module

biopipen.ns.gsea

</>

Gene set enrichment analysis

Classes
class

biopipen.ns.gsea.GSEA(*args, **kwds) → Proc

</>
Bases
biopipen.core.proc.Proc pipen.proc.Proc

Gene set enrichment analysis

Need devtools::install_github("GSEA-MSigDB/GSEA_R")

Attributes
  • cache — Should we detect whether the jobs are cached?
  • desc — The description of the process. Will use the summary fromthe docstring by default.
  • dirsig — When checking the signature for caching, whether should we walkthrough the content of the directory? This is sometimes time-consuming if the directory is big.
  • envs — The arguments that are job-independent, useful for common optionsacross jobs.
  • envs_depth — How deep to update the envs when subclassed.
  • error_strategy — How to deal with the errors
    • - retry, ignore, halt
    • - halt to halt the whole pipeline, no submitting new jobs
    • - terminate to just terminate the job itself
  • export — When True, the results will be exported to <pipeline.outdir>Defaults to None, meaning only end processes will export. You can set it to True/False to enable or disable exporting for processes
  • forks — How many jobs to run simultaneously?
  • input — The keys for the input channel
  • input_data — The input data (will be computed for dependent processes)
  • lang — The language for the script to run. Should be the path to theinterpreter if lang is not in $PATH.
  • name — The name of the process. Will use the class name by default.
  • nexts — Computed from requires to build the process relationships
  • num_retries — How many times to retry to jobs once error occurs
  • order — The execution order for this process. The bigger the numberis, the later the process will be executed. Default: 0. Note that the dependent processes will always be executed first. This doesn't work for start processes either, whose orders are determined by Pipen.set_starts()
  • output — The output keys for the output channel(the data will be computed)
  • output_data — The output data (to pass to the next processes)
  • plugin_opts — Options for process-level plugins
  • requires — The dependency processes
  • scheduler — The scheduler to run the jobs
  • scheduler_opts — The options for the scheduler
  • script — The script template for the process
  • submission_batch — How many jobs to be submited simultaneously
  • template — Define the template engine to use.This could be either a template engine or a dict with key engine indicating the template engine and the rest the arguments passed to the constructor of the pipen.template.Template object. The template engine could be either the name of the engine, currently jinja2 and liquidpy are supported, or a subclass of pipen.template.Template. You can subclass pipen.template.Template to use your own template engine.
Input
  • configfile — The configuration file in TOML format to specify some envs.clscol: If not provided, will use envs.clscol doc.string: Documentation string used as a prefix to name result files. If not provided, will use envs['doc.string']
  • gmtfile — The GMT file of reference gene sets
  • infile — The expression file.Either a tab-delimited matrix or an RDS file (on envs.infmt)
  • metafile — The meta data file, determining the class of the samplesTwo columns are required Sample: The unique sample id for each sample [Group]: The groups/classes of the samples
Output
  • outdir — The output directory
Envs
  • clscol — The column of the metafile determining the classes
  • doc_string — Documentation string used as a prefix to name result filesOther configs passed to GSEA() directly
  • inopts — The options for read.table() to read the input fileIf rds will use readRDS()
  • metaopts — The options for read.table() to read the meta file
Requires
  • GSEA-MSigDB/GSEA_R —
    • check: {{proc.lang}} <(echo "library(GSEA)")
Classes
Methods
  • __init_subclass__() — Do the requirements inferring since we need them to build up theprocess relationship </>
  • from_proc(proc, name, desc, envs, envs_depth, cache, export, error_strategy, num_retries, forks, input_data, order, plugin_opts, requires, scheduler, scheduler_opts, submission_batch) (Type) — Create a subclass of Proc using another Proc subclass or Proc itself</>
  • gc() — GC process for the process to save memory after it's done</>
  • init() — Init all other properties and jobs</>
  • log(level, msg, *args, logger) — Log message for the process</>
  • run() — Run the process</>
class

pipen.proc.ProcMeta(name, bases, namespace, **kwargs)

