Bioinformatics Analysis Table of Contents
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This is an article written based on my work experience working in the field of bioinformatics for five years.
Ⅰ. Background Theory
Ⅱ. Prerequisites
Introduction to Computer Science
Ⅲ. Data Acquisition and Processing
Understanding FASTQ, FASTA, GTF, GFF Files
RNA Sequencing Quality Control (QC)
HDF Files and filtered_feature_bc_matrix.h5
Ⅳ. Data Analysis
Bioinformatics RStudio Useful Functions Collection
Bioinformatics Python Useful Functions Collection
Collection of Python Functions for Organic Chemistry
Collection of Bioinformatics Linux Useful Functions
Collection of LLM Useful Functions
Obtaining DEGs in Bulk RNA-seq (DESeq2, t-test, ANOVA)
Cell Type Classification Pipeline
Determining Cell Types with Seurat
Determining Cell Types with scater
Determining Cell Types with scanpy
Comparison between Seurat and scanpy
Ligand-Receptor Interaction Analysis
Understanding and Running RCTD
Understanding and Running XFuse
Bioinformatics and Language Models
Ⅴ. Data Visualization
Ⅵ. Appendix
Ⅴ. Appendix
► Overview of Spatial Transcriptomics Analysis
► Cell–Cell Interaction Analysis in Spatial Transcriptomics
► Single-Cell Foundation Models
► Spatial Transcriptomics and Drug Discovery
Input : 2022.07.20 19:28
Modification : 2023.06.16 11:42