seismicrna.table package

Submodules

class seismicrna.table.base.AvgTable

Bases: RelTypeTable, ABC

Average over an ensemble of RNA structures.

classmethod header_type(): Type of the header for the table.

class seismicrna.table.base.ClustFreqTable

Bases: FreqTable, ABC

classmethod header_type(): Type of the header for the table.

classmethod index_depth(): Number of columns in the index.

classmethod kind(): Kind of table.

class seismicrna.table.base.ClustPosTable: Bases: ClustTable, ProfilePosTable, ABC

class seismicrna.table.base.ClustReadTable: Bases: ClustTable, ReadTable, ABC

class seismicrna.table.base.ClustTable

Bases: RelTypeTable, ABC

Cluster for each RNA structure in an ensemble.

classmethod header_type(): Type of the header for the table.

classmethod kind(): Kind of table.

class seismicrna.table.base.FreqTable

Bases: Table, ABC

Table of frequencies.

classmethod by_read(): Whether the table contains data for each read.

property data: Series: Table’s data.

classmethod path_segs(): Table’s path segments.

class seismicrna.table.base.MaskPosTable: Bases: MaskTable, ProfilePosTable, ABC

class seismicrna.table.base.MaskReadTable: Bases: MaskTable, ReadTable, ABC

class seismicrna.table.base.MaskTable

Bases: AvgTable, ABC

classmethod kind(): Kind of table.

class seismicrna.table.base.PosTable

Bases: RelTypeTable, ABC

Table indexed by position.

MASK = 'pos-mask'

classmethod by_read(): Whether the table contains data for each read.

ci_count(confidence: float, **kwargs)

Confidence intervals of counts, under these simplifications:

Counts are independent of each other.
Counts follow binomial distributions.
Coverage counts are constant.

Parameters:

confidence (float) – Confidence level; must be in [0, 1).
**kwargs – Keyword arguments for fetch methods.

Returns:

Lower and upper bounds of the confidence interval.

Return type:

tuple[pandas.DataFrame, pandas.DataFrame]

ci_ratio(confidence: float, **kwargs)

Confidence intervals of ratios, under these simplifications:

Ratios are independent of each other.
Ratios follow beta distributions.
Coverage counts are constant.

Parameters:

confidence (float) – Confidence level; must be in [0, 1).
**kwargs – Keyword arguments for fetch methods.

Returns:

Lower and upper bounds of the confidence interval.

Return type:

tuple[pandas.DataFrame, pandas.DataFrame]

property end3

property end5

classmethod index_depth(): Number of columns in the index.

iter_profiles(*, sections: Iterable[Section] | None = None, quantile: float = 0.0, rel: str = 'Mutated', order: int | None = None, clust: int | None = None): Yield RNA mutational profiles from the table.

classmethod path_segs(): Table’s path segments.

property range

property range_int

resample(fraction: float = 1.0, *, exclude_masked: bool = False, seed: int | None = None, max_seed: int = 4294967296)

Resample the reads and return a new DataFrame.

Parameters:

fraction (float = 1.) – Number of reads to resample, expressed as a fraction of the original number of reads. Must be ≥ 0; may be > 1.
exclude_masked (bool = False) – Exclude positions that have been masked.
seed (int | None = None) – Seed for the random number generator.
max_seed (int = 2 ** 32) – Maximum seed to pass to the next random number generator.

property section: Section covered by the table.

property seq

class seismicrna.table.base.ProfilePosTable: Bases: PosTable, ABC

class seismicrna.table.base.ReadTable

Bases: RelTypeTable, ABC

Table indexed by read.

classmethod by_read(): Whether the table contains data for each read.

classmethod index_depth(): Number of columns in the index.

classmethod path_segs(): Table’s path segments.

property reads

class seismicrna.table.base.RelPosTable: Bases: RelTable, PosTable, ABC

class seismicrna.table.base.RelReadTable: Bases: RelTable, ReadTable, ABC

class seismicrna.table.base.RelTable

Bases: AvgTable, ABC

classmethod kind(): Kind of table.

class seismicrna.table.base.RelTypeTable

Bases: Table, ABC

Table with multiple types of relationships.

property data: DataFrame: Table’s data.

fetch_count(*, exclude_masked: bool = False, squeeze: bool = False, **kwargs) → Series | DataFrame: Fetch counts of one or more columns.

fetch_ratio(*, exclude_masked: bool = False, squeeze: bool = False, precision: int | None = None, quantile: float = 0.0, **kwargs) → Series | DataFrame: Fetch ratios of one or more columns.

classmethod header_rows() → list[int]: Row(s) of the file to use as the columns.

class seismicrna.table.base.Table

Bases: ABC

Table base class.

abstract classmethod by_read() → bool: Whether the table contains data for each read.

property data: DataFrame | Series: Table’s data.

classmethod ext(): Table’s file extension: either ‘.csv’ or ‘.csv.gz’.

