seismicrna package

Subpackages

Submodules

seismicrna.interface.dataset_from_report(report_path: str | Path, verify_times: bool = True) → MutsDataset

Load a dataset from a report file.

Parameters:

  • report_path (str | Path) – The path to a report json file from the relate, mask, or cluster steps.

  • verify_times (bool = True) – Ensure that the report file does not have a timestamp that is earlier than that of one of its constituents.

Returns:

The type of MutsDataset returned depends on the report file.

Return type:

RelateMutsDataset | MaskMutsDataset | ClusterMutsDataset

seismicrna.interface.table_from_dataset(dataset: MutsDataset, table: str = 'pos') → TableWriter

Tabulate a dataset to generate a TableWriter

Parameters:

  • dataset (RelateMutsDataset | MaskMutsDataset | ClusterMutsDataset) – A dataset from the Relate, Mask, or Cluster steps.

  • table (str = "pos") – The type of table to generate. Valid options include “pos” for per-position table, “read” for per-read table, and “abundance” for a cluster abundance table.

Returns:

The type of TableWriter returned depends on the Dataset type.

Return type:

TableWriter

seismicrna.interface.table_from_report(report_path: str | Path, verify_times: bool = True, table: str = 'pos')

Load a dataset from a report file and tabulate it.

Parameters:

  • report_path (str | Path) – Path to a report JSON file from the relate, mask, or cluster step.

  • verify_times (bool) – If True, ensure the report file does not have a timestamp earlier than any of its constituent files.

  • table (str) – Type of table to generate: “pos” for per-position, “read” for per-read, or “abundance” for cluster abundance.

Returns:

The type of TableWriter returned depends on the report file.

Return type:

TableWriter

seismicrna.join.join_regions(out_dir: Path, joined_region: str, sample: str, branches_flat: Iterable[str], ref: str, regs: Iterable[str], clustered: bool, *, clusts: dict[str, dict[int, dict[int, int]]], mask_pos_table: bool, mask_read_table: bool, cluster_pos_table: bool, cluster_abundance_table: bool, verify_times: bool, num_cpus: int, force: bool, tmp_pfx, keep_tmp)

Join one or more regions (horizontally).

Parameters:

  • out_dir (pathlib.Path) – Output directory.

  • joined_region (str) – Name of the joined region.

  • branches_flat (Iterable[str]) – Branches of the datasets being pooled.

  • sample (str) – Name of the sample.

  • ref (str) – Name of the reference.

  • regs (Iterable[str]) – Names of the regions being joined.

  • clustered (bool) – Whether the dataset is clustered.

  • tmp_dir (Path) – Temporary directory.

  • clusts (dict[str, dict[int, dict[int, int]]]) – For each region, for each number of clusters, the cluster from the original region to use as the cluster in the joined region (ignored if clustered is False).

  • mask_pos_table (bool) – Tabulate relationships per position for mask data.

  • mask_read_table (bool) – Tabulate relationships per read for mask data

  • cluster_pos_table (bool) – Tabulate relationships per position for cluster data.

  • cluster_abundance_table (bool) – Tabulate number of reads per cluster for cluster data.

  • verify_times (bool) – Verify that report files from later steps have later timestamps.

  • num_cpus (bool) – Number of processors to use.

  • force (bool) – Force the report to be written, even if it exists.

Returns:

Path of the Join report file.

Return type:

pathlib.Path

seismicrna.join.joined_mask_report_exists(top: Path, sample: str, branches_flat: Iterable[str], ref: str, joined_region: str, regs: Iterable[str])

Return whether a mask report for the joined region exists.

seismicrna.join.parse_join_clusts_file(file: str | Path)

Parse a file of joined clusters.

seismicrna.join.run(joined_region: str = Sentinel.UNSET, input_path: Iterable[str | Path] = Sentinel.UNSET, *, join_clusts: str | None = None, mask_pos_table: bool = True, mask_read_table: bool = True, cluster_pos_table: bool = True, cluster_abundance_table: bool = True, verify_times: bool = True, tmp_pfx: str | Path = './tmp', keep_tmp: bool = False, num_cpus: int = 4, force: bool = False) → list[Path]

Merge regions (horizontally) from the Mask or Cluster step.

Parameters:

  • join_clusts (str | None) – Specify which clusters to join clusters using this CSV file [keyword-only, default: None]

  • mask_pos_table (bool) – Tabulate relationships per position for mask data [keyword-only, default: True]

  • mask_read_table (bool) – Tabulate relationships per read for mask data [keyword-only, default: True]

  • cluster_pos_table (bool) – Tabulate relationships per position for cluster data [keyword-only, default: True]

  • cluster_abundance_table (bool) – Tabulate number of reads per cluster for cluster data [keyword-only, default: True]

  • verify_times (bool) – Verify that report files from later steps have later timestamps [keyword-only, default: True]

  • tmp_pfx (str | pathlib._local.Path) – Write all temporary files to a directory with this prefix [keyword-only, default: ‘./tmp’]

  • keep_tmp (bool) – Keep temporary files after finishing [keyword-only, default: False]

  • num_cpus (int) – Use up to this many CPUs simultaneously [keyword-only, default: 4]

  • force (bool) – Force all tasks to run, overwriting any existing output files [keyword-only, default: False]

seismicrna.join.write_report(report_type: type[JoinReport], out_dir: Path, **kwargs)

Instantiate and save a JoinReport.

