Sqanti-sim is an open-source tool for creating realistic simulated long-read RNA-seq datasets for Oxford Nanopore and PacBio platforms. It lets users control the types of known and novel transcripts using SQANTI3 structural categories. The tool also produces a matching reduced GTF annotation and can generate related Illumina and CAGE data for testing transcriptome analysis workflows.

• Docs and examples

• Module Name: sqanti-sim (see the modules page for more information)
• Environment variables set
  • SQANTI-SIM_HOME

Allocate an interactive session and run the program.
Sample session (user input in bold):

[user@biowulf]$ sinteractive
salloc.exe: Pending job allocation 46116226
salloc.exe: job 46116226 queued and waiting for resources
salloc.exe: job 46116226 has been allocated resources
salloc.exe: Granted job allocation 46116226
salloc.exe: Waiting for resource configuration
salloc.exe: Nodes cn3144 are ready for job

[user@cn3144 ~]$ module load sqanti-sim
[+] Loading sqanti-sim  e4d5e58  on cn3144 
[+] Loading singularity  4.2.2  on cn3144

[user@cn3144 ~]$ cd /data/$USER

[user@cn3144 ~]$ git clone https://github.com/ConesaLab/SQANTI-SIM.git
[user@cn3144 ~]$ cd SQANTI-SIM
[user@cn3144 ~]$ cd example/human

[user@cn3144 ~]$ sqanti-sim.py classif --gtf example-detected_isoforms.gtf
Rscript (R) version 4.3.3 (2024-02-29)
                                                                      
      _____  ____            _   _ _______ _____      _____ _____ __  __ 
     / ____|/ __ \     /\   | \ | |__   __|_   _|    / ____|_   _|  \/  |
    | (___ | |  | |   /  \  |  \| |  | |    | |_____| (___   | | | \  / |
     \___ \| |  | |  / /\ \ | . ` |  | |    | |______\___ \  | | | |\/| |
     ____) | |__| | / ____ \| |\  |  | |   _| |_     ____) |_| |_| |  | |
    |_____/ \___\_\/_/    \_\_| \_|  |_|  |_____|   |_____/|_____|_|  |_|
                                                                          
            A SIMULATOR OF CONTROLLED NOVELTY AND DEGRADATION           
                 OF TRANSCRIPTS SEQUENCED BY LONG-READS                
    
[SQANTI-SIM] CLASSIF MODE

[SQANTI-SIM] Running with the following parameters:
[SQANTI-SIM] - Ref GTF: example_detected_isoforms.gtf
[SQANTI-SIM] - Out prefix: sqanti-sim
[SQANTI-SIM] - Out dir: .
[SQANTI-SIM] - N threads: 1

[SQANTI-SIM][29-04-2025 16:15:03] Classifying transcripts in structural categories
[SQANTI-SIM] Parsing transcripts from GTF reference annotation file
[SQANTI-SIM] Classifying transcripts according to its SQANTI3 structural category
chr22
100%|██████████████████████████████████████████████████████| 105/105 [00:01<00:00, 54.95it/s]
[SQANTI-SIM] Writting structural category file
[SQANTI-SIM] Summary table from categorization
_______________________________________________________________________________
S Q A N T I - S I M 📊

Classification summary Table 🔎
_______________________________________________________________________________
| full-splice_match: 35
| incomplete-splice_match: 15
| novel_in_catalog: 140
| novel_not_in_catalog: 113
| fusion: 7
| antisense: 43
| genic_intron: 0
| genic: 5
| intergenic: 74

[user@cn3144 ~]$ exit
salloc.exe: Relinquishing job allocation 46116226
[user@biowulf ~]$

Create a batch input file (e.g. sqanti-sim.sh). For example:

#!/bin/bash

cd /data/$USER

git clone https://github.com/ConesaLab/SQANTI-SIM.git
cd SQANTI-SIM
cd example/human

sqanti-sim.py classif --gtf example-detected_isoforms.gtf

Submit this job using the Slurm sbatch command.

sbatch [--cpus-per-task=#] [--mem=#] splam.sh

Create a swarmfile (e.g. sqanti-sim.swarm). For example:

sqanti-sim.py classif --gtf sample1.gtf -o sample1 -d output/sample1
sqanti-sim.py classif --gtf sample2.gtf -o sample2 -d output/sample2
sqanti-sim.py classif --gtf sample3.gtf -o sample3 -d output/sample3

Submit this job using the swarm command.

swarm [-g #] [-t #] --module sqanti-sim sqanti-sim.swarm