# Bioconductor Doubletrouble

Doubletrouble aims to identify duplicated genes from whole-genome protein sequences and...

- Repository: https://github.com/bioMate-AI/biomate-bioconductor-kb (793 stars)
- Category: Engineering
- License: see repository
- Last updated: 2026-06-20
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add bioMate-AI/biomate-bioconductor-kb --skill bioconductor-doubletrouble -g -a claude-code -y`
Codex: `npx skills add bioMate-AI/biomate-bioconductor-kb --skill bioconductor-doubletrouble -g -a codex -y`
Cursor: `npx skills add bioMate-AI/biomate-bioconductor-kb --skill bioconductor-doubletrouble -g -a cursor -y`
Gemini CLI: `npx skills add bioMate-AI/biomate-bioconductor-kb --skill bioconductor-doubletrouble -g -a gemini-cli -y`

## Description

doubletrouble aims to identify duplicated genes from whole-genome protein sequences and classify them based on their modes of duplication. The duplication modes are i. segmental duplication (SD); ii. tandem duplication (TD); iii. proximal duplication (PD); iv. transposed duplication (TRD) and; v. dispersed duplication (DD). Transposon-derived duplicates (TRD) can be further subdivided into rTRD (retrotransposon-derived duplication) and dTRD (DNA transposon-derived duplication). If users want a s

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# doubletrouble

## Workflows

### Standard Workflow

```r
library(doubletrouble)
library(syntenet)

# Load example data
data(yeast_seq)
data(yeast_annot)
data(diamond_intra)

# Prepare input data
pdata <- process_input(yeast_seq, yeast_annot)

# Classify gene pairs using the standard scheme
c_standard <- classify_gene_pairs(
  annotation = pdata$annotation,
  blast_list = diamond_intra,
  scheme = "standard"
)

# Calculate duplicate frequencies
table(c_standard$Scerevisiae$type)
```
*Note*: Inputs are processed protein sequences and gene annotations along with intraspecies DIAMOND search results; output is a list of classified duplicated gene pairs.

## When to Use
- To identify and classify duplicated genes from whole-genome protein sequences using `classify_gene_pairs`.
- To classify duplicates into different schemes: binary (SD vs SSD), standard (SD, TD, PD, DD), or extended (SD, TD, PD, TRD, DD).

## When NOT to Use
- For finding synteny or running sequence similarity searches directly; use `syntenet` functions like `process_input` and `run_diamond` instead.
- When whole-genome protein sequences (proteome) and gene annotations (GFF3/GTF) are not available.

## Data Requirements
- **Proteome**: List of `AAStringSet` objects containing translated sequences of the primary transcripts.
- **Annotation**: List of `GRanges` objects containing genomic coordinates of all features.
- **Intraspecies BLAST/DIAMOND results**: A list of data frames with tabular output (e.g., from `run_diamond`).

## Key Parameters
- **annotation**: Processed annotation list (a `GRangesList` object).
- **blast_list**: A list of data frames with DIAMOND/BLAST tabular output for intraspecies comparisons.
- **scheme** ("standard"): Classification scheme to use ("binary", "standard", "extended", or "full").
- **blast_inter**: List of data frames with DIAMOND/BLAST tabular output for interspecies comparisons (required for "extended" and "full" schemes).

The rest: https://github.com/bioMate-AI/biomate-bioconductor-kb/blob/HEAD/skills/genomics/doubletrouble/SKILL.md