• Installation

    Download links and installation instructions can be found here

  • A tour through HTSeq

    The Tour shows you how to get started. It explains how to install HTSeq, and then demonstrates typical analysis steps with explicit examples. Read this first, and then see the Reference for details.

  • Tutorial: Transcription start sites (TSS)

    This chapter explains typical usage patterns for HTSeq by explaining in detail three different solutions to the same programming task.

  • Counting reads

    This chapter explorer in detail the use case of counting the overlap of reads with annotation features and explains how to implement custom logic by writing on’s own customized counting scripts

  • Reference documentation

    The various classes of HTSeq are described here.

  • Scripts

    The following scripts can be used without any Python knowledge.

    • Quality Assessment with htseq-qa

      Given a FASTQ or SAM file, this script produces a PDF file with plots depicting the base calls and base-call qualities by position in the read. This is useful to assess the technical quality of a sequencing run.

    • htseq-count: counting reads within features

      Given one/multiple SAM/BAM/CRAM files with alignments and a GTF file with genomic features, this script counts how many reads map to each feature. This script is especially popular for bulk and single-cell RNA-Seq analysis.

    • htseq-count-barcodes: counting reads with cell barcodes and UMIs

      Similar to htseq-count, but for a single SAM/BAM/CRAM file containing reads with cell and molecular barcodes (e.g. 10X Genomics cellranger output). This script enables customization of single-cell RNA-Seq pipelines, e.g. to quantify exon-level expression or simply to obtain a count matrix that contains chromosome information additional feature metadata.

  • Appendices