https://github.com/shuyib/from_cell_to_statistics
An introduction to Genomic Data Science/Bioinformatics.
https://github.com/shuyib/from_cell_to_statistics
bioinformatics biology cancer dna fasta fastq gwas molecular-biology protein rna
Last synced: 2 months ago
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An introduction to Genomic Data Science/Bioinformatics.
- Host: GitHub
- URL: https://github.com/shuyib/from_cell_to_statistics
- Owner: Shuyib
- License: cc0-1.0
- Created: 2023-10-22T13:18:57.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-05-16T15:53:58.000Z (over 1 year ago)
- Last Synced: 2025-03-22T09:43:38.894Z (7 months ago)
- Topics: bioinformatics, biology, cancer, dna, fasta, fastq, gwas, molecular-biology, protein, rna
- Language: Jupyter Notebook
- Homepage:
- Size: 16.6 MB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
[](https://github.com/Shuyib/from_cell_to_statistics/actions/workflows/devops.yml)
[](https://mybinder.org/v2/gh/Shuyib/from_cell_to_statistics/HEAD)
[](https://codespaces.new/Shuyib/from_cell_to_statistics)
This is a workshop about Genomic Data Science/Bioinformatics. We go from the basics of cell
and molecular biology to the analysis of high-throughput sequencing data. We use a couple of
examples to illustrate the concepts and tools used in the field. The workshop is divided in:
* Genomic Data science discipline & definition.
* Cell & Molecular biology basics.
* DNA (Deoxyribonucleic acid) where is it? how to isolate it? replicate it?
getting it's order.
* How DNA is stored in files FASTA(.fa) & FASTQ (.fastq) to enable use of computer
science skills & statistical skills.
* Apply programming to answer a common problem: GC content.
* Cancer definition predisposing factors, how to study variation DNA in a massive.
sample using short nucleotide polymorphisms(snp).
* Determining flanking regions of BRCA1.
Goals:
* Understand Genomic Data science and what it entails?
* Understand the principles of cell biology that is, cell. How it replicates, reproduces
and where the genetic material is.
* Get to know molecular techniques to study the cell (genetic material/genetic code)
Polymerase chain reaction(P.C.R) and Sequencing.
* Be able to use programming to determine GC content of any .fa file for any living
organism.
* Identify cancer predisposing factors and define cancer.
* Able to apply a workflow to find snp flanking regions for BRCA 1 gene.
* Develop an interest for bioinformatics.
Where to learn more:
* [Rosalind](https://rosalind.info/problems/locations/)
* [Coursera Specialization: Genomic Data Science](https://www.coursera.org/specializations/genomic-data-science)
* [Bioinformatics Specialization](https://www.coursera.org/specializations/genomic-data-science)
* East African Bioinformatics communities:
[Bioinformatics Hub of Kenya Initiative](bhki.org)
[EanBit](https://eanbit.icipe.org/)
[H3Africa](https://h3africa.org/)
# File structure
```
.
├── data
│ ├── 60731777.jpeg - Bhki logo
│ ├── Bioinformatics for everyone.pptx - full presentation
│ ├── chr-1.fasta - Chromosome 1 of human genome
│ ├── dna_20000.txt - DNA sequence of 20000 nucleotides
│ ├── ecoli.fasta - Ecoli genome
│ └── SRR835775_1.first1000.fastq - First 1000 reads of a fastq file
├── Dockerfile - Dockerfile to reproduce the environment
├── Makefile - Workflow to run the scripts
├── Practicing file manipulation for bioinformatics1.ipynb - Jupyter notebook
├── readfastq.py - Python script to read fastq files
├── README.md - This is file you are reading at the moment
├── Replicate this in other IDE-2.png - Image
├── Replicate this in other IDEs -1.png - Image
└── requirements.txt - Python packages to install
└── LICENSE - License file CC BY-NC-SA 4.0
```
# Setup virtual environment
```bash
python3 -m venv venv
source venv/bin/activate
pip install --no-cache-dir upgrade pip
pip install --no-cache-dir -r requirements.txt
```
Or
``` bash
make install
```
# Run the notebook
```bash
jupyter notebook
```
# View notebook
https://nbsanity.com/Shuyib/from_cell_to_statistics/blob/main/Practicing%20file%20manipulation%20for%20bioinformatics1.ipynb
# Run Docker container
```bash
sudo docker build -t bioenv .
sudo docker run -p 9090:9090 bioenv
```
Or
```bash
make docker_build docker_run
```