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TE Count Specifications

Process Details

  • Name: TE Count
  • Process UUID: nxg0y1xlve36uxkqcghyave103m9ed
  • Process Group: TE Transcripts

Overview

TE Count is a specialized quantification process designed for counting features with particular optimization for Transposable Elements (TEs). This process analyzes aligned RNA-seq data to quantify both gene expression and transposable element activity, providing comprehensive transcript abundance measurements that account for the unique challenges posed by repetitive genomic sequences.

This process is implemented in Bash, which invokes Python scripts for data processing and cleanup of TE count results.

Key Functionality

  • Transposable Element Quantification: Optimized counting algorithm specifically designed to handle the complex mapping patterns of transposable elements
  • Multi-mapper Handling: Distributes reads among multiple alignments to accurately quantify repetitive sequences
  • Gene Expression Counting: Simultaneous quantification of regular gene transcripts alongside transposable elements
  • Strand-aware Processing: Supports both stranded and unstranded library protocols for accurate quantification

Input/Output Specification

Inputs

Required Inputs

  • Sorted BAM Files

    • Description: Set of coordinate-sorted BAM files containing aligned RNA-seq reads
    • Format: BAM

  • BAM Index Files

    • Description: Index files corresponding to the sorted BAM files for efficient random access
    • Format: BAI

  • GTF Annotation File

    • Description: Gene annotation file containing transcript and gene feature definitions
    • Format: GTF

Outputs

  • Count Table
    • Description: Tab-separated file containing quantified read counts for genes and transposable elements
    • Format: TSV

Parameters & Settings

These parameters can be adjusted in the Foundry UI when running this process.

  • Library Stranded?

    • Description: no: library is unstranded; forward:'Second-strand' cDNA library (e.g. QIAseq stranded); reverse: 'First-strand' cDNA library (e.g. Illumina TruSeq stranded)
    • Available options: no (default), forward, reverse

  • Mode

    • Description: uniq: Unique mappers only; multi: Distribute among all alignments (default)
    • Available options: multi (default), uniq

  • Iterations

    • Description: Maximum number of iterations used to optimize multi-reads assignment (default: 100)
    • Default value: 100

References & Resources

  • Tool Documentation: Contact the team for details on clean_TE_count.py
  • Related Papers: Jin, Y., Tam, O.H., Paniagua, E. & Hammell, M. TEtranscripts: a package for including transposable elements in differential expression analysis of RNA-seq datasets. Bioinformatics 31, 3593-3599 (2015). DOI: 10.1093/bioinformatics/btv422