</>
Bases
abc.ABCMeta

Meta class for Proc

Methods
  • __call__(cls, *args, **kwds) (Proc) — Make sure Proc subclasses are singletons</>
  • __instancecheck__(cls, instance) — Override for isinstance(instance, cls).</>
  • __repr__(cls) (str) — Representation for the Proc subclasses</>
  • __subclasscheck__(cls, subclass) — Override for issubclass(subclass, cls).</>
  • register(cls, subclass) — Register a virtual subclass of an ABC.</>
staticmethod
register(cls, subclass)
</>

Register a virtual subclass of an ABC.

Returns the subclass, to allow usage as a class decorator.

staticmethod
__instancecheck__(cls, instance)
</>

Override for isinstance(instance, cls).

staticmethod
__subclasscheck__(cls, subclass)
</>

Override for issubclass(subclass, cls).

staticmethod
__repr__(cls) → str
</>

Representation for the Proc subclasses

staticmethod
__call__(cls, *args, **kwds)
</>

Make sure Proc subclasses are singletons

Parameters
  • *args (Any) — and
  • **kwds (Any) — Arguments for the constructor
Returns (Proc)

The Proc instance

classmethod

from_proc(proc, name=None, desc=None, envs=None, envs_depth=None, cache=None, export=None, error_strategy=None, num_retries=None, forks=None, input_data=None, order=None, plugin_opts=None, requires=None, scheduler=None, scheduler_opts=None, submission_batch=None)

</>

Create a subclass of Proc using another Proc subclass or Proc itself

Parameters
  • proc (Type) — The Proc subclass
  • name (str, optional) — The new name of the process
  • desc (str, optional) — The new description of the process
  • envs (Mapping, optional) — The arguments of the process, will overwrite parent oneThe items that are specified will be inherited
  • envs_depth (int, optional) — How deep to update the envs when subclassed.
  • cache (bool, optional) — Whether we should check the cache for the jobs
  • export (bool, optional) — When True, the results will be exported to<pipeline.outdir> Defaults to None, meaning only end processes will export. You can set it to True/False to enable or disable exporting for processes
  • error_strategy (str, optional) — How to deal with the errors
    • - retry, ignore, halt
    • - halt to halt the whole pipeline, no submitting new jobs
    • - terminate to just terminate the job itself
  • num_retries (int, optional) — How many times to retry to jobs once error occurs
  • forks (int, optional) — New forks for the new process
  • input_data (Any, optional) — The input data for the process. Only when this processis a start process
  • order (int, optional) — The order to execute the new process
  • plugin_opts (Mapping, optional) — The new plugin options, unspecified items will beinherited.
  • requires (Sequence, optional) — The required processes for the new process
  • scheduler (str, optional) — The new shedular to run the new process
  • scheduler_opts (Mapping, optional) — The new scheduler options, unspecified items willbe inherited.
  • submission_batch (int, optional) — How many jobs to be submited simultaneously
Returns (Type)

The new process class

classmethod

__init_subclass__()

</>

Do the requirements inferring since we need them to build up theprocess relationship

method

init()

</>

Init all other properties and jobs

method

gc()

</>

GC process for the process to save memory after it's done

method

log(level, msg, *args, logger=<LoggerAdapter pipen.core (WARNING)>)

</>

Log message for the process

Parameters
  • level (int | str) — The log level of the record
  • msg (str) — The message to log
  • *args — The arguments to format the message
  • logger (LoggerAdapter, optional) — The logging logger
method

run()

