Transposable Element (TE) Analysis¶

The Transposable Element module provides identification and quantification of TE transcripts using two complementary methods.

Overview¶

Transposable elements are highly repetitive, making them challenging to quantify. The 3t-seq pipeline addresses this with specialized alignment and quantification strategies.

Workflow¶

graph LR
    A[Trimmed FASTQ] --> B[Salmon-TE Evaluation]
    B --> C[Salmon-TE Quantification]
    A --> D[STAR Alignment]
    D --> E[starTE Quantification]
    E --> F[TE Analysis Results]

Methods¶

starTE Analysis¶

starTE uses STAR for alignment and a specialized counting algorithm for multi-mapping reads.

Random Match: Randomly assigns multi-mapping reads to a single locus.
Multi-mapping Allocation: Uses fractional counting to distribute multi-mapping reads equally across all valid alignment loci (each locus receives \(1/n\) of a count for a read mapping to \(n\) locations).

SalmonTE Analysis¶

SalmonTE is a fast and accurate quantification method for TE transcripts.

Uses quasi-mapping to quickly assign reads to a curated database of TE consensus sequences.
Highly efficient for large datasets.

Parameters & Defaults¶

starTE Random¶

Parameter	Default	Description
`outFilterMultimapNmax`	`5000`	Support for highly repetitive elements.
`winAnchorMultimapNmax`	`5000`	Max number of multimaps for a single window.

starTE Multihit¶

Parameter	Default	Description
`outFilterMultimapNmax`	`1`	Only uniquely mapped reads for fractional calculation.
`featureCounts --fraction`	`true`	Enables fractional counting logic.

Results¶

Location	Description
`results/alignments/starTE/`	STAR-TE quantification results and log files.
`results/salmonTE/`	SalmonTE quantification results.
`results/analysis/rdata/`	Normalized TE counts for downstream analysis.
`results/analysis/tables/`	Tabular summaries of TE expression.