e-learning

CLIP-Seq data analysis from pre-processing to motif detection

Abstract

The eCLIP data provided here is a subset of the eCLIP data of RBFOX2 from a study published by Nostrand et al.. The dataset contains the first biological replicate of RBFOX2 CLIP-seq and the input control experiment (FASTQ files). The data was changed and downsampled to reduce data processing time, consequently the data does not correspond to the original source pulled from Nostrand et al.. Also included is a text file (.txt) encompassing the chromosome sizes of hg38 and a genome annotation (.gtf) file taken from Ensembl.

About This Material

This is a Hands-on Tutorial from the GTN which is usable either for individual self-study, or as a teaching material in a classroom.

Questions this will address

  • How is raw CLIP-Seq data processed and analysed?
  • How do I find binding motifs and targets for a protein (e.g., RBFOX2)?

Learning Objectives

  • Remove Adapters, Barcodes and Unique Molecular Identifiers (UMIs) from the reads
  • Align trimmed reads with STAR
  • De-duplicate the read library
  • Inspect the read mapping and de-duplication quality
  • Perform peak calling with PEAKachu
  • Analyse the peaks and find potential binding motifs and targets
  • Check the quality of the peak calling

Licence: Creative Commons Attribution 4.0 International

Keywords: Transcriptomics

Target audience: Students

Resource type: e-learning

Version: 23

Status: Active

Prerequisites:

  • Introduction to Galaxy Analyses
  • Mapping
  • Quality Control

Learning objectives:

  • Remove Adapters, Barcodes and Unique Molecular Identifiers (UMIs) from the reads
  • Align trimmed reads with STAR
  • De-duplicate the read library
  • Inspect the read mapping and de-duplication quality
  • Perform peak calling with PEAKachu
  • Analyse the peaks and find potential binding motifs and targets
  • Check the quality of the peak calling

Date modified: 2023-11-09

Date published: 2018-08-17

Authors: Bérénice Batut, Daniel Maticzka, Florian Heyl

Scientific topics: Transcriptomics


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