classmethod gzipped(): Whether the table’s file is compressed with gzip.

property header: Header for the table’s data.

classmethod header_depth()

abstract classmethod header_type() → type[Header]: Type of the header for the table.

classmethod index_cols() → list[int]: Column(s) of the file to use as the index.

abstract classmethod index_depth() → int: Number of columns in the index.

abstract classmethod kind() → str: Kind of table.

property path: Path of the table’s CSV file (possibly gzipped).

property path_fields: dict[str, Any]: Table’s path fields.

abstract classmethod path_segs() → tuple[Segment, ...]: Table’s path segments.

abstract property ref: str: Name of the table’s reference.

property refseq: DNA: Reference sequence.

abstract property sample: str: Name of the table’s sample.

abstract property sect: str: Name of the table’s section.

abstract property top: Path: Path of the table’s output directory.

seismicrna.table.base.get_rel_name(rel_code: str): Get the name of a relationship from its code.

class seismicrna.table.calc.AvgTabulator(dataset: MutsDataset | ClusterMutsDataset | UnbiasDataset)

Bases: Tabulator, ABC

property max_order: int: Number of clusters, or 0 if not clustered.

class seismicrna.table.calc.ClustTabulator(dataset: MutsDataset | ClusterMutsDataset | UnbiasDataset)

Bases: PartialTabulator, ABC

property clust_header: Header of the per-cluster data.

property max_order: Number of clusters, or 0 if not clustered.

property table_per_clust: Number of reads in each cluster.

class seismicrna.table.calc.FullTabulator(dataset: MutsDataset | ClusterMutsDataset | UnbiasDataset)

Bases: Tabulator, ABC

classmethod get_null_value(): The null value for a count: either 0 or NaN.

class seismicrna.table.calc.MaskTabulator(dataset: MutsDataset | ClusterMutsDataset | UnbiasDataset): Bases: PartialTabulator, AvgTabulator

class seismicrna.table.calc.PartialTabulator(dataset: MutsDataset | ClusterMutsDataset | UnbiasDataset)

Bases: Tabulator, ABC

classmethod get_null_value(): The null value for a count: either 0 or NaN.

property table_per_pos

class seismicrna.table.calc.RelateTabulator(dataset: MutsDataset | ClusterMutsDataset | UnbiasDataset): Bases: FullTabulator, AvgTabulator

class seismicrna.table.calc.Tabulator(dataset: MutsDataset | ClusterMutsDataset | UnbiasDataset)

Bases: ABC

Base class for tabulating data for multiple tables from a report loader.

abstract classmethod get_null_value() → int | float: The null value for a count: either 0 or NaN.

abstract property max_order: int: Number of clusters, or 0 if not clustered.

property p_ends_given_noclose: Probability of each end coordinate.

property pos_header: Header of the per-position data.

property read_header: Header of the per-read data.

property ref

property refseq

property sample

property section

property table_per_pos

property table_per_read

property top

seismicrna.table.calc.adjust_counts(table_per_pos: DataFrame, p_ends_given_noclose: ndarray, n_reads_clust: Series | int, section: Section, min_mut_gap: int, quick_unbias: bool, quick_unbias_thresh: float): Adjust the given table of masked/clustered counts per position to correct for observer bias.

seismicrna.table.calc.all_patterns(mask: RelPattern | None = None): Every RelPattern, keyed by its name.

seismicrna.table.calc.tabulate_loader(dataset: MutsDataset | ClusterMutsDataset | UnbiasDataset): Return a new Dataset, choosing the subclass based on the type of the argument dataset.

class seismicrna.table.load.ClustFreqTableLoader(table_file: Path)

Bases: TableLoader, ClustFreqTable

Load cluster data indexed by cluster.

property data: Series: Table’s data.

class seismicrna.table.load.ClustPosTableLoader(table_file: Path)

Bases: PosTableLoader, ClustPosTable

Load cluster data indexed by position.

class seismicrna.table.load.ClustReadTableLoader(table_file: Path)

Bases: ReadTableLoader, ClustReadTable

Load cluster data indexed by read.

class seismicrna.table.load.MaskPosTableLoader(table_file: Path)

Bases: PosTableLoader, MaskPosTable

Load masked bit vector data indexed by position.

class seismicrna.table.load.MaskReadTableLoader(table_file: Path)

Bases: ReadTableLoader, MaskReadTable

Load masked bit vector data indexed by read.

class seismicrna.table.load.PosTableLoader(table_file: Path)

Bases: RelTypeTableLoader, PosTable, ABC

Load data indexed by position.

class seismicrna.table.load.ReadTableLoader(table_file: Path)

Bases: RelTypeTableLoader, ReadTable, ABC

Load data indexed by read.

class seismicrna.table.load.RelPosTableLoader(table_file: Path)

Bases: PosTableLoader, RelPosTable

Load relation data indexed by position.

class seismicrna.table.load.RelReadTableLoader(table_file: Path)