Parameters:

  • report_type (type[JoinReport]) – The concrete JoinReport subclass to instantiate.

  • out_dir (Path) – Directory in which to save the report file.

seismicrna.lists.find_pos(table: PositionTable, max_fmut_pos: float, complement: bool)

Find positions that pass a mutation-rate filter.

Parameters:

  • table (PositionTable) – Per-position table from which mutation rates are fetched.

  • max_fmut_pos (float) – Maximum allowed mutation frequency; positions above this threshold are masked (or kept if complement is True).

  • complement (bool) – If True, invert the filter so that positions above the threshold are kept instead of masked.

seismicrna.lists.iter_tables(input_path: Iterable[str | Path], **kwargs)

Iterate through all types of List and all Tables from which each type of List can be created.

seismicrna.lists.run(input_path: Iterable[str | Path] = Sentinel.UNSET, *, branch: str = '', min_ninfo_pos: int = 1000, max_fmut_pos: float = 1.0, force: bool = False, num_cpus: int = 4) → list[Path]

List positions to mask.

Parameters:

  • branch (str) – Create a new branch of the workflow with this name [keyword-only, default: ‘’]

  • min_ninfo_pos (int) – Mask positions with fewer than this many informative base calls [keyword-only, default: 1000]

  • max_fmut_pos (float) – Mask positions with more than this fraction of mutated base calls [keyword-only, default: 1.0]

  • force (bool) – Force all tasks to run, overwriting any existing output files [keyword-only, default: False]

  • num_cpus (int) – Use up to this many CPUs simultaneously [keyword-only, default: 4]

seismicrna.lists.write_list(table: PositionTableLoader, list_type: type[List], *, branch: str, min_ninfo_pos: int, max_fmut_pos: float, force: bool)

Write a List based on a Table.

Draw the SEISMIC-RNA logo as an SVG.

Parameters:

  • report (bool) – If True, render the variant of the logo used in reports (different background triangle color).

  • out_svg (str | Path | None) – Path to write the SVG file; if None the SVG is returned as a string instead of being written to disk.

  • dpi (int) – Resolution in dots per inch used when saving the figure.

exception seismicrna.migrate.FindAndReplaceError

Bases: ValueError

seismicrna.migrate.find_and_replace(file: Path, find: str, replace: str, count: int = 1)

Replace occurrences of a string in a plain-text or gzipped file.

Parameters:

  • file (Path) – Path to the file to modify in place.

  • find (str) – Substring to search for.

  • replace (str) – Replacement string.

  • count (int) – Expected number of occurrences of find; if the actual count differs a FindAndReplaceError is raised. Pass -1 to skip the check.

seismicrna.migrate.migrate_align_dir(align_dir: Path)
seismicrna.migrate.migrate_cluster_ref_dir(ref_dir: Path, num_cpus: int)
seismicrna.migrate.migrate_cluster_reg_dir(reg_dir: Path)
seismicrna.migrate.migrate_fold_ref_dir(ref_dir: Path, num_cpus: int)
seismicrna.migrate.migrate_fold_reg_dir(reg_dir: Path)
seismicrna.migrate.migrate_mask_ref_dir(ref_dir: Path, num_cpus: int)
seismicrna.migrate.migrate_mask_reg_dir(reg_dir: Path)
seismicrna.migrate.migrate_out_dir(out_dir: Path, num_cpus: int)
seismicrna.migrate.migrate_relate_ref_dir(ref_dir: Path)
seismicrna.migrate.migrate_sample_dir(sample_dir: Path, num_cpus: int)
seismicrna.migrate.run(input_path: Iterable[str | Path] = Sentinel.UNSET, *, out_dir: str | Path = './out', num_cpus: int = 4)

Migrate output directories from v0.23 to v0.24

Parameters:

  • out_dir (str | pathlib._local.Path) – Write all output files to this directory [keyword-only, default: ‘./out’]

  • num_cpus (int) – Use up to this many CPUs simultaneously [keyword-only, default: 4]

seismicrna.migrate.update_brickle(file: str | Path, md5_checksum: str)
seismicrna.migrate.update_brickles(report: Report, top: str | Path)
seismicrna.pool.pool_samples(out_dir: Path, pooled_sample: str, branches_flat: Iterable[str], ref: str, samples: Iterable[str], *, min_pearson: float, max_marcd: float, relate_pos_table: bool, relate_read_table: bool, verify_times: bool, num_cpus: int, force: bool, tmp_pfx, keep_tmp)

Pool one or more samples (vertically).