</>

Run the process

class

biopipen.ns.gsea.PreRank(*args, **kwds) → Proc

</>
Bases
biopipen.core.proc.Proc pipen.proc.Proc

PreRank the genes for GSEA analysis

Attributes
  • cache — Should we detect whether the jobs are cached?
  • desc — The description of the process. Will use the summary fromthe docstring by default.
  • dirsig — When checking the signature for caching, whether should we walkthrough the content of the directory? This is sometimes time-consuming if the directory is big.
  • envs — The arguments that are job-independent, useful for common optionsacross jobs.
  • envs_depth — How deep to update the envs when subclassed.
  • error_strategy — How to deal with the errors
    • - retry, ignore, halt
    • - halt to halt the whole pipeline, no submitting new jobs
    • - terminate to just terminate the job itself
  • export — When True, the results will be exported to <pipeline.outdir>Defaults to None, meaning only end processes will export. You can set it to True/False to enable or disable exporting for processes
  • forks — How many jobs to run simultaneously?
  • input — The keys for the input channel
  • input_data — The input data (will be computed for dependent processes)
  • lang — The language for the script to run. Should be the path to theinterpreter if lang is not in $PATH.
  • name — The name of the process. Will use the class name by default.
  • nexts — Computed from requires to build the process relationships
  • num_retries — How many times to retry to jobs once error occurs
  • order — The execution order for this process. The bigger the numberis, the later the process will be executed. Default: 0. Note that the dependent processes will always be executed first. This doesn't work for start processes either, whose orders are determined by Pipen.set_starts()
  • output — The output keys for the output channel(the data will be computed)
  • output_data — The output data (to pass to the next processes)
  • plugin_opts — Options for process-level plugins
  • requires — The dependency processes
  • scheduler — The scheduler to run the jobs
  • scheduler_opts — The options for the scheduler
  • script — The script template for the process
  • submission_batch — How many jobs to be submited simultaneously
  • template — Define the template engine to use.This could be either a template engine or a dict with key engine indicating the template engine and the rest the arguments passed to the constructor of the pipen.template.Template object. The template engine could be either the name of the engine, currently jinja2 and liquidpy are supported, or a subclass of pipen.template.Template. You can subclass pipen.template.Template to use your own template engine.
Input
  • configfile — The configuration file in TOML format to specify some envs.clscol: If not provided, will use envs.clscol classes: Defines pos and neg labels. If not provided, use will envs.classes.
  • infile — The expression file.Either a tab-delimited matrix or an RDS file (on envs.inopts)
  • metafile — The meta data file, determining the class of the samplesTwo columns are required Sample: The unique sample id for each sample [Group]: The groups/classes of the samples
Output
  • outfile — The rank file with 1st column the genes, and the rest theranks for different class pairs provided by envs.classes or in.configfile
Envs
  • classes — The classes to specify the pos and neg labels.It could be a pair of labels (e.g. ["CASE", "CNTRL"]), where the first one is pos and second is neg. Or you can have multiple pairs of labels (e.g. [["CASE1", "CNTRL"], ["CASE2", "CNTRL"]])
  • clscol — The column of metafile specifying the classes of the samples
  • inopts — Options for read.table() to read in.infile
  • metaopts — Options for read.table() to read in.metafile
  • method — The method to do the preranking.Supported: s2n(signal_to_noise), abs_s2n(abs_signal_to_noise), t_test, ratio_of_classes, diff_of_classes and log2_ratio_of_classes.
Classes
Methods
  • __init_subclass__() — Do the requirements inferring since we need them to build up theprocess relationship </>
  • from_proc(proc, name, desc, envs, envs_depth, cache, export, error_strategy, num_retries, forks, input_data, order, plugin_opts, requires, scheduler, scheduler_opts, submission_batch) (Type) — Create a subclass of Proc using another Proc subclass or Proc itself</>
  • gc() — GC process for the process to save memory after it's done</>
  • init() — Init all other properties and jobs</>
  • log(level, msg, *args, logger) — Log message for the process</>
  • run() — Run the process</>
class

pipen.proc.ProcMeta(name, bases, namespace, **kwargs)

</>
Bases
abc.ABCMeta

Meta class for Proc

Methods
  • __call__(cls, *args, **kwds) (Proc) — Make sure Proc subclasses are singletons</>
  • __instancecheck__(cls, instance) — Override for isinstance(instance, cls).</>
  • __repr__(cls) (str) — Representation for the Proc subclasses</>
  • __subclasscheck__(cls, subclass) — Override for issubclass(subclass, cls).</>
  • register(cls, subclass) — Register a virtual subclass of an ABC.</>
staticmethod
register(cls, subclass)
</>

Register a virtual subclass of an ABC.

