IntroductionSCENIC (Single-Cell rEgulatory Network Inference and Clustering) is a computational method used to construct transcription factor-target gene regulatory networks (GRNs) from single-cell RNA-seq data. Here is a simplified overview of the SCENIC workflow:  1) Co-expression analysis: Identify gene sets that are co-expressed with a given transcription factor (TF).2) Motif analysis: Use c..

Introduction `Single-cell analysis` initially focused on sequencing mRNA at single-cell resolution. Advances in technology now allow us to quantify intracellular and cell surface proteins, DNA methylation, and chromatin accessibility at the cellular level. However, single-cell metabolomics has stagnated. As mentioned in Part 2, quantifying metabolites is challenging due to their diversity, inclu..

In Part 1, we delved into the mathematical basis of FBA. In this article, we will explore the pipeline of the personalized multi-omics FBA model and apply it to real-world data. IntroductionLet's revise Part 1:FBA is a mathematical method used to simulate the metabolomic profiles of cells.Why simulate metabolic profiles instead of directly measuring them?Current metabolic profiling methods remai..

Before proceeding with the article, refer to this review paper on flux balance analysis (FBA). If you are a beginner in FBA, reading the review paper first should greatly aid you in grasping the basics. IntroductionFBA is a mathematical method used to simulate the metabolomic profiles of cells. In this article, we will delve into the mathematical basis of FBA. In Part 2, we will discuss how geno..

`GSEA` 포스팅은 총 3가지 파트로 이루어져 있습니다. 이번 파트에서는 이론적인 배경과 수식의 전개를 확인하며, `Part 2`에서는 스크래치부터의 구현, 그리고 마지막 `Part 3`에서는 실제 자료를 통해 pathway 분석을 진행해보겠습니다.Gene Set Enrichment Analysis`Gene Set Enrichment Analysis (GSEA)`는 `In Silico``pathway` 분석 기법으로, `microarray`나 `RNA-seq` 자료를 통해 특정 `gene set`이 관심있는 `표현형`과 얼마나 연관성이 있는지 확인하는 통계적 기법입니다. 여러 전통적인 기법과`PAEA`와 같은 새로운 방법의 검정법 등이 논문에 많이 그리고 새로이 등장하고 있습니다. 그 중 `GSEA`는..