Parameters:

  • out_dir (pathlib.Path) – Output directory.

  • pooled_sample (str) – Name of the pooled sample.

  • branches_flat (Iterable[str]) – Branches of the datasets being pooled.

  • ref (str) – Name of the reference

  • samples (Iterable[str]) – Names of the samples in the pool.

  • tmp_dir (Path) – Temporary directory.

  • min_pearson (float) – Skip pooling if any pair of samples has Pearson r below this.

  • max_marcd (float) – Skip pooling if any pair of samples has MARCD above this.

  • relate_pos_table (bool) – Tabulate relationships per position for relate data.

  • relate_read_table (bool) – Tabulate relationships per read for relate data

  • verify_times (bool) – Verify that report files from later steps have later timestamps.

  • num_cpus (bool) – Number of processors to use.

  • force (bool) – Force the report to be written, even if it exists.

Returns:

Path of the Pool report file.

Return type:

pathlib.Path

seismicrna.pool.run(pooled_sample: str = Sentinel.UNSET, input_path: Iterable[str | Path] = Sentinel.UNSET, *, relate_pos_table: bool = True, relate_read_table: bool = False, min_pearson: float = 0.0, max_marcd: float = 1.0, verify_times: bool = True, tmp_pfx: str | Path = './tmp', keep_tmp: bool = False, num_cpus: int = 4, force: bool = False) → list[Path]

Merge samples (vertically) from the Relate step.

Parameters:

  • relate_pos_table (bool) – Tabulate relationships per position for relate data [keyword-only, default: True]

  • relate_read_table (bool) – Tabulate relationships per read for relate data [keyword-only, default: False]

  • min_pearson (float) – Pool samples only if their Pearson correlation is at least this large [keyword-only, default: 0.0]

  • max_marcd (float) – Pool samples only if their mean arsince distance is at most this [keyword-only, default: 1.0]

  • verify_times (bool) – Verify that report files from later steps have later timestamps [keyword-only, default: True]

  • tmp_pfx (str | pathlib._local.Path) – Write all temporary files to a directory with this prefix [keyword-only, default: ‘./tmp’]

  • keep_tmp (bool) – Keep temporary files after finishing [keyword-only, default: False]

  • num_cpus (int) – Use up to this many CPUs simultaneously [keyword-only, default: 4]

  • force (bool) – Force all tasks to run, overwriting any existing output files [keyword-only, default: False]

seismicrna.pool.write_report(out_dir: Path, **kwargs)
seismicrna.table.get_dataset_flags(dataset: MutsDataset, relate_pos_table: bool, relate_read_table: bool, mask_pos_table: bool, mask_read_table: bool, cluster_pos_table: bool, cluster_abundance_table: bool)

Return the tabulator and table flags for a dataset.

seismicrna.table.get_tabulator_type(dataset_type: type[Dataset], count: bool = False) → type[DatasetTabulator] | type[CountTabulator]

Determine which class of Tabulator can process the dataset.

seismicrna.table.load_all_datasets(input_path: Iterable[str | Path], **kwargs)

Load datasets from all steps of the workflow.

seismicrna.table.run(input_path: Iterable[str | Path] = Sentinel.UNSET, *, relate_pos_table: bool = True, relate_read_table: bool = False, mask_pos_table: bool = True, mask_read_table: bool = True, cluster_pos_table: bool = True, cluster_abundance_table: bool = True, verify_times: bool = True, num_cpus: int = 4, force: bool = False) → list[Path]

Tabulate counts of relationships per read and position.

Parameters:

  • relate_pos_table (bool) – Tabulate relationships per position for relate data [keyword-only, default: True]

  • relate_read_table (bool) – Tabulate relationships per read for relate data [keyword-only, default: False]

  • mask_pos_table (bool) – Tabulate relationships per position for mask data [keyword-only, default: True]

  • mask_read_table (bool) – Tabulate relationships per read for mask data [keyword-only, default: True]

  • cluster_pos_table (bool) – Tabulate relationships per position for cluster data [keyword-only, default: True]

  • cluster_abundance_table (bool) – Tabulate number of reads per cluster for cluster data [keyword-only, default: True]

  • verify_times (bool) – Verify that report files from later steps have later timestamps [keyword-only, default: True]

  • num_cpus (int) – Use up to this many CPUs simultaneously [keyword-only, default: 4]

  • force (bool) – Force all tasks to run, overwriting any existing output files [keyword-only, default: False]

seismicrna.table.tabulate(dataset: MutsDataset, tabulator_type: type[DatasetTabulator], pos_table: bool, read_table: bool, clust_table: bool, force: bool, num_cpus: int)

Write tables for a dataset using the appropriate tabulator.

