module

biopipen.ns.cellranger

</>

Cellranger pipeline module for BioPipen

Classes
class

biopipen.ns.cellranger.CellRangerCount(*args, **kwds) → Proc

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

Run cellranger count

to count gene expression and/or feature barcode reads requires cellranger v7+.

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
  • fastqs — The input fastq filesEither a list of fastq files or a directory containing fastq files If a directory is provided, it should be passed as a list with one element.
  • id — The id defining output directory. If not provided, it is inferredfrom the fastq files.
Output
  • outdir — The output directory
Envs
  • — Other environment variables required by cellranger countSee cellranger count --help for more details or https://www.10xgenomics.com/support/software/cell-ranger/advanced/cr-command-line-arguments#count
  • cellranger — Path to cellranger
  • create_bam (flag) — Enable or disable BAM file generation.This is required by cellrange v8+. When using cellrange v8-, it will be transformed to --no-bam.
  • include_introns (flag) — Set to false to exclude intronic reads in count.
  • ncores — Number of cores to use
  • ref — Path of folder containing 10x-compatible transcriptome reference
  • tmpdir — Path to temporary directory, used to save the soft-lined fastq filesto pass to cellranger
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.cellranger.CellRangerVdj(*args, **kwds) → Proc

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

Run cellranger vdj

to perform sequence assembly and paired clonotype calling. requires cellranger v7+.

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
  • fastqs — The input fastq filesEither a list of fastq files or a directory containing fastq files If a directory is provided, it should be passed as a list with one element.
  • id — The id determining the output directory. If not provided, it is inferredfrom the fastq files.
Output
  • outdir — The output directory
Envs
  • — Other environment variables required by cellranger vdjSee cellranger vdj --help for more details or https://www.10xgenomics.com/support/software/cell-ranger/advanced/cr-command-line-arguments#vdj
  • cellranger — Path to cellranger
  • ncores — Number of cores to use
  • ref — Path of folder containing 10x-compatible transcriptome reference
  • tmpdir — Path to temporary directory, used to save the soft-lined fastq filesto pass to cellranger
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.cellranger.CellRangerSummary(*args, **kwds) → Proc

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

Summarize cellranger metrics

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
  • indirs — The directories containing cellranger resultsfrom CellRangerCount/CellRangerVdj.
Output
  • outdir — The output directory
Envs
  • group (type=auto) — The group of the samples for boxplots.If None, don't do boxplots. It can be a dict of group names and sample names, e.g. {"group1": ["sample1", "sample2"], "group2": ["sample3"]} or a file containing the group information, with the first column being the sample names and the second column being the group names. The file should be tab-delimited with no header.
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