Saravanan666/pypi-org huggingface dataset:
Package: sequana-quality-control
This pipeline is not maintained anymore but should be functional. It is a short-read quality control pipeline
from theSequanaproject. We would recommend to use the fastqc, demultiplex,
and multitax pipelines instead.Overview:A quality control pipeline for illumina data set. This pipeline removes contaminants (e.g. Phix), performs fastqc, adapter cleaning and trimming and checks for contaminantsInput:Raw fastq filesOutput:Cleaned fastQ files, remove phix and adapters + taxonomyStatus:production.not maintained. Please use sequana_fastqc and sequana_multitax pipeline insteadCitation:Cokelaer et al, (2017), ‘Sequana’: a Set of Snakemake NGS pipelines, Journal of Open Source Software, 2(16), 352, JOSS DOI doi:10.21105/joss.00352InstallationYou must install Sequana first:pip install sequanaThen, just install this package:pip install sequana_quality_controlUsagesequana_quality_control --help
sequana_quality_control --input-directory DATAPATHThis creates a directory with the pipeline and configuration file. You will then need
to execute the pipeline:cd quality_control
sh quality_control.sh  # for a local runThis launch a snakemake pipeline. If you are familiar with snakemake, you can
retrieve the pipeline itself and its configuration files and then execute the pipeline yourself with specific parameters:snakemake -s quality_control.rules -c config.yaml --cores 4 --stats stats.txtOr usesequanixinterface.RequirementsThis pipelines requires the following executable(s):fastqcbwakraken2 (optional)krona (optional)sambambasamtoolspigzcutadapt [or atropos]DetailsThis pipeline runsquality_controlin parallel on the input fastq files (paired or not).
A brief sequana summary report is also produced.Rules and configuration detailsHere is thelatest documented configuration fileto be used with the pipeline. Each rule used in the pipeline may have a section in the configuration file.ChangeLogVersionDescription0.10.0add missing MANIFEST0.9.0remove design_file for cutadapt to reflect changes in
sequana 0.12.0update kraken rules to use a kraken2 versionUpdate to use new sequana framework (0.12)added CI action0.8.4fix the onsuccess section to reflect changes in sequana 0.9.30.8.3fix cleaning output files0.8.2fix typo in parameter (-skip-phix-removal –> –skip-phix-removal)implement hiearchical kraken analysis. Required major updates of
the sequana kraken rules + general fixes in sequana0.8.1uses more sequana tools to handle the options
Package: sequana-revcomp
This is is therevcomppipeline from theSequanaprojetOverview:revert and complement input Fast filesInput:A set of FastQ files (paired or single-end) compressed or notOutput:A set of reverse completed filesStatus:productionCitation:Cokelaer et al, (2017), ‘Sequana’: a Set of Snakemake NGS pipelines, Journal of Open Source Software, 2(16), 352, JOSS DOIhttps://doi:10.21105/joss.00352InstallationIf you already have all requirements, you can install the packages using pip:pip install sequana_revcomp --upgradeUsageThis command will scan all files ending in .fastq.gz found in the local
directory, create a directory called revcomp where a snakemake pipeline can be executed.:::sequana_revcomp –input-directory DATAPATHThis creates a directory with the pipeline and configuration file. You will then need
to execute the pipeline:cd revcomp
sh revcomp.sh  # for a local run
make cleanThis launch a snakemake pipeline. If you are familiar with snakemake, you can
retrieve the pipeline itself and its configuration files and then execute the pipeline yourself with specific parameters:snakemake -s revcomp.rules -c config.yaml --cores 4 \
    --wrapper-prefix https://raw.githubusercontent.com/sequana/sequana-wrappers/Or usesequanixinterface.RequirementsThis pipelines requires the following executable(s):seqtkDetailsThis pipeline runsseqtkin parallel on the input fastq files.Rules and configuration detailsHere is thelatest documented configuration fileto be used with the pipeline. Each rule used in the pipeline may have a section in the configuration file.ChangelogVersionDescription0.9.0set singularity container0.8.4implemented –from-project option0.8.3Uses new sequana framework to spee up –help calls–threads option0.8.2Fix schema and rule. output files are now saved in the ./rc directory0.8.1Improve the –help message0.8.0First version from sequana 0.8.0Contribute & Code of ConductTo contribute to this project, please take a look at theContributing Guidelinesfirst. Please note that this project is released with aCode of Conduct. By contributing to this project, you agree to abide by its terms.
