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cg-fluffy

NIPT analysis pipeline

  • 3.2.0
  • PyPI
  • Socket score

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4

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FluFFyPipe

NIPT analysis pipeline, using WisecondorX for detecting aneuplodies and large CNVs, AMYCNE for FFY and PREFACE for FF prediction (optional). FluFFYPipe produces a variety of output files, as well as a per batch csv summary.

Run FluFFyPipe

Run NIPT analysis, using a previously comnputed reference:

fluffy --sample <samplesheet>  --project <input_folder> --out <output_folder> --analyse

Run NIPT analysis, using an internally computed reference (i.e the reference is built using all samples listed in samplesheet):

fluffy --sample <samplesheet>  --project <input_folder> --out <output_folder> --analyse --batch-ref

optionally, skip preface:

fluffy --sample <samplesheet>  --project <input_folder> --out <output_folder> --skip_preface --analyse

All output will be written to the output folder, this output includes:

bam files
wisecondorX output
tiddit coverage summary
Fetal fraction estimation

as well as a summary csv and multiqc html (per batch)

the input folder is a project folder containing one folder per sample, each of these subfolders contain the fastq file(s). The samplesheet contains at least a "sampleID" column, the sampleID should match the subfolders in the input folder. The samplesheet may contain other columns, such as flowcell and index folder: such columns will be printed to the summary csv. If the samplesheet contains a SampleName column, fluffy will name the output according to SampleName

Create a WisecondorX reference

fluffy --sample <samplesheet>  --project <input_folder> --out <output_folder> --reference

samplesheet should contain atleast a "sampleID" column. All samples in the samplesheet will be used to construct the reference, visit the WisecondorX manual for more information.

Optional fluffy parameters:

Analysis mode:
	--dry_run - run the pipeline without generating files
	-l	-	add paramters to the slurm header of the script, should be given on the following format parameter:value
			example: qos:high 

Reference mode:
	--dry_run - run the pipeline without generating files

Rerun mode:
	--dry_run - run the pipeline without generating files

Troubleshooting and rerun

There are three statuses of the fluffy pipeline: running, complete, and failed

The status of a fluffy run is found in the

<output_folder>/analysis_status.json

The status of all jobs are listed in

<output_folder>/sacct/fluffy_<date>.log.status

Where is the timepoint when the jobs were submitted Use grep to find the failed jobs:

grep -v COMPLETE <output_folder>/sacct/fluffy_<date>.log.status

The output logs are stored in:

 <output_folder>/logs

Before continuing, you may want to generate the summary csv for all completed cases:

bash <output_folder>/scripts/summarizebatch-<hash>

where is a randomly generated string.

use the rerun module to rerun failed fluffy analyses:

fluffy --sample <samplesheet>  --project <input_folder> --out <output_folder> --skip_preface rerun

Install FluFFyPipe

FluFFyPipe requires python 3, slurm, slurmpy, and singularity, python-coloredlogs.

fluffy may be installed using pip:

pip install fluffy-cg

alternatively, fluffy is cloned and installed from github: git clone https://github.com/Clinical-Genomics/fluffy cd fluffy pip install -e .

Next download the FluFFyPipe singularity container

 singularity pull library://jeisfeldt/default/fluffy:sha256.dbef92cd5eab8558c2729f73a191d73a7576a24e9bb44dde7372c0cd405c4ef6 

copy the example config (found in example_config), and edit the variables. You will need to download/create the following files:

Reference fasta (indexed using bwa)

WisecondorX reference files (created using the reference mode)

PREFACE model file (optional)

blacklist bed file (used by wisecondorX)

FluFFyPipe singularity collection (singularity pull --name FluFFyPipe.sif shub://J35P312/FluFFyPipe)

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