XAVIER

eXome Analysis and Variant explorER

This is the home of the XAVIER pipeline. Its long-term goals: to accurately call germline and somatic variants, to infer CNVs, and to boldly annotate variants like no pipeline before!

Overview

Welcome to XAVIER! Before getting started, we highly recommend reading through xavier's documentation.

The xavier pipeline is composed several inter-related sub commands to setup and run the pipeline across different systems. Each of the available sub commands perform different functions:

• xavier run: Run the XAVIER pipeline with your input files.
• xavier unlock: Unlocks a previous runs output directory.
• xavier cache: Cache remote resources locally, coming soon!

XAVIER is a comprehensive whole exome-sequencing pipeline following the Broad's set of best practices. It relies on technologies like Singularity¹ to maintain the highest-level of reproducibility. The pipeline consists of a series of data processing and quality-control steps orchestrated by Snakemake², a flexible and scalable workflow management system, to submit jobs to a cluster or cloud provider.

The pipeline is compatible with data generated from Illumina short-read sequencing technologies. As input, it accepts a set of FastQ or BAM files and can be run locally on a compute instance, on-premise using a cluster, or on the cloud (feature coming soon!). A user can define the method or mode of execution. The pipeline can submit jobs to a cluster using a job scheduler like SLURM, or run on AWS using Tibanna (feature coming soon!). A hybrid approach ensures the pipeline is accessible to all users.

Before getting started, we highly recommend reading through the usage section of each available sub command.

Dependencies

Requires: singularity>=3.5 snakemake==6.X

Snakemake and singularity must be installed on the target system. Snakemake orchestrates the execution of each step in the pipeline. To guarantee the highest level of reproducibility, each step relies on versioned images from DockerHub. Snakemake uses singaularity to pull these images onto the local filesystem prior to job execution, and as so, snakemake and singularity are the only two dependencies.

Run XAVIER pipeline

Biowulf

```bash

XAVIER is configured to use different execution backends: local or slurm

view the help page for more information

module load ccbrpipeliner xavier run --help

@slurm: uses slurm and singularity execution method

The slurm MODE will submit jobs to the cluster.

It is recommended running XAVIER in this mode.

Please note that you can dry-run the command below

by providing --runmode dryrun flag

Do not run this on the head node!

Grab an interactive node

sinteractive --mem=110g --cpus-per-task=12 --gres=lscratch:200 module load ccbrpipeliner

First, initialize the output directory

xavier run \ --input /data/R?.fastq.gz \ --output /data/$USER/xavier_hg38 \ --genome hg38 \ --pairs pairs.txt \ --mode slurm \ --runmode init

Second, do a dry run to visualize outputs

xavier run \ --input /data/R?.fastq.gz \ --output /data/$USER/xavier_hg38 \ --genome hg38 \ --pairs pairs.txt \ --mode slurm \ --runmode dryrun

Then do a complete run

xavier run \ --input /data/R?.fastq.gz \ --output /data/$USER/xavier_hg38 \ --genome hg38 \ --pairs pairs.txt \ --mode slurm \ --runmode run ```

FRCE

```bash

grab an interactive node

srun --export all --pty --x11 bash

add xavier to path correctly

. /mnt/projects/CCBR-Pipelines/pipelines/guis/latest/bin/setup

add SIF cache and TMPDIR path

SIFCACHE="/mnt/projects/CCBR-Pipelines/SIFs/XAVIER" TMPDIR="/scratch/cluster_scratch/$USER"

run xavier

Initialize and then dryrun (or run)

xavier run \ --input /data/R?.fastq.gz \ --output /data/$USER/xavier_hg38 \ --genome hg38 \ --sif-cache $SIFCACHE \ --tmp-dir $TMPDIR \ --pairs pairs.txt \ --mode slurm \ --runmode init # run

```

Help & Contributing

Come across a bug? Open an issue and include a minimal reproducible example.

Have a question? Ask it in discussions.

Want to contribute to this project? Check out the contributing guidelines.

General Inquiries and Collaboration: Please contact the CCBR Pipeliner team at CCBR_Pipeliner@mail.nih.gov.

References

<sup>1. Kurtzer GM, Sochat V, Bauer MW (2017). Singularity: Scientific containers for mobility of compute. PLoS ONE 12(5): e0177459.
2. Koster, J. and S. Rahmann (2018). "Snakemake-a scalable bioinformatics workflow engine." Bioinformatics 34(20): 3600.</sup>