Returns the subclass, to allow usage as a class decorator.

staticmethod
__instancecheck__(cls, instance)
</>

Override for isinstance(instance, cls).

staticmethod
__subclasscheck__(cls, subclass)
</>

Override for issubclass(subclass, cls).

staticmethod
__repr__(cls) → str
</>

Representation for the Proc subclasses

staticmethod
__call__(cls, *args, **kwds)
</>

Make sure Proc subclasses are singletons

Parameters
  • *args (Any) — and
  • **kwds (Any) — Arguments for the constructor
Returns (Proc)

The Proc instance

classmethod

from_proc(proc, name=None, desc=None, envs=None, envs_depth=None, cache=None, export=None, error_strategy=None, num_retries=None, forks=None, input_data=None, order=None, plugin_opts=None, requires=None, scheduler=None, scheduler_opts=None, submission_batch=None)

</>

Create a subclass of Proc using another Proc subclass or Proc itself

Parameters
  • proc (Type) — The Proc subclass
  • name (str, optional) — The new name of the process
  • desc (str, optional) — The new description of the process
  • envs (Mapping, optional) — The arguments of the process, will overwrite parent oneThe items that are specified will be inherited
  • envs_depth (int, optional) — How deep to update the envs when subclassed.
  • cache (bool, optional) — Whether we should check the cache for the jobs
  • export (bool, optional) — When True, the results will be exported to<pipeline.outdir> Defaults to None, meaning only end processes will export. You can set it to True/False to enable or disable exporting for processes
  • error_strategy (str, optional) — How to deal with the errors
    • - retry, ignore, halt
    • - halt to halt the whole pipeline, no submitting new jobs
    • - terminate to just terminate the job itself
  • num_retries (int, optional) — How many times to retry to jobs once error occurs
  • forks (int, optional) — New forks for the new process
  • input_data (Any, optional) — The input data for the process. Only when this processis a start process
  • order (int, optional) — The order to execute the new process
  • plugin_opts (Mapping, optional) — The new plugin options, unspecified items will beinherited.
  • requires (Sequence, optional) — The required processes for the new process
  • scheduler (str, optional) — The new shedular to run the new process
  • scheduler_opts (Mapping, optional) — The new scheduler options, unspecified items willbe inherited.
  • submission_batch (int, optional) — How many jobs to be submited simultaneously
Returns (Type)

The new process class

classmethod

__init_subclass__()

</>

Do the requirements inferring since we need them to build up theprocess relationship

method

init()

</>

Init all other properties and jobs

method

gc()

</>

GC process for the process to save memory after it's done

method

log(level, msg, *args, logger=<LoggerAdapter pipen.core (WARNING)>)

</>

Log message for the process

Parameters
  • level (int | str) — The log level of the record
  • msg (str) — The message to log
  • *args — The arguments to format the message
  • logger (LoggerAdapter, optional) — The logging logger
method

run()

