single-cell-lectures

Lecture contents for single-cell analysis in Python

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1.Using human single-cell atlas data to gain biological insights – a Vanderbilt perspective

No coding exercise

2. Objects and scRNA-seq data structure

section01_scRNAseq_intro.ipynb

section02_AnnData_Basics.ipynb

3. Interpreting scRNA-seq data: high dimensional data analysis and visualization

section03_data_process_dim_reduction.ipynb

4. Use case: scRNA-seq data quality control

section04_DataQuality.ipynb

5. Scalable Methods for Annotating and Integrating scRNA-seq Datasets

Lecture5_Annotation_Integration.ipynb

6. Differential Gene Expression in scRNA-seq and Other Transcriptomic Methods

Lecture6_SpatialTranscriptomics_ImageManip.ipynb