Parameters:

  • dataset (MutsDataset) – Dataset to tabulate (from the relate, mask, or cluster step).

  • tabulator_type (type[DatasetTabulator]) – Tabulator class that can process this dataset type.

  • pos_table (bool) – If True, write a per-position table.

  • read_table (bool) – If True, write a per-read table.

  • clust_table (bool) – If True, write a cluster abundance table.

  • force (bool) – If True, overwrite existing table files.

  • num_cpus (int) – Number of CPUs to use for computation.

seismicrna.urls.open_url(url: str)
seismicrna.wf.flatten(nested)
seismicrna.wf.run(fasta: str | Path = Sentinel.UNSET, input_path: Iterable[str | Path] = Sentinel.UNSET, *, out_dir: str | Path = './out', tmp_pfx: str | Path = './tmp', keep_tmp: bool = False, brotli_level: int = 10, force: bool = False, num_cpus: int = 4, fastqz: Iterable[str | Path] = (), fastqy: Iterable[str | Path] = (), fastqx: Iterable[str | Path] = (), phred_enc: int = 33, demult: bool = False, barcode_start: int = 0, barcode_end: int = 0, read_pos: int = None, barcode: tuple[tuple[str, DNA, int]] = (), mismatch_tolerance: int = 0, index_tolerance: int = 0, allow_n: bool = False, dmfastqz: Iterable[str | Path] = (), dmfastqy: Iterable[str | Path] = (), dmfastqx: Iterable[str | Path] = (), fastp: bool = True, fastp_5: bool = False, fastp_3: bool = True, fastp_w: int = 6, fastp_m: int = 25, fastp_poly_g: str = 'auto', fastp_poly_g_min_len: int = 10, fastp_poly_x: bool = False, fastp_poly_x_min_len: int = 10, fastp_adapter_trimming: bool = True, fastp_adapter_1: str = '', fastp_adapter_2: str = '', fastp_adapter_fasta: str | None = None, fastp_detect_adapter_for_pe: bool = True, fastp_min_length: int = 9, bt2_local: bool = True, bt2_discordant: bool = False, bt2_mixed: bool = False, bt2_dovetail: bool = False, bt2_contain: bool = True, bt2_score_min_e2e: str = 'L,-1,-0.8', bt2_score_min_loc: str = 'L,1,0.8', bt2_i: int = 0, bt2_x: int = 600, bt2_gbar: int = 4, bt2_l: int = 20, bt2_s: str = 'L,1,0.1', bt2_d: int = 4, bt2_r: int = 2, bt2_dpad: int = 2, bt2_orient: str = 'fr', bt2_un: bool = True, min_mapq: int = 25, sep_strands: bool = False, f1r2_fwd: bool = False, rev_label: str = '-rev', min_phred: int = 25, min_reads: int = 1000, insert3: bool = True, ambindel: bool = True, overhangs: bool = True, clip_end5: int = 4, clip_end3: int = 4, batch_size: int = 65536, write_read_names: bool = False, relate_pos_table: bool = True, relate_read_table: bool = False, relate_cx: bool = True, mask_coords: Iterable[tuple[str, int, int]] = (), mask_primers: Iterable[tuple[str, DNA, DNA]] = (), primer_gap: int = 0, mask_regions_file: str | None = None, count_del: bool = True, count_ins: bool = True, no_mut: Iterable[str] = (), only_mut: Iterable[str] = (), probe: str = 'DMS', mask_a: bool | None = None, mask_c: bool | None = None, mask_g: bool | None = None, mask_u: bool | None = None, mask_polya: int = 5, mask_pos: Iterable[tuple[str, int]] = (), mask_pos_file: Iterable[str | Path] = (), mask_read: Iterable[str] = (), mask_read_file: Iterable[str | Path] = (), mask_discontig: bool = True, min_ncov_read: int = 1, min_fcov_read: float = 0.0, min_finfo_read: float = 0.95, max_fmut_read: float = 1.0, min_mut_gap: int = None, mut_collisions: str = 'auto', min_ninfo_pos: int = 1000, max_fmut_pos: float = 1.0, quick_unbias: bool = True, quick_unbias_thresh: float = 0.001, max_mask_iter: int = 0, mask_pos_table: bool = True, mask_read_table: bool = True, cluster: bool = False, min_clusters: int = 1, max_clusters: int = 0, min_em_runs: int = 6, max_em_runs: int = 30, jackpot: bool = True, jackpot_conf_level: float = 0.95, max_jackpot_quotient: float = 1.1, max_jackpot_sims: int = 12, jackpot_max_data: int = 268435456, min_em_iter: int = 10, max_em_iter: int = 500, em_thresh: float = 0.37, min_marcd_run: float = 0.016, max_pearson_run: float = 0.9, max_arcd_vs_ens_avg: float = 0.2, max_gini_run: float = 0.667, max_loglike_vs_best: float = 0.0, min_pearson_vs_best: float = 0.97, max_marcd_vs_best: float = 0.008, try_all_ks: bool = False, write_all_ks: bool = False, cluster_pos_table: bool = True, cluster_abundance_table: bool = True, verify_times: bool = True, fold: bool = False, fold_coords: Iterable[tuple[str, int, int]] = (), fold_primers: Iterable[tuple[str, DNA, DNA]] = (), fold_regions_file: str | None = None, fold_full: bool = True, fold_dry_run: bool = False, fold_backend: str = 'auto', fold_temp: float = 37.0, fold_energy_method: str = 'auto', deigan_slope: float = 1.8, deigan_intercept: float = -0.6, fold_quantile: float = 0.95, fold_constraint: str | None = None, fold_commands: str | None = None, eddy_prior_paired_file: str | None = None, eddy_prior_unpaired_file: str | None = None, fold_md: int = 0, fold_mfe: bool = False, fold_max: int = 20, fold_percent: float = 20.0, fold_isolated: bool = False, draw: bool = False, struct_num: Iterable[int] = (), color: bool = True, draw_svg: bool = True, draw_png: bool = False, update_rnartistcore: bool = False, export: bool = False, samples_meta: str = None, refs_meta: str = None, all_pos: bool = True, cgroup: str = 'k', graph_quantile: float = 0.0, hist_bins: int = 10, hist_margin: float = 0.1, struct_file: Iterable[str | Path] = (), terminal_pairs: bool = True, window: int = 45, winmin: int = 9, csv: bool = True, html: bool = True, svg: bool = False, pdf: bool = False, png: bool = False, graph_mprof: bool = True, graph_tmprof: bool = True, graph_ncov: bool = True, graph_mhist: bool = True, graph_abundance: bool = True, graph_giniroll: bool = False, graph_roc: bool = True, graph_aucroll: bool = False, graph_poscorr: bool = False, graph_mutdist: bool = False, mutdist_null: bool = True, collate: bool = True, name: str = 'collated', verbose_name: bool = False, include_svg: bool = True, include_graph: bool = True, group: str = 'sample', portable: bool = False, collate_out_dir: str | Path | None = None, seed: int | None = None)