Package: sequana-sphinxext
Python version:3.7.3, 3.8 ,3.9Status:ProductionIssues:Please fill issuesOn githubHow to cite:Citations are important for us to carry on developments.
For Sequana library (including the pipelines), please useCokelaer et al, (2017), ‘Sequana’: a Set of Snakemake NGS pipelines, Journal of
Open Source Software, 2(16), 352,JOSS DOI doi:10.21105/joss.00352The sequana_sphinxext  package is used exclusively to provide Sphinx extensions for the Sequana
project.Sequanaincludes a set of pipelines related to NGS (new generation sequencing) including quality control, variant calling, coverage, taxonomy, transcriptomics.Please see thedocumentationfor an up-to-date status.We have three sphinx extension to be added in your Sphinx configuration files in the extensions list:extensions += [
    "sequana_sphinxext.snakemakerule",
    "sequana_sphinxext.pipeline",
    "sequana_sphinxext.wrapper"]You can then include a wrapper fromsequana wrappersusing e.g.:.. sequana_wrapper:: fastqcor a rule from Sequana:.. snakemakerule:: fastq_samplingor a pipeline from sequana:.. sequana_pipeline:: demultiplex
Package: sequanix
Sequanix
########
Sequanix is a graphical user interface (GUI) that can be used to run Snakemake workflows... image::https://github.com/sequana/sequanix/actions/workflows/main.yml/badge.svg?branch=main:target:https://github.com/sequana/sequanix/actions/workflows/main.yml.. image::https://coveralls.io/repos/github/sequana/sequanix/badge.svg?branch=main:target:https://coveralls.io/github/sequana/sequanix?branch=main.. image::http://readthedocs.org/projects/sequana/badge/?version=main:target:https://sequana.readthedocs.io/en/main/sequanix.html:alt: Documentation Status.. image::http://joss.theoj.org/papers/10.21105/joss.00352/status.svg:target:http://joss.theoj.org/papers/10.21105/joss.00352:alt: JOSS (journal of open source software) DOI:Python version: 3.8, 3.9, 3.10
:Documentation:On readthedocs <http://sequana.readthedocs.org/>_
:Issues:On github <https://github.com/sequana/sequana/issues>_
:How to cite: Citations are important for us to carry on developments.For **Sequanix**: Dimitri Desvillechabrol, Rachel Legendre, Claire Rioualen,
Christiane Bouchier, Jacques van Helden, Sean Kennedy, Thomas Cokelaer.
Sequanix: A Dynamic Graphical Interface for Snakemake Workflows 
Bioinformatics, bty034, https://doi.org/10.1093/bioinformatics/bty034
Also available on bioRxiv (DOI: https://doi.org/10.1101/162701)Sequanixis a derivative of theSequanaproject that is dedicated to the analyse of NGS data (sequencing data). We provide a set of NGS pipelines  including quality control, variant calling, coverage, taxonomy, transcriptomics. Please see the Sequanadocumentation <http://sequana.readthedocs.org>_ for an up-to-date status and further information.NotesFix OpenGL for mac Big Sur:https://stackoverflow.com/a/64021312/11988671Installation
############Please see the installation notes and installation steps on thehttps://sequana.readthedocs.iolink.In brief::pip install sequanixFor developers, use::git clone git@github.com:sequana/sequanix.git
pip install -e .[testing]Design choice
#############Uses PySide6 from v0.2.0. See e.g.,https://www.pythonguis.com/faq/pyqt6-vs-pyside6/from information
on the switch to PySide6. In brief, the Qt project has recently adopted PySide as the official Qt for Python release which should ensure its viability going forward. When we migrate PyQt5 to PyQt6, we therefore decided to use PySide instead of PyQt.Changelog========= ==========================================================================
Version   Description
========= ==========================================================================
0.2.0     * add logo
          * remove pin on python3.7
          * switch from PyQt5 to PySide6
          * remove automatic creation of readtag in config. we let the pipelines
            handle it
0.1.0     * revamp Sequanix independently of Sequana
========= ==========================================================================
Package: sequdas-client
SeqUDAS: Sequence Upload and Data Archiving SystemOverviewModern DNA sequencing machines generate several gigabytes (GB) of data per run. Organizing and archiving this data presents a challenge for small labs. We present a Sequence Upload and Data Archiving System (SeqUDAS) that aims to ease the task of maintaining a sequence data repository through process automation and an intuitive web interface.FeaturesAutomated upload and storage of sequence data to a central storage server.Data validation with MD5 checksums for data integrity assuranceIllumina modulesare incorpated to parse metrics binaries and generate a report similar to Illumina SAV.FASTQC and MultiQC workflows are included to perform QC analysis automatically.A taxonomic report will be generated based on Kraken reportArchival information, QC results and taxonomic report can be viewed through a mobile-friendly web interfacePass sequence data along to another remote server via API (IRIDA)ArchitectureSeqUDAS consists of three components:Data manager: Installed on a PC directly attached to an illumina sequencing machine.Data analyzer: Installed on a server to run the data analysis jobs.Web Application: Installed on a web server to provide account management and report viewing.
Package: sequdas-qc
SeqUDAS Quality Control Analysis ComponentSetting up a Development EnvironmentA condaenvironment.ymlfile is provided in this repository. It can be used to set up a conda environment as follows:conda env create -f environment.ymlOnce the environment has been create, activate it:conda activate sequdas-qc...then install thesequdas_qccodebase into the environment in 'editable' modepip install --editable .You can verify thatsequdas-qcis available on the$PATHby invoking the help output as follows:sequdas-qc -h
Package: sequel
Opinionated imperative Everything as Code orchestrator.se·quel/ˈsēkwəl/Something that takes place after or as a result of an earlier event.“this encouragement to grow potatoes had a disastrous sequel some
fifty years later”ChangelogAll notable changes to this project will be documented in this file.The format is based onKeep a Changelog, and this project will adheres toSemantic Versioningfrom version 1.0 and after.[unreleased]Nothing yet.[0.4.2] - 2019-05-14FixedMore reliable teardownNoisy failure when something goes wrong[0.4.1] - 2019-05-07FixedChanges were not merged :([0.4] - 2019-05-07AddedAn API for Codex and friends!!10[0.3] - 2019-05-07AddedNow with rollbacks!!9A better usage example in the docs[0.2.2] - 2019-05-01Fixedgoogle-cloud-storagewas always imported.!8[0.2.1] - 2019-04-23FixedLedger reading on GCP would fail if file not found instead of returning
nothing.Outcomes were not saved in ledger.[0.2] - 2019-04-05Thestorytellerrelease!Milestone 0.2ChangedThe API was completely refactored.AddedState can now be saved and not run again:!7RemovedSpecifying graph name is now removed:!6FixedEpisodes with multiples outcomes would be run multiple times.[0.1] - 2019-04-01This is our first release!AddedCommand line interface that loads a python file for resolving jobs out
of callables.
Package: sequel-core
Sequel: A Continual Learning Library in PyTorch and JAXThe goal of this library is to provide a simple and easy to use framework for continual learning. The library is written in PyTorch and JAX and provides a simple interface to run experiments. The library is still in development and we are working on adding more algorithms and datasets.Documetation:https://nik-dim.github.io/sequel-site/Reproducibility Board:https://nik-dim.github.io/sequel-site/reproducibility/Weights&Biases:https://wandb.ai/nikdim/SequeLInstallationThe library can be installed via pip:pipinstallsequel-coreAlternatively, you can install the library from source:gitclonehttps://github.com/nik-dim/sequel.git
python3-mbuildor use the library by cloning the repository. In order to use the library, you need to install the dependencies. This can be done via therequirements.txtfile. We recommend to use a conda environment for this. The following commands will create a conda environment with the required packages and activate it:# create the conda environmentcondacreate-nsequel-ypython=3.10cudacudatoolkitcuda-nvcc-cnvidia-canaconda
condaactivatesequel# install all required packagespipinstall-rrequirements.txt# Optional: Depending on the machine, the next command might be needed to enable CUDA support for GPUspipinstalljax[cuda11_cudnn82]-fhttps://storage.googleapis.com/jax-releases/jax_cuda_releases.htmlRun an experimentFor some examples, you can modify theexample_pytorch.pyandexample_jax.pyfiles, or run:# example experiment on PyTorchpythonexample_pytorch.py# ...and in JAXpythonexample_jax.pyExperiments are located in theexamples/directory inconfigs. In order to run an experiment you simply do the following:pythonmain.py+experiment=EXPERIMENT_DIR/EXPERRIMENT# examplespythonmain.py+examples=ewc_rotatedmnistmode=pytorch# or mode=jaxpythonmain.py+examples=mcsgd_rotatedmnistmode=pytorch# or mode=jaxIn order to create your own experiment you follow the template of the experiments inconfigs/examples/. You override the defaults so that e.g. another algorithm is selected and you specify the training details. To run multiple experiments with different configs, the--multirunflag ofHydracan be used.
For instance:pythonmain.py--multirun+examples=ewc_rotatedmnist\mode=pytorchoptimizer.lr=0.01,0.001\benchmark.batch_size=128,256\training.epochs_per_task=1# online setting
Package: sequelize-to-excel
# Sequelize to ExcelWhy Should I Use This?This library is intended to extract column names , field names , table name and other information from your node model file developed in standard Sequelize formatThe excel will help you to have sneak peak of complete file at once , along with the corresponding database field nameThis can also be used as standalone app , as well as libraryInstallationpip install sequelize-to-excelUsing SequelizeToExcelImport the package and call the method from initalize objectfrom sequelize_to_excel import SequelizeToExcel
objSeq = SequelizeToExcel("<filename>")
objSeq.extract_and_export()you will find the generate excel file in the same folder .Make sure you provide the input file preferrably in the same folder.
Package: sequence
A Python module for looping over a sequence of commands with a focus on high configurability and extensibility.Latest VersionThe latest version of this project can be found at :http://github.com/thomst/sequence.InstallationOption 1 : Install via pippip install sequenceOption 2 : If you have downloaded the sourcepython setup.py installDocumentationHow to use?from sequence import Timer
from sequence import Sequence
from sequence import Cmd

interval = 8
timer = Timer(interval)

def f(x): print x
cmd1 = Cmd(f, args=['cmd1'], stall=3)   #stall the execution of cmd2 for 3 sec
cmd2 = Cmd(f, args=['cmd2'])            #just right now (depending on the order)
cmd3 = Cmd(f, args=['cmd3'], delay=4)   #soonest after 4 sec from loop-start
                                        #other options are available...

sequence = Sequence(timer, [cmd1, cmd2, cmd3])
sequence.go()Reporting BugsPlease report bugs at github issue tracker:https://github.com/thomst/sequence/issuesAuthorthomst <thomaslfuss@gmx.de>
Thomas Leichtfußhttp://github.com/thomst
Package: sequence2hash
sequence2hash - Convert sequence to hashThis tool converts a valid value in a sequence to a hash and contains a path to a valid value in the key fieldFeaturesConvert valid values in the sequence to hashesPaths showing valid values in the key fieldValid values not (), [], {}, None, ''RequirementsDoes not require any third party librariesInstallationpipinstallsequence2hashExamplesDefine the sequence variable:parameters={'queryKey':'','constraints':{'ids':[],'phids':(),'name':'Operating platform''members':('Bunoob',1944,'Google'),'watchers':[],'status':'','isMilestone':True,'icons':[],'colors':['blue','','red',''],'parents':[],'ancestors':[],},'attachments':{'subscribers':None},'order':'newest','before':'','after':'','limit':{}}Transfer:importsequence2hashforxinsequence2hash.flatten(parameters):print(x)Output:{'key':['constraints','name'],'value':'Operating platform'}{'key':['constraints','members','0'],'value':'Bunoob'}{'key':['constraints','members','1'],'value':1944}{'key':['constraints','members','2'],'value':'Google'}{'key':['constraints','isMilestone'],'value':True}{'key':['constraints','colors','0'],'value':'blue'}{'key':['constraints','colors','2'],'value':'red'}{'key':['order'],'value':'newest'}CreditsPython Cookbook 3rd Edition Documentation: Life is short and I use Python!
Package: sequence_aligner
# **Aligner**### What**Aligner** is a tool for [FASTA] (https://en.wikipedia.org/wiki/FASTA_format) DNA sequence alignment.### How to use**Aligner** is fairly simple to use.  All you need is a standard FASTA textfile (*.txt).By the way, included in this package are two example files (fasta_example_1.txt,fasta_example_2.txt).In order to install,```pip install sequence_aligner```To use aligner from the command line, you run the following commands:```aligner [-h] --file_path FILE_PATH [--storage_path STORAGE_PATH] [--results_nameRESULTS_NAME]```FILE PATH is the path to the fasta sequence text file.While FILE PATH is required, STORAGE_PATH and FILE_NAME are optional.By default, the result file will be stored in the following generated directory:`/tmp/sequence_results`And the file name will be generated with the following pattern:`sequence_read-<datetime here>.txt` for example: `sequence_read-2016-07-01T16.42.21.246183.txt`Once you run the command line, within seconds, your results will begenerated, and you'll receive a print out of the location and name of your file.For example:```Sequence Alignment results stored --> /tmp/sequence_results/sequence_read-2016-07-01T17.59.48.458859.txt```### How it worksIn order to align sequences, first, I created a dictionary of allsubsequences from the size 'greater than half' to full length.One sequence in the list of sequences was designated the "anchorsequence".I gathered that at any given state of the anchor sequence, therewould exist a sequence with the the greatest overlap.  Iteratingthrough the sequence list,  the sequence with thesub-sequence (from the dictionary mentioned above) having thegreatest 'score' is identified.  The score is based on the amount ofoverlap with the anchor sequence.  This subsequence is then mergedinto the anchor sequence.  This iteration continues until allsequences in the sequence list have been merged into the anchorsequence.## Caveats/Issues* One issue I dealt with was speed.  After many iterations ofrefactoring, I was able to bring runtime down from ~45-50 min to ~10-11min.* This program assumes that sequences overlap and that there are nomutations.## Next Steps* Improve efficiency* Improve 'match-iness' algorithm -- right now, my 'score' is merelybased on length of overlap at a given state of the anchor sequence.More preprocessing could be done before commencing alignment in orderto score the level of 'matchiness' between all pairs of sequences.
Package: sequence-alignment-by-cross-correlation
Sequence Alignmentby cross correlationThis is an implementation of the cross correlation algorithm for DNA/RNA alignmentExplore the docs »Report Bug·Request FeatureTable of ContentsAbout The ProjectBuilt WithGetting StartedPrerequisitesInstallationUsageRoadmapContributingLicenseContactAcknowledgmentsAbout The ProjectThe project is based on the paperSequence Alignment by Cross-Correlationand bridges the gap between the knowledge and an useful implementation. The underlying technique is the cross correlation algorithm, which can be tested in thisnotebook.Anothernotebookcan be seen here. The focus of this notebook is to illustrate how we can use the cross correlation for genomic data.The gene sequences were obtained using theNCBIdatabase.(back to top)Getting StartedThis is an example of how you may give instructions on setting up your project locally.
To get a local copy up and running follow these simple example steps.PrerequisitesThis is an example of how to list things you need to use the software and how to install them.python3:https://realpython.com/installing-python/InstallationClone the repogitclonehttps://github.com/kuhjuice/sequence_alignment_by_cross_correlation.gitNavigate into the repocdsequence_alignment_by_cross_correlationInstall requirements.txtpipinstall-rrequirements.txtorpip3install-rrequirements.txtAsk the CLI for help withpython3sequence_alignment_by_cross_correlation.py--help(back to top)UsageExample 1If we want to get an understanding of what the tool can do for us, we can use the help function of the CLI.python3sequence_alignment_by_cross_correlation/sequence_alignment_by_cross_correlation.py--helpExample 2If we want to find the gene omcB in the genome of Chlamydia Trachomatis we can use the sequence files insequencesToTestExecuting the following will search for the omcB Gene in the genome of Chlamydia Trachomatispython3sequence_alignment_by_cross_correlation/sequence_alignment_by_cross_correlation.py'sequencesToTest/C_T_genome.fasta''sequencesToTest/omcB_C_T_100fit.fna'(back to top)RoadmapFix BugsMake it a real packageEvalueate if useful for other projectsSee theopen issuesfor a full list of proposed features (and known issues).(back to top)ContributingContributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make aregreatly appreciated.If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".
Don't forget to give the project a star! Thanks again!Fork the ProjectCreate your Feature Branch (git checkout -b feature/AmazingFeature)Commit your Changes (git commit -m 'Add some AmazingFeature')Push to the Branch (git push origin feature/AmazingFeature)Open a Pull Request(back to top)LicenseDistributed under the MIT License. SeeLICENSE.txtfor more information.(back to top)ContactBo Kern -@blood_in_the_water@chaos.social-bo@blackscript.deProject Link:https://github.com/kuhjuice/sequence_alignment_by_cross_correlation(back to top)AcknowledgmentsTU-BerlinCarmen Regner(back to top)