APTARS - Analysis of Pacbio TARgeted Sequencing

APTARS is a snakemake pipeline that takes PacBio subreads as input, generates consensus reads using CCS, demultiplexes using lima, refines and cluster using isoseq3, map the reads to the genome using minimap2, assembles gene transcripts using cDNA_cupcake and annotates transcripts using Sqant3. Note that APTARS can also be used for un-targetted Pacbio data. Below is the dag of the pipeline:

Getting Started

Input

• PacBio subreads.bam

• Primers in fasta format

  Example format:

   >Clontech_5p
   AAGCAGTGGTATCAACGCAGAGTACATGGGG
   >C1_3_UT_3p
   CGCACTCTGATATGTGGTACTCTGCGTTGATACCACTGCTT
   >C1_1_UT_3p
   CTCACAGTCTGTGTGTGTACTCTGCGTTGATACCACTGCTT
   >C3_1_UT_3p
   CTCTCACGAGATGTGTGTACTCTGCGTTGATACCACTGCTT
   >C4_1_UT_3p
   CGCGCGTGTGTGCGTGGTACTCTGCGTTGATACCACTGCTT

  The primer ids must contain the information on whether they are 5 prime or 3 prime as "_5p" or "_3p" suffix respectively.

• Reference genome assembly in fasta format

• GTF: Gencode GTF; tested on v38 comprehensive CHR gene annotation

• Cage peaks: refTSS; tested on refTSS_v3.3_human_coordinate.hg38.bed

• Intropolis: tested on intropolis.v1.hg19_with_liftover_to_hg38.min_count_10.tsv

• Poly(a) atlas: tested on atlas.clusters.2.0.GRCh38.96.bed

• Poly(A) list: Human Poly(A) list included in the pipeline (/data) and is automatically used

Make sure the contig names in the annotation files and reference genome are the same.

Depedencies

• miniconda
• SQANTI3: v4.2 - https://github.com/ConesaLab/SQANTI3/archive/refs/tags/v4.2.tar.gz
• The rest of the dependencies (including snakemake) are installed via conda through the environment.yml file

SQANTI3 setup:

wget https://github.com/ConesaLab/SQANTI3/archive/refs/tags/v4.2.tar.gz
tar -xvf v4.2.tar.gz
echo "  - cdna_cupcake=22.0.0" >> SQANTI3-4.2/SQANTI3.conda_env.yml

Installation

Clone the directory:

git clone --recursive https://github.com/sid-sethi/APTARS.git

Create conda environment for the pipeline which will install all the dependencies:

cd APTARS
conda env create -f environment.yml

Usage

Edit config.yml to set up the working directory and input files/directories. snakemake command should be issued from within the pipeline directory. Please note that before you run any of the snakemake commands, make sure to first activate the conda environment using the command conda activate aptars.

cd APTARS
conda activate aptars
snakemake --use-conda -j <num_cores> all

It is a good idea to do a dry run (using -n parameter) to view what would be done by the pipeline before executing the pipeline.

snakemake --use-conda -n all

You can visualise the processes to be executed in a DAG:

snakemake --dag | dot -Tpng > dag.png

To exit a running snakemake pipeline, hit ctrl+c on the terminal. If the pipeline is running in the background, you can send a TERM signal which will stop the scheduling of new jobs and wait for all running jobs to be finished.

killall -TERM snakemake

To deactivate the conda environment:

conda deactivate

Output

working directory  
|--- config.yml           # a copy of the parameters used in the pipeline  
|--- Consensus_reads/  
     |-- # output of CCS  
|--- Demultiplxed/  
     |-- # output of lima  
|--- Refine/  
     |-- # output of isoseq3 refine  
|--- Cluster/  
     |-- # output of isoseq3 cluster  
|--- Mapping/  
     |-- # output of minimap2  
|--- Collapsed_isoforms/  
     |-- # output of cDNA_cupcake  
|--- Sqanti/  
     |-- # output of sqanti3