Run the entire workflow.

Parameters:

  • out_dir (str | pathlib._local.Path) – Write all output files to this directory [keyword-only, default: ‘./out’]

  • tmp_pfx (str | pathlib._local.Path) – Write all temporary files to a directory with this prefix [keyword-only, default: ‘./tmp’]

  • keep_tmp (bool) – Keep temporary files after finishing [keyword-only, default: False]

  • brotli_level (int) – Compress pickle files with this level of Brotli (0 - 11) [keyword-only, default: 10]

  • force (bool) – Force all tasks to run, overwriting any existing output files [keyword-only, default: False]

  • num_cpus (int) – Use up to this many CPUs simultaneously [keyword-only, default: 4]

  • fastqz (Iterable) – FASTQ file(s) of single-end reads [keyword-only, default: ()]

  • fastqy (Iterable) – FASTQ file(s) of paired-end reads with mates 1 and 2 interleaved [keyword-only, default: ()]

  • fastqx (Iterable) – FASTQ files of paired-end reads with mates 1 and 2 in separate files [keyword-only, default: ()]

  • phred_enc (int) – Specify the Phred score encoding of FASTQ and SAM/BAM/CRAM files [keyword-only, default: 33]

  • demult (bool) – Enable demultiplexing [keyword-only, default: False]

  • barcode_start (int) – Index of start of barcode [keyword-only, default: 0]

  • barcode_end (int) – Index of end of barcode [keyword-only, default: 0]

  • read_pos (int) – Expected position of the barcode in the read (1-indexed). Defaults to –barcode-start [keyword-only, default: None]

  • barcode (tuple) – A list of barcode name, barcode sequence, and barcode position (1-indexed relative to read start) to demultiplex [keyword-only, default: ()]

  • mismatch_tolerance (int) – Designates the allowable amount of mismatches allowed in a string and still be considered a valid pattern find. will increase non-parallel computation at a factorial rate. use caution going above 2 mismatches. does not apply to clipped sequences. [keyword-only, default: 0]

  • index_tolerance (int) – Designates the allowable amount of distance you allow the pattern to be found in a read from the reference index [keyword-only, default: 0]

  • allow_n (bool) – Allow N as a valid mismatch when –mismatch-tolerance ≥ 1. Increases memory consumption. [keyword-only, default: False]

  • dmfastqz (Iterable) – Demultiplexed FASTQ files of single-end reads [keyword-only, default: ()]

  • dmfastqy (Iterable) – Demultiplexed FASTQ files of paired-end reads interleaved in one file [keyword-only, default: ()]

  • dmfastqx (Iterable) – Demultiplexed FASTQ files of mate 1 and mate 2 reads [keyword-only, default: ()]

