2. What is Notebook and How to use it

Drylab Notebook is a lightweight, stable, notebook-centric environment designed for interactive data exploration, visualization, and standard analyses. It prioritizes simplicity, fast startup, and reproducibility.

This environment is ideal for users who want a clean Jupyter workspace without the overhead of many specialized or experimental packages.

What is the Notebook?

Every analysis session has a persistent notebook — a .ipynb file saved to your workspace. It records every code cell, markdown cell, bash command, and script file generated during the session, making your work reproducible and shareable.

Your notebook location: /Your Project/note.ipynb

Core capabilities

Interactive analysis

• Python, R, and Bash notebooks via Jupyter

• Step-by-step data exploration

• Rapid iteration on analysis and figures

Statistical analysis

• Descriptive statistics and hypothesis testing

• Regression and classical machine learning

• Differential expression for bulk and single-cell data

Light transcriptomic workflows

• Basic RNA-seq and scRNA-seq analysis

• Clustering, dimensionality reduction, visualization

• Simple trajectory and pseudotime analysis

Reporting and visualization

• Publication-ready plots

• Tables and summary statistics

• Shareable notebooks and reports

Included tooling (high level)

Python

• Core scientific stack: NumPy, Pandas, SciPy, scikit-learn

• Visualization: Matplotlib, Seaborn, Plotly

• Transcriptomics: Scanpy, AnnData

• Genomics utilities: pysam, Biopython

• File formats: HDF5, Parquet, Excel

R

• Tidyverse-style data manipulation

• Seurat and SeuratObject

• Bioconductor core (DESeq2, edgeR, limma)

• Single-cell infrastructure (SingleCellExperiment, scater, scran)

• Basic trajectory and spatial support (slingshot, SpatialExperiment)

System & runtime

• Jupyter Server with Python, R, and Bash kernels

• Minimal bioinformatics CLIs (samtools, bedtools, bcftools)

• Optimized for stability and low overhead

Typical applications

• Exploratory data analysis

• Teaching and training

• Figure generation for manuscripts

• Pilot analyses before scaling up

• Users new to computational biology
  Cell Types

Key Notebook Actions

append — Add a new cell at a given index (default for new code)

edit — Modify a cell in-place (simple typo/parameter fixes only)

Ai edit — Modify a cell using AI

edit_and_move — Delete the buggy cell and re-append a fixed version at the end. Use this after debugging, so the notebook runs correctly top-to-bottom.

How to Open Notebook

Click to the Notebook tab on the right corner to open the notebook windows. Toggle between them using the Preview / Edit button at the top of the notebook panel.

Preview Mode

• Read-only view of the notebook

• Renders markdown cells as formatted text (headers, tables, bold, etc.)

• Shows all cell outputs (plots, tables, printed results) from the last run

• Use this to review your work, share results, or read documentation

• No accidental edits possible

Edit Mode

• Interactive mode where you can write and modify cells

• Markdown cells show raw syntax (e.g. ## Title, *bold**)

• Code cells are fully editable with syntax highlighting

• You can add, remove, reorder, or modify any cell

• Use this when actively working on analysis