</>

Run the process

class

biopipen.ns.gsea.FGSEA(*args, **kwds) → Proc

</>
Bases
biopipen.core.proc.Proc pipen.proc.Proc

Gene set enrichment analysis using fgsea

Attributes
  • cache — Should we detect whether the jobs are cached?
  • desc — The description of the process. Will use the summary fromthe docstring by default.
  • dirsig — When checking the signature for caching, whether should we walkthrough the content of the directory? This is sometimes time-consuming if the directory is big.
  • envs — The arguments that are job-independent, useful for common optionsacross jobs.
  • envs_depth — How deep to update the envs when subclassed.
  • error_strategy — How to deal with the errors
    • - retry, ignore, halt
    • - halt to halt the whole pipeline, no submitting new jobs
    • - terminate to just terminate the job itself
  • export — When True, the results will be exported to <pipeline.outdir>Defaults to None, meaning only end processes will export. You can set it to True/False to enable or disable exporting for processes
  • forks — How many jobs to run simultaneously?
  • input — The keys for the input channel
  • input_data — The input data (will be computed for dependent processes)
  • lang — The language for the script to run. Should be the path to theinterpreter if lang is not in $PATH.
  • name — The name of the process. Will use the class name by default.
  • nexts — Computed from requires to build the process relationships
  • num_retries — How many times to retry to jobs once error occurs
  • order — The execution order for this process. The bigger the numberis, the later the process will be executed. Default: 0. Note that the dependent processes will always be executed first. This doesn't work for start processes either, whose orders are determined by Pipen.set_starts()
  • output — The output keys for the output channel(the data will be computed)
  • output_data — The output data (to pass to the next processes)
  • plugin_opts — Options for process-level plugins
  • requires — The dependency processes
  • scheduler — The scheduler to run the jobs
  • scheduler_opts — The options for the scheduler
  • script — The script template for the process
  • submission_batch — How many jobs to be submited simultaneously
  • template — Define the template engine to use.This could be either a template engine or a dict with key engine indicating the template engine and the rest the arguments passed to the constructor of the pipen.template.Template object. The template engine could be either the name of the engine, currently jinja2 and liquidpy are supported, or a subclass of pipen.template.Template. You can subclass pipen.template.Template to use your own template engine.
Input
  • infile — The expression file (genes x samples).Either a tab-delimited file.
  • metafile — The meta data file, determining the class of the samplesTwo columns are required. If column Sample is found, it will be used as the samples; otherwise the first column should be the samples. The other column should be the group/class of the samples, whose name is specified by envs.clscol.
Output
  • outdir — The output directory containing the results, includingthe table and plots.
Envs
  • case — The case label for the positive class.
  • cases (type=json;order=99) — If you have multiple cases, you can specify them here.The keys are the names of the cases and the values are the above options except mutaters. If some options are not specified, the default values specified above will be used. If no cases are specified, the default case will be added with the name GSEA.
  • clscol — The column of metafile specifying the classes of the samplesWhen in.metafile is not specified, it can also be specified as a list of classes, in the same order as the samples in in.infile.
  • control — The control label for the negative class.When there are only two classes in in.metafile at column envs.clscol, either case or control can be specified and the other will be automatically set to the other class.
  • eps (type=float) — This parameter sets the boundary for calculating the p value.See https://rdrr.io/bioc/fgsea/man/fgseaMultilevel.html
  • gmtfile — The pathways in GMT format, with the gene names/ids in the same format as the seurat object.One could also use a URL to a GMT file. For example, from https://download.baderlab.org/EM_Genesets/current_release/Human/symbol/Pathways/.
  • maxsize (type=int) — Maximal size of a gene set to test. All pathways above the threshold are excluded.
  • method (choice) — The method to do the preranking.
    • - signal_to_noise: Signal to noise.
        The larger the differences of the means (scaled by the standard deviations);
        that is, the more distinct the gene expression is in each phenotype and the more the gene
        acts as a "class marker".
    • - s2n: Alias of signal_to_noise.
    • - abs_signal_to_noise: The absolute value of signal_to_noise.
    • - abs_s2n: Alias of abs_signal_to_noise.
    • - t_test: T test.
        Uses the difference of means scaled by the standard deviation and number of samples.
    • - ratio_of_classes: Also referred to as fold change.
        Uses the ratio of class means to calculate fold change for natural scale data.
    • - diff_of_classes: Difference of class means.
        Uses the difference of class means to calculate fold change for nature scale data
    • - log2_ratio_of_classes: Log2 ratio of class means.
        Uses the log2 ratio of class means to calculate fold change for natural scale data.
        This is the recommended statistic for calculating fold change for log scale data.
  • minsize (type=int) — Minimal size of a gene set to test. All pathways below the threshold are excluded.
  • ncores (type=int) — Number of cores for parallelizationPassed to nproc of fgseaMultilevel().
  • rest (type=json;order=98) — Rest arguments for fgsea()See also https://rdrr.io/bioc/fgsea/man/fgseaMultilevel.html
  • top (type=auto) — Do gsea table and enrich plot for top N pathways.If it is < 1, will apply it to padj, selecting pathways with padj < top.
Requires
  • bioconductor-fgsea —
    • check: {{proc.lang}} -e "library(fgsea)"
Classes
Methods
  • __init_subclass__() — Do the requirements inferring since we need them to build up theprocess relationship </>
  • from_proc(proc, name, desc, envs, envs_depth, cache, export, error_strategy, num_retries, forks, input_data, order, plugin_opts, requires, scheduler, scheduler_opts, submission_batch) (Type) — Create a subclass of Proc using another Proc subclass or Proc itself</>
  • gc() — GC process for the process to save memory after it's done</>
  • init() — Init all other properties and jobs</>
  • log(level, msg, *args, logger) — Log message for the process</>
  • run() — Run the process</>
class