  • fastp (bool) – Use fastp to QC, filter, and trim reads before alignment [keyword-only, default: True]

  • fastp_5 (bool) – Trim low-quality bases from the 5’ ends of reads [keyword-only, default: False]

  • fastp_3 (bool) – Trim low-quality bases from the 3’ ends of reads [keyword-only, default: True]

  • fastp_w (int) – Use this window size (nt) for –fastp-5 and –fastp-3 [keyword-only, default: 6]

  • fastp_m (int) – Use this mean quality threshold for –fastp-5 and –fastp-3 [keyword-only, default: 25]

  • fastp_poly_g (str) – Trim poly(G) tails (two-color sequencing artifacts) from the 3’ end [keyword-only, default: ‘auto’]

  • fastp_poly_g_min_len (int) – Minimum number of Gs to consider a poly(G) tail for –fastp-poly-g [keyword-only, default: 10]

  • fastp_poly_x (bool) – Trim poly(X) tails (i.e. of any nucleotide) from the 3’ end [keyword-only, default: False]

  • fastp_poly_x_min_len (int) – Minimum number of bases to consider a poly(X) tail for –fastp-poly-x [keyword-only, default: 10]

  • fastp_adapter_trimming (bool) – Trim adapter sequences from the 3’ ends of reads [keyword-only, default: True]

  • fastp_adapter_1 (str) – Trim this adapter sequence from the 3’ ends of read 1s [keyword-only, default: ‘’]

  • fastp_adapter_2 (str) – Trim this adapter sequence from the 3’ ends of read 2s [keyword-only, default: ‘’]

  • fastp_adapter_fasta (str | None) – Trim adapter sequences in this FASTA file from the 3’ ends of reads [keyword-only, default: None]

  • fastp_detect_adapter_for_pe (bool) – Automatically detect the adapter sequences for paired-end reads [keyword-only, default: True]

  • fastp_min_length (int) – Discard reads shorter than this length [keyword-only, default: 9]

  • bt2_local (bool) – Align reads in local mode rather than end-to-end mode [keyword-only, default: True]

  • bt2_discordant (bool) – Output paired-end reads whose mates align discordantly [keyword-only, default: False]

  • bt2_mixed (bool) – Attempt to align individual mates of pairs that fail to align [keyword-only, default: False]

  • bt2_dovetail (bool) – Consider dovetailed mate pairs to align concordantly [keyword-only, default: False]

  • bt2_contain (bool) – Consider nested mate pairs to align concordantly [keyword-only, default: True]

  • bt2_score_min_e2e (str) – Discard alignments that score below this threshold in end-to-end mode [keyword-only, default: ‘L,-1,-0.8’]

  • bt2_score_min_loc (str) – Discard alignments that score below this threshold in local mode [keyword-only, default: ‘L,1,0.8’]

  • bt2_i (int) – Discard paired-end alignments shorter than this many bases [keyword-only, default: 0]

  • bt2_x (int) – Discard paired-end alignments longer than this many bases [keyword-only, default: 600]

  • bt2_gbar (int) – Do not place gaps within this many bases from the end of a read [keyword-only, default: 4]

  • bt2_l (int) – Use this seed length for Bowtie2 [keyword-only, default: 20]

  • bt2_s (str) – Seed Bowtie2 alignments at this interval [keyword-only, default: ‘L,1,0.1’]

  • bt2_d (int) – Discard alignments if over this many consecutive seed extensions fail [keyword-only, default: 4]

  • bt2_r (int) – Re-seed reads with repetitive seeds up to this many times [keyword-only, default: 2]

  • bt2_dpad (int) – Pad the alignment matrix with this many bases (to allow gaps) [keyword-only, default: 2]

  • bt2_orient (str) – Require paired mates to have this orientation [keyword-only, default: ‘fr’]

  • bt2_un (bool) – Output unaligned reads to a FASTQ file [keyword-only, default: True]

  • min_mapq (int) – Discard reads with mapping qualities below this threshold [keyword-only, default: 25]

  • sep_strands (bool) – Separate each alignment map into forward- and reverse-strand reads [keyword-only, default: False]

  • f1r2_fwd (bool) – With –sep-strands, consider forward mate 1s and reverse mate 2s to be forward-stranded [keyword-only, default: False]

  • rev_label (str) – With –sep-strands, add this label to each reverse-strand reference [keyword-only, default: ‘-rev’]

  • min_phred (int) – Mark base calls with Phred scores lower than this threshold as ambiguous [keyword-only, default: 25]

  • min_reads (int) – Discard alignment maps with fewer than this many reads [keyword-only, default: 1000]

  • insert3 (bool) – Mark each insertion on the base to its 3’ (True) or 5’ (False) side [keyword-only, default: True]

  • ambindel (bool) – Mark all ambiguous insertions and deletions (indels) [keyword-only, default: True]

