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|
%global _empty_manifest_terminate_build 0
Name: python-cg-fluffy
Version: 3.2.0
Release: 1
Summary: NIPT analysis pipeline
License: MIT
URL: https://github.com/Clinical-Genomics/fluffy
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/4b/1d/29e5a919194598b9befab33f602c8711b330b02de20bd13b02b2551e623a/cg-fluffy-3.2.0.tar.gz
BuildArch: noarch
Requires: python3-click
Requires: python3-coloredlogs
Requires: python3-slurmpy
Requires: python3-pyyaml
Requires: python3-numpy
%description
[](https://codecov.io/gh/Clinical-Genomics/fluffy)
# 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.
<p align="center">
<img src="https://github.com/J35P312/FluFFyPipe/blob/master/logo/IMG_20200320_132001.jpg" width="400" height="400" >
</p>
# 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 <date> 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 <hash> 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)
%package -n python3-cg-fluffy
Summary: NIPT analysis pipeline
Provides: python-cg-fluffy
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-cg-fluffy
[](https://codecov.io/gh/Clinical-Genomics/fluffy)
# 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.
<p align="center">
<img src="https://github.com/J35P312/FluFFyPipe/blob/master/logo/IMG_20200320_132001.jpg" width="400" height="400" >
</p>
# 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 <date> 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 <hash> 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)
%package help
Summary: Development documents and examples for cg-fluffy
Provides: python3-cg-fluffy-doc
%description help
[](https://codecov.io/gh/Clinical-Genomics/fluffy)
# 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.
<p align="center">
<img src="https://github.com/J35P312/FluFFyPipe/blob/master/logo/IMG_20200320_132001.jpg" width="400" height="400" >
</p>
# 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 <date> 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 <hash> 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)
%prep
%autosetup -n cg-fluffy-3.2.0
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-cg-fluffy -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Wed May 31 2023 Python_Bot <Python_Bot@openeuler.org> - 3.2.0-1
- Package Spec generated
|