pipen.proc.ProcMeta(name, bases, namespace, **kwargs)

</>
Bases
abc.ABCMeta

Meta class for Proc

Methods
  • __call__(cls, *args, **kwds) (Proc) — Make sure Proc subclasses are singletons</>
  • __instancecheck__(cls, instance) — Override for isinstance(instance, cls).</>
  • __repr__(cls) (str) — Representation for the Proc subclasses</>
  • __subclasscheck__(cls, subclass) — Override for issubclass(subclass, cls).</>
  • register(cls, subclass) — Register a virtual subclass of an ABC.</>
staticmethod
register(cls, subclass)
</>

Register a virtual subclass of an ABC.

Returns the subclass, to allow usage as a class decorator.

staticmethod
__instancecheck__(cls, instance)
</>

Override for isinstance(instance, cls).

staticmethod
__subclasscheck__(cls, subclass)
</>

Override for issubclass(subclass, cls).

staticmethod
__repr__(cls) → str
</>

Representation for the Proc subclasses

staticmethod
__call__(cls, *args, **kwds)
</>

Make sure Proc subclasses are singletons

Parameters
  • *args (Any) — and
  • **kwds (Any) — Arguments for the constructor
Returns (Proc)

The Proc instance

classmethod

from_proc(proc, name=None, desc=None, envs=None, envs_depth=None, cache=None, export=None, error_strategy=None, num_retries=None, forks=None, input_data=None, order=None, plugin_opts=None, requires=None, scheduler=None, scheduler_opts=None, submission_batch=None)

</>

Create a subclass of Proc using another Proc subclass or Proc itself

Parameters
  • proc (Type) — The Proc subclass
  • name (str, optional) — The new name of the process
  • desc (str, optional) — The new description of the process
  • envs (Mapping, optional) — The arguments of the process, will overwrite parent oneThe items that are specified will be inherited
  • envs_depth (int, optional) — How deep to update the envs when subclassed.
  • cache (bool, optional) — Whether we should check the cache for the jobs
  • export (bool, optional) — When True, the results will be exported to<pipeline.outdir> Defaults to None, meaning only end processes will export. You can set it to True/False to enable or disable exporting for processes
  • error_strategy (str, optional) — How to deal with the errors
    • - retry, ignore, halt
    • - halt to halt the whole pipeline, no submitting new jobs
    • - terminate to just terminate the job itself
  • num_retries (int, optional) — How many times to retry to jobs once error occurs
  • forks (int, optional) — New forks for the new process
  • input_data (Any, optional) — The input data for the process. Only when this processis a start process
  • order (int, optional) — The order to execute the new process
  • plugin_opts (Mapping, optional) — The new plugin options, unspecified items will beinherited.
  • requires (Sequence, optional) — The required processes for the new process
  • scheduler (str, optional) — The new shedular to run the new process
  • scheduler_opts (Mapping, optional) — The new scheduler options, unspecified items willbe inherited.
  • submission_batch (int, optional) — How many jobs to be submited simultaneously
Returns (Type)

