results exist)
• Group comparison (control vs disease, etc.)

Statistical Analysis includes:

• Mean, variance, fold-change
• Group comparisons (t-test / basic statistical tests)
• Correlation analysis
• Basic interpretation of results

Machine Learning :

• Basic classification models:
• Logistic Regression
• Random Forest
• Feature selection
• Model evaluation:
• Accuracy, confusion matrix
• ROC curve

All packages include reproducible code scripts (R/Python) so you can fully reproduce and validate the analysis

Custom Orders are also welcome based on specific datasets, analysis requirement and research goals