The bridge between the NCBI Gene Expression Omnibus and Bioconductor

Microarray Analysis Pipeline in Python

Subclassification of disease states based on the intersection of literature and expression

analyze_geo_microarrays.py : Differential expression analysis of published microarrays datasets from the NCBI Gene Expression Omnibus (GEO)

useful little tools & code snippets without a home; mostly genomics-oriented and one-liners

A small utility to quickly tag studies and samples from the NCBI Gene Expression Omnibus (GEO) with a curses interface.

Bioinformatic analysis of gene expression microarray profiles and DGEs on R and R studio

A list of publicly available Microarray Gene Expression datasets with proper attribution and associated toolkits.

Volcano Plot for Gene Expression Analysis

This repository contains a Jupyter Notebook for the analysis of Non-Small Cell Lung Cancer (NSCLC) data using various machine learning techniques.

Automatic NGS data analysis from SRA download to the quantification of RNAs.

Scripts using GEOquery package to fetch expression matrices and phenotypic data associated with GSE datasets

This repository contains scripts and detailed information for microarray-based transcriptomic analysis using NCBI GEO data for the course project.

This repository includes scripts, data, and documentation for analyzing Bulk RNA-seq data from NCBI GEO, supporting journal paper preparation in alignment with course requirements.

This repository contains scripts for VCF-GWAS file processing and microarray dataset differential expression analysis as per course requirements.

This folder contains R scripts for differential expression analysis and analyses of tissue-specific expression, inter-species conservation, and genetic variations of the CAPN10 gene in a bioinformatics project on PCOS and insulin resistance.

My solutions for the project of "An Intro to Bioinformatics" - Sharif University of Technology (SUT) - Prof. Somayyeh Koohi and Prof. Ali Sharifi-Zarchi - Fall 2021(1400-1).

This repository showcases bioinformatics analysis and visualization results from an independent project for a scientific writing course, utilizing iDEP and a microarray dataset derived from NCBI GEO.