  • overhangs (bool) – Retain the overhangs of paired-end mates that dovetail [keyword-only, default: True]

  • clip_end5 (int) – Clip this many bases from the 5’ end of each read [keyword-only, default: 4]

  • clip_end3 (int) – Clip this many bases from the 3’ end of each read [keyword-only, default: 4]

  • batch_size (int) – Limit batches to at most this many reads [keyword-only, default: 65536]

  • write_read_names (bool) – Write the name of each read in a second set of batches (necessary for the options –mask-read or –mask-read-file) [keyword-only, default: False]

  • relate_pos_table (bool) – Tabulate relationships per position for relate data [keyword-only, default: True]

  • relate_read_table (bool) – Tabulate relationships per read for relate data [keyword-only, default: False]

  • relate_cx (bool) – Use a fast (C extension module) version of the relate algorithm; the slow (Python) version is still avilable as a fallback if the C extension cannot be loaded, and for debugging/benchmarking [keyword-only, default: True]

  • mask_coords (Iterable) – Select a region of a reference given its 5’ and 3’ end coordinates [keyword-only, default: ()]

  • mask_primers (Iterable) – Select a region of a reference given its forward and reverse primers [keyword-only, default: ()]

  • primer_gap (int) – Leave a gap of this many bases between the primer and the region [keyword-only, default: 0]

  • mask_regions_file (str | None) – Select regions of references from coordinates/primers in a CSV file [keyword-only, default: None]

  • count_del (bool) – Count deletions as mutations [keyword-only, default: True]

  • count_ins (bool) – Count insertions as mutations [keyword-only, default: True]

  • no_mut (Iterable) – Do not count this type of mutation (overrides –count-del/ins) [keyword-only, default: ()]

  • only_mut (Iterable) – Count only this type of mutation (overrides other mutation settings) [keyword-only, default: ()]

  • probe (str) – Use default mask options for this chemical probe [keyword-only, default: ‘DMS’]

  • mask_a (bool | None) – Mask positions with base A [keyword-only, default: None]

  • mask_c (bool | None) – Mask positions with base C [keyword-only, default: None]

  • mask_g (bool | None) – Mask positions with base G [keyword-only, default: None]

  • mask_u (bool | None) – Mask positions with base U [keyword-only, default: None]

  • mask_polya (int) – Mask stretches of at least this many consecutive A bases (0 disables) [keyword-only, default: 5]

  • mask_pos (Iterable) – Mask this position in this reference [keyword-only, default: ()]

  • mask_pos_file (Iterable) – Mask positions in references from a file [keyword-only, default: ()]

  • mask_read (Iterable) – Mask the read with this name [keyword-only, default: ()]

  • mask_read_file (Iterable) – Mask the reads with names in this file [keyword-only, default: ()]

  • mask_discontig (bool) – Mask paired-end reads with discontiguous mates [keyword-only, default: True]

  • min_ncov_read (int) – Mask reads with fewer than this many bases covering the region [keyword-only, default: 1]

  • min_fcov_read (float) – Mask reads covering less than this fraction of the region [keyword-only, default: 0.0]

  • min_finfo_read (float) – Mask reads with less than this fraction of informative base calls [keyword-only, default: 0.95]

  • max_fmut_read (float) – Mask reads with more than this fraction of mutated base calls [keyword-only, default: 1.0]

  • min_mut_gap (int) – Mask reads with two mutations separated by fewer than this many bases [keyword-only, default: None]

  • mut_collisions (str) – If two mutations are closer than –min-mut-gap positions, MERGE the mutations, DROP the read, or AUTO-select based on the probe. [keyword-only, default: ‘auto’]

  • min_ninfo_pos (int) – Mask positions with fewer than this many informative base calls [keyword-only, default: 1000]

  • max_fmut_pos (float) – Mask positions with more than this fraction of mutated base calls [keyword-only, default: 1.0]

  • quick_unbias (bool) – Correct observer bias using a quick (typically linear time) heuristic [keyword-only, default: True]

  • quick_unbias_thresh (float) – Treat mutated fractions under this threshold as 0 with –quick-unbias [keyword-only, default: 0.001]

  • max_mask_iter (int) – Stop masking after this many iterations (0 for no limit) [keyword-only, default: 0]

  • mask_pos_table (bool) – Tabulate relationships per position for mask data [keyword-only, default: True]

  • mask_read_table (bool) – Tabulate relationships per read for mask data [keyword-only, default: True]

  • cluster (bool) – Cluster reads to find alternative structures [keyword-only, default: False]

  • min_clusters (int) – Start at this many clusters [keyword-only, default: 1]

  • max_clusters (int) – Stop at this many clusters (0 for no limit) [keyword-only, default: 0]

  • min_em_runs (int) – Run EM (successfully) at least this number of times for each K [keyword-only, default: 6]