Bases: ReadTableLoader, RelReadTable

Load relation data indexed by read.

class seismicrna.table.load.RelTypeTableLoader(table_file: Path)

Bases: TableLoader, RelTypeTable, ABC

Load a table of relationship types.

property data: DataFrame: Table’s data.

class seismicrna.table.load.TableLoader(table_file: Path)

Bases: Table, ABC

Load a table from a file.

property ref: str: Name of the table’s reference.

property sample: str: Name of the table’s sample.

property sect: str: Name of the table’s section.

property top: Path: Path of the table’s output directory.

seismicrna.table.load.find_all_tables(files: Iterable[str | Path])

seismicrna.table.load.find_pos_tables(files: Iterable[str | Path])

seismicrna.table.load.find_read_tables(files: Iterable[str | Path])

seismicrna.table.load.find_tables(segments: Iterable[Segment], files: Iterable[str | Path]): Yield every table file with the given type of segment from among the given paths.

seismicrna.table.load.load_all_tables(files: Iterable[str | Path]): Yield every table among the given paths.

seismicrna.table.load.load_any_table(table_file: Path)

seismicrna.table.load.load_pos_table(table_file: Path) → PosTableLoader

seismicrna.table.load.load_pos_tables(files: Iterable[str | Path]): Yield every positional table among the given paths.

seismicrna.table.load.load_read_table(table_file: Path) → ReadTableLoader

seismicrna.table.load.load_read_tables(files: Iterable[str | Path]): Yield every per-read table among the given paths.

seismicrna.table.load.load_table(types: Iterable[type[PosTableLoader | ReadTableLoader | ClustFreqTableLoader]], table_file: Path): Load a Table of one of several types from a file.

seismicrna.table.load.load_tables(finder: Callable[[Iterable[str | Path]], Iterable[Path]], loader: Callable[[Path], TableLoader], files: Iterable[str | Path]): Yield every table with the given type of segment from among the given paths.

seismicrna.table.main.run(input_path: tuple[str, ...], *, table_pos: bool = True, table_read: bool = True, table_clust: bool = True, force: bool = False, max_procs: int = 16, parallel: bool = True)

Count mutations for each read and position; output tables.

Parameters:

table_pos (bool) – Make a table counting relationships per position [keyword-only, default: True]
table_read (bool) – Make a table counting relationships per read [keyword-only, default: True]
table_clust (bool) – Make a table counting reads per cluster (only for clustered data) [keyword-only, default: True]
force (bool) – Force all tasks to run, overwriting any existing output files [keyword-only, default: False]
max_procs (int) – Run up to this many processes simultaneously [keyword-only, default: 16]
parallel (bool) – Run tasks in parallel or in series [keyword-only, default: True]

class seismicrna.table.write.ClustFreqTableWriter(tabulator: AvgTabulator | ClustTabulator)

Bases: TableWriter, ClustFreqTable

property data: Table’s data.

class seismicrna.table.write.ClustPosTableWriter(tabulator: AvgTabulator | ClustTabulator): Bases: PosTableWriter, ClustPosTable

class seismicrna.table.write.ClustReadTableWriter(tabulator: AvgTabulator | ClustTabulator): Bases: ReadTableWriter, ClustReadTable

class seismicrna.table.write.MaskPosTableWriter(tabulator: AvgTabulator | ClustTabulator): Bases: PosTableWriter, MaskPosTable

class seismicrna.table.write.MaskReadTableWriter(tabulator: AvgTabulator | ClustTabulator): Bases: ReadTableWriter, MaskReadTable

class seismicrna.table.write.PosTableWriter(tabulator: AvgTabulator | ClustTabulator)

Bases: TableWriter, PosTable, ABC

property data: Table’s data.

class seismicrna.table.write.ReadTableWriter(tabulator: AvgTabulator | ClustTabulator)

Bases: TableWriter, ReadTable, ABC

property data: Table’s data.

class seismicrna.table.write.RelPosTableWriter(tabulator: AvgTabulator | ClustTabulator): Bases: PosTableWriter, RelPosTable

class seismicrna.table.write.RelReadTableWriter(tabulator: AvgTabulator | ClustTabulator): Bases: ReadTableWriter, RelReadTable

class seismicrna.table.write.TableWriter(tabulator: AvgTabulator | ClustTabulator)

Bases: Table, ABC

Write a table to a file.

property columns

property ref: Name of the table’s reference.

property sample: Name of the table’s sample.

property sect: Name of the table’s section.

property top: Path of the table’s output directory.

write(force: bool): Write the table’s rounded data to the table’s CSV file.

seismicrna.table.write.get_tabulator_writer_types(tabulator: Tabulator)

seismicrna.table.write.get_tabulator_writers(tabulator: AvgTabulator | ClustTabulator, *, table_pos: bool = True, table_read: bool = True, table_clust: bool = True)

seismicrna.table.write.write(report_file: Path, *, force: bool, **kwargs): Helper function to write a table from a report file.