Font size
  • A-
  • A
  • A+
Site color
  • R
  • A
  • A
  • A
eCampus
  • MAIN
  • eCAMPUS
    CLASS
  • FORUM
  • English ‎(en)‎ Español - Internacional ‎(es)‎
  • Acceder
Skip to main content

Tutorial RNASeq of comparative transcriptomics based on the species Sparus aurata

  1. Home
  2. Courses
  3. Tutorial RNASeq differential expression
  4. 2.2.1.4 - Postprocessing
◄2. STEP-BY-STEP MODE TUTORIAL3. PIPELINE MODE TUTORIAL►
  • CONTENTS
  • 1. PRELIMINARY INFORMATION
    • 1.1 - Tutorial objective
    • 1.2 - Tutorial material and case study
    • 1.3 - Experiment design and support
    • 1.4 - Installing and activating RNASeq and the Server-Side
  • 2. STEP-BY-STEP MODE TUTORIAL
    • 2.1. - TOPHAT/HISAT2 & CUFFLINKS
      • 2.1.1 - Preparing your experiment
      • 2.1.2 - Quality analysis and preprocessing
      • 2.1.3 - Mapping
      • 2.1.4 - Transcriptome Assembly
      • 2.1.5 - Differential Expression analysis
      • 2.1.6 - GOSeq
    • 2.2. - MAPPING & COUNTING PROTOCOL
      • 2.2.1 - Genome mapping
        • 2.2.1.1 - Preparing your experiment
        • 2.2.1.2 - Quality analysis and preprocessing
        • 2.2.1.3. - Mapping
        • 2.2.1.4 - Postprocessing
        • 2.2.1.5 - Differential Expression analysis
        • 2.2.1.6 - GOseq
      • 2.2.2 - Transcriptome mapping
        • 2.2.2.1 - Preparing your experiment
        • 2.2.2.2 - Quality analysis and preprocessing
        • 2.2.2.3 - Mapping
        • 2.2.2.4 - Postprocesing
        • 2.2.2.5 - Differential Expression
  • 3. PIPELINE MODE TUTORIAL
    • 3.1 - TopHat/Hisat2 & Cufflinks protocol
    • 3.2 - Mapping & Counting protocol
  • 4. BIBLIOGRAPHY
  • CITE US
  • 2.2.1.4 - Postprocessing


    The next step of this protocol is postprocessing, where the goal is to count how many reads are associated with each gene. This can be done using Corset (Davidson and Oshlack, 2014) or HTSeq (Anders et al., 2015). For this tutorial, we use HTSeq. To perform the counting of reads with HTSeq go to the Step-By-Step menu path Mapping & Counting → Postprocessing → htseq and do as indicated in Video 10.

    Video 10. Quantification of gene expression levels using HTSeq.

    Expected results from Postprocessing analysis

    When HTSeq is complete, you will obtain the following output files: 

    1. counts.txt: contains read counts per gene based on the provided genome annotation (GFF file).

    2. sorted.bam: for each sample, the original unsorted BAM file is processed to generate a version sorted by genomic position.

    These files are available in the following link HTSeq.

    Remember you can check if the job was successfully completed by accessing the job tracking panel of RNASeq.  

    To learn more about HTSeq, see https://pmc.ncbi.nlm.nih.gov/articles/PMC4287950/.

    ◄2.2.1.3 - Mapping2.2.1.5 - Differential Expression analysis►
    • Home
    • Calendar
    • Course sections
      • CONTENTS
      • 1. PRELIMINARY INFORMATION
      • 1.1 - Tutorial objective
      • 1.2 - Tutorial material and case study
      • 1.3 - Experiment design and support
      • 1.4 - Installing and activating RNASeq and the Server-Side
      • 2. STEP-BY-STEP MODE TUTORIAL
      • 2.1. - TOPHAT/HISAT2 & CUFFLINKS
      • 2.1.1 - Preparing your experiment
      • 2.1.2 - Quality analysis and preprocessing
      • 2.1.3 - Mapping
      • 2.1.4 - Transcriptome Assembly
      • 2.1.5 - Differential Expression analysis
      • 2.1.6 - GOSeq
      • 2.2. - MAPPING & COUNTING PROTOCOL
      • 2.2.1.1 - Prepare your experiment for the mapping & counting analysis
      • 2.2.1.2 - Quality analysis and preprocessing
      • 2.2.1.3 - Mapping
      • 2.2.1.4 - Postprocessing
      • 2.2.1.5 - Differential Expression analysis
      • 3. PIPELINE MODE TUTORIAL
      • 3.1 - TopHat/Hisat2 & Cufflinks protocol
      • 3.2 - Mapping & Counting protocol
      • 4. BIBLIOGRAPHY
      • Pipeline mode: Tophat & Cufflinks protocol results
      • Pipeline mode: Mapping & Counting protocol results
      • CITE US
      • CASE STUDY
      • 2.2.1 - Genome mapping
      • 2.2.1.6 - GOseq
      • 2.2.2 - Transcriptome mapping
      • 2.2.2.1 - Preparing your experiment
      • 2.2.2.2 - Quality analysis and preprocessing
      • 2.2.2.3 - Mapping
      • 2.2.2.4 - Postprocessing
      • 2.2.2.5 - Differential Expression analysis
    Accessibility settings
    About us
    Team
    Publications
    R&D
    Patents & trademarks
    Announcements
    Careers
    Journal Sequencing Partners

    Biotechvana


    Valencia Lab
    Parc Cientific Universitat de Valencia
    Carrer del Catedràtic Agustín Escardino, 9. 46980 Paterna (Valencia) Spain
    Madrid Lab
    Parque Científico de Madrid
    Campus de Cantoblanco
    Calle Faraday 7, 28049 Madrid Spain
    Contact us
    Phone: +34 960 06 74 93
    Email: biotechvana@biotechvana.com

    Esta plataforma forma parte de: IVACE PROJECT IMDIGB/2020/56


    Projectes de Digitalizació de PIME (DIGITALIZA-CV TELETREBALL)2020
    IVACE PROJECT IMDIGB/2020/56

    Biotechvana © 2021
    eCampus Privacy policy    eCampus Terms of use