  • max_em_runs (int) – Run EM (successfully or not) at most this number of times for each K [keyword-only, default: 30]

  • jackpot (bool) – Calculate the jackpotting quotient to find over-represented reads [keyword-only, default: True]

  • jackpot_conf_level (float) – Confidence level for the jackpotting quotient confidence interval [keyword-only, default: 0.95]

  • max_jackpot_quotient (float) – Remove runs whose jackpotting quotient exceeds this limit [keyword-only, default: 1.1]

  • max_jackpot_sims (int) – Maximum number of simulations to compute the jackpotting quotient [keyword-only, default: 12]

  • jackpot_max_data (int) – Skip calculating the jackpotting quotient if reads × positions exceeds this limit [keyword-only, default: 268435456]

  • min_em_iter (int) – Run EM for at least this many iterations [keyword-only, default: 10]

  • max_em_iter (int) – Run EM for at most this many iterations [keyword-only, default: 500]

  • em_thresh (float) – Stop EM when the log likelihood increases by less than this threshold [keyword-only, default: 0.37]

  • min_marcd_run (float) – Remove runs with two clusters that differ by less than this MARCD [keyword-only, default: 0.016]

  • max_pearson_run (float) – Remove runs with two clusters more similar than this correlation [keyword-only, default: 0.9]

  • max_arcd_vs_ens_avg (float) – Remove runs where a cluster differs by more than this ARCD from the ensemble average at any position [keyword-only, default: 0.2]

  • max_gini_run (float) – Remove runs where any cluster’s Gini coefficient exceeds this limit [keyword-only, default: 0.667]

  • max_loglike_vs_best (float) – Remove Ks with a log likelihood gap larger than this (0 for no limit) [keyword-only, default: 0.0]

  • min_pearson_vs_best (float) – Remove Ks where every run has less than this correlation vs. the best [keyword-only, default: 0.97]

  • max_marcd_vs_best (float) – Remove Ks where every run has more than this MARCD vs. the best [keyword-only, default: 0.008]

  • try_all_ks (bool) – Try all numbers of clusters (Ks), even after finding the best number [keyword-only, default: False]

  • write_all_ks (bool) – Write all numbers of clusters (Ks), rather than only the best number [keyword-only, default: False]

  • cluster_pos_table (bool) – Tabulate relationships per position for cluster data [keyword-only, default: True]

  • cluster_abundance_table (bool) – Tabulate number of reads per cluster for cluster data [keyword-only, default: True]

  • verify_times (bool) – Verify that report files from later steps have later timestamps [keyword-only, default: True]

  • fold (bool) – Predict the secondary structure using the reactivities [keyword-only, default: False]

  • fold_coords (Iterable) – Fold a region of a reference given its 5’ and 3’ end coordinates [keyword-only, default: ()]

  • fold_primers (Iterable) – Fold a region of a reference given its forward and reverse primers [keyword-only, default: ()]

  • fold_regions_file (str | None) – Fold regions of references from coordinates/primers in a CSV file [keyword-only, default: None]

  • fold_full (bool) – If no regions are specified, whether to default to the full region or to the table’s region [keyword-only, default: True]

  • fold_dry_run (bool) – Only generate the fold command and input files; do not run folding [keyword-only, default: False]

  • fold_backend (str) – Model RNA structures using Fold (RNAstructure), ShapeKnots (RNAstructure), or RNAfold (ViennaRNA); auto selects Fold for DMS and RNAFold for other probes [keyword-only, default: ‘auto’]

  • fold_temp (float) – Predict structures at this temperature (Celsius) [keyword-only, default: 37.0]

  • fold_energy_method (str) – Use this method to incorporate reactivities into folding energies. auto selects Cordero for DMS and Eddy for other probes; Eddy requires –fold-backend=RNAFold; Cordero requires –fold-backend=Fold or ShapeKnots [keyword-only, default: ‘auto’]

  • deigan_slope (float) – Slope (kcal/mol) for SHAPE reactivities using Deigan method; used only with –fold-energy-method=Deigan [keyword-only, default: 1.8]

  • deigan_intercept (float) – Intercept (kcal/mol) for SHAPE reactivities using Deigan method; used only with –fold-energy-method=Deigan [keyword-only, default: -0.6]

  • fold_quantile (float) – Normalize and winsorize reactivities to this quantile for folding [keyword-only, default: 0.95]

  • fold_constraint (str | None) – Force bases to be paired/unpaired from a file of constraints [keyword-only, default: None]

  • fold_commands (str | None) – Command file for RNAFold [keyword-only, default: None]

  • eddy_prior_paired_file (str | None) – File of per-position prior probabilities of being paired for the Eddy method (passed as –sp-data with –sp-strategy Pp); only used with –fold-energy-method=Eddy and –fold-backend=RNAFold [keyword-only, default: None]

  • eddy_prior_unpaired_file