RNA-seq Tutorial (with Reference Genome)
This tutorial will serve as a guideline for how to go about analyzing RNA sequencing data when a reference genome is available. We will be going through quality control of the reads, alignment of the reads to the reference genome, conversion of the files to raw counts, analysis of the counts with DeSeq2, and finally annotation of the reads ...
CebolaLab/RNA-seq: Step-by-step analysis pipeline for RNA-seq data - GitHub
Many resources were used in building this RNA-seq tutorial. Highly recommended RNA-seq tutorial series: Introduction to differential gene expression analysis; Other RNA-seq tutorials: Statistical analysis of RNA-Seq data by Ignacio Gonz´alez. Analysis of RNA-Seq data: gene-level exploratory analysis and differential expression by Bernd Klaus ...
GitHub - griffithlab/rnaseq_tutorial: Informatics for RNA-seq: A …
Educational tutorials and working pipelines for RNA-seq analysis including an introduction to: cloud computing, critical file formats, reference genomes, gene annotation, expression, differential expression, alternative splicing, data visualization, and interpretation.
Reference-based RNA-Seq data analysis - Galaxy Training …
2016年10月5日 · In this tutorial, we have analyzed real RNA sequencing data to extract useful information, such as which genes are up or downregulated by depletion of the Pasilla gene, but also which GO terms or KEGG pathways they are involved in. To answer these questions, we analyzed RNA sequence datasets using a reference-based RNA-Seq data analysis approach.
RNA-seq workflow: gene-level exploratory analysis and differential ...
2019年10月16日 · Here we walk through an end-to-end gene-level RNA-seq differential expression workflow using Bioconductor packages. We will start from the FASTQ files, show how these were quantified to the reference transcripts, and prepare gene-level count datasets for downstream analysis.
2020年2月13日 · Why do RNA-seq? • RNAludes experiments to-seq inc – Profile abundance of mRNA and other RNAs – Identify "differentially expressed" genes – Identify alternated spliced transcript isoforms – Assemble transcriptome – Identify variants in transcribed regions of genome 3
A Beginner’s Guide to Analysis of RNA Sequencing Data
Our goals in the present review are to break down the steps of a typical RNA-seq analysis and to highlight the pitfalls and checkpoints along the way that are vital for bench scientists and biomedical researchers performing experiments that use RNA-seq.
scRNAseq_analysis_vignette/Tutorial.md at master - GitHub
The biggest advantage of single-cell as compared to bulk RNA-seq is the potential to look into cellular heterogeneity of samples, by looking for cell groups with distinct molecular signatures. However, not every gene has the same level of information and the same contribution when trying to identify different cell groups.
RNA-seq | Griffith Lab
RNA sequencing (RNA-seq) has rapidly become the assay of choice for robustly interrogating RNA transcript abundance and diversity. Similarly single cell RNA sequencing (scRNA-seq) has been widely adopted for experimental systems where it …
Analyzing RNA-seq data with DESeq2 - Bioconductor
2024年11月14日 · This package includes an array of tools for manipulating and aggregating data, as well as a wide range of customizable visualizations, and project management functionality that simplify RNA-Seq analysis and provide a variety of ways of exploring and analyzing data.