The new process class

classmethod

__init_subclass__()

</>

Do the requirements inferring since we need them to build up theprocess relationship

method

init()

</>

Init all other properties and jobs

method

gc()

</>

GC process for the process to save memory after it's done

method

log(level, msg, *args, logger=<LoggerAdapter pipen.core (WARNING)>)

</>

Log message for the process

Parameters
  • level (int | str) — The log level of the record
  • msg (str) — The message to log
  • *args — The arguments to format the message
  • logger (LoggerAdapter, optional) — The logging logger
method

run()

</>

Run the process

class

biopipen.ns.gsea.Enrichr(*args, **kwds) → Proc

</>
Bases
biopipen.core.proc.Proc pipen.proc.Proc

Gene set enrichment analysis using Enrichr

Need devtools::install_github("wjawaid/enrichR")

Attributes
  • cache — Should we detect whether the jobs are cached?
  • desc — The description of the process. Will use the summary fromthe docstring by default.
  • dirsig — When checking the signature for caching, whether should we walkthrough the content of the directory? This is sometimes time-consuming if the directory is big.
  • envs — The arguments that are job-independent, useful for common optionsacross jobs.
  • envs_depth — How deep to update the envs when subclassed.
  • error_strategy — How to deal with the errors
    • - retry, ignore, halt
    • - halt to halt the whole pipeline, no submitting new jobs
    • - terminate to just terminate the job itself
  • export — When True, the results will be exported to <pipeline.outdir>Defaults to None, meaning only end processes will export. You can set it to True/False to enable or disable exporting for processes
  • forks — How many jobs to run simultaneously?
  • input — The keys for the input channel
  • input_data — The input data (will be computed for dependent processes)
  • lang — The language for the script to run. Should be the path to theinterpreter if lang is not in $PATH.
  • name — The name of the process. Will use the class name by default.
  • nexts — Computed from requires to build the process relationships
  • num_retries — How many times to retry to jobs once error occurs
  • order — The execution order for this process. The bigger the numberis, the later the process will be executed. Default: 0. Note that the dependent processes will always be executed first. This doesn't work for start processes either, whose orders are determined by Pipen.set_starts()
  • output — The output keys for the output channel(the data will be computed)
  • output_data — The output data (to pass to the next processes)
  • plugin_opts — Options for process-level plugins
  • requires — The dependency processes
  • scheduler — The scheduler to run the jobs
  • scheduler_opts — The options for the scheduler
  • script — The script template for the process
  • submission_batch — How many jobs to be submited simultaneously
  • template — Define the template engine to use.This could be either a template engine or a dict with key engine indicating the template engine and the rest the arguments passed to the constructor of the pipen.template.Template object. The template engine could be either the name of the engine, currently jinja2 and liquidpy are supported, or a subclass of pipen.template.Template. You can subclass pipen.template.Template to use your own template engine.
Input
  • infile — The gene list file.You can specify whether this file has header and the index (0-based) of the columns where the genes are present
Output
  • outdir — The output directory
Envs
  • dbs — The databases to enrich against.See https://maayanlab.cloud/Enrichr/#libraries for all available databases/libaries
  • genecol — Which column has the genes (0-based index or column name)
  • inopts — Options for read.table() to read in.infile
Classes
Methods
  • __init_subclass__() — Do the requirements inferring since we need them to build up theprocess relationship </>
  • from_proc(proc, name, desc, envs, envs_depth, cache, export, error_strategy, num_retries, forks, input_data, order, plugin_opts, requires, scheduler, scheduler_opts, submission_batch) (Type) — Create a subclass of Proc using another Proc subclass or Proc itself</>
  • gc() — GC process for the process to save memory after it's done</>
  • init() — Init all other properties and jobs</>
  • log(level, msg, *args, logger) — Log message for the process</>
  • run() — Run the process</>
class

pipen.proc.ProcMeta(name, bases, namespace, **kwargs)

