Tools for Data Science in Genomic Sequencing.
This repository includes projects using Python, R Language, Bioconductor, and Galaxy to understand, analyze, and interpret data from next-generation sequencing experiments.
The following projects are included:
1. Galaxy for Next Generation Sequencing
Set up a workflow to analyse DNA polymorphic sites of father-mother-child sequencing samples
2. Python for DNA Sequencing Analysis
This project includes a set of tools for DNA sequence analysis (
a. check records in file (count_records), b. compute the length of each DNA sequence (check_length), c. identify open read frame in each DNA sequence (orf_identifier), d. identify repeated motif in sequence (repeats_identifier) ).
3. Linux Command Line Tools for Data Science in Biology
This project apply bowtie2, samtools, bedtools and bcftools to:
- Analyze RNA-seq data to determine sets of genes that are expressed in the various tissues;
- cataloging genetic variation using SAMtools and BEDtools as well as other Unix commands;
- develop a pipeline for variant calling in a given genome; 4) perform the bioinformatics analysis to determine genes that are differentially expressed at different experimental conditions with Linux command line.
4. Sequencing Alignment and Genome Assembly
Python is used to implement key algorithms and data structures to analyze real genomes and DNA sequencing datasets.
5. R and Bioconductor
Use tools from the Bioconductor project and R programming language to analyze genomic data.
6. Statistics with R for Genomic Data
An introduction to the statistics for analysis of genomic data.