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Bases
abc.ABCMeta

Meta class for Proc

Methods
  • __call__(cls, *args, **kwds) (Proc) — Make sure Proc subclasses are singletons</>
  • __instancecheck__(cls, instance) — Override for isinstance(instance, cls).</>
  • __repr__(cls) (str) — Representation for the Proc subclasses</>
  • __subclasscheck__(cls, subclass) — Override for issubclass(subclass, cls).</>
  • register(cls, subclass) — Register a virtual subclass of an ABC.</>
staticmethod
register(cls, subclass)
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Register a virtual subclass of an ABC.

Returns the subclass, to allow usage as a class decorator.

staticmethod
__instancecheck__(cls, instance)
</>

Override for isinstance(instance, cls).

staticmethod
__subclasscheck__(cls, subclass)
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Override for issubclass(subclass, cls).

staticmethod
__repr__(cls) → str
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Representation for the Proc subclasses

staticmethod
__call__(cls, *args, **kwds)
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Make sure Proc subclasses are singletons

Parameters
  • *args (Any) — and
  • **kwds (Any) — Arguments for the constructor
Returns (Proc)

The Proc instance

classmethod

from_proc(proc, name=None, desc=None, envs=None, envs_depth=None, cache=None, export=None, error_strategy=None, num_retries=None, forks=None, input_data=None, order=None, plugin_opts=None, requires=None, scheduler=None, scheduler_opts=None, submission_batch=None)

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Create a subclass of Proc using another Proc subclass or Proc itself

Parameters
  • proc (Type) — The Proc subclass
  • name (str, optional) — The new name of the process
  • desc (str, optional) — The new description of the process
  • envs (Mapping, optional) — The arguments of the process, will overwrite parent oneThe items that are specified will be inherited
  • envs_depth (int, optional) — How deep to update the envs when subclassed.
  • cache (bool, optional) — Whether we should check the cache for the jobs
  • export (bool, optional) — When True, the results will be exported to<pipeline.outdir> Defaults to None, meaning only end processes will export. You can set it to True/False to enable or disable exporting for processes
  • error_strategy (str, optional) — How to deal with the errors
    • - retry, ignore, halt
    • - halt to halt the whole pipeline, no submitting new jobs
    • - terminate to just terminate the job itself
  • num_retries (int, optional) — How many times to retry to jobs once error occurs
  • forks (int, optional) — New forks for the new process
  • input_data (Any, optional) — The input data for the process. Only when this processis a start process
  • order (int, optional) — The order to execute the new process
  • plugin_opts (Mapping, optional) — The new plugin options, unspecified items will beinherited.
  • requires (Sequence, optional) — The required processes for the new process
  • scheduler (str, optional) — The new shedular to run the new process
  • scheduler_opts (Mapping, optional) — The new scheduler options, unspecified items willbe inherited.
  • submission_batch (int, optional) — How many jobs to be submited simultaneously
Returns (Type)

The new process class

classmethod

__init_subclass__()

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Do the requirements inferring since we need them to build up theprocess relationship

method

init()

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Init all other properties and jobs

method

gc()

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GC process for the process to save memory after it's done

method

log(level, msg, *args, logger=<LoggerAdapter pipen.core (WARNING)>)

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Log message for the process

Parameters
  • level (int | str) — The log level of the record
  • msg (str) — The message to log
  • *args — The arguments to format the message
  • logger (LoggerAdapter, optional) — The logging logger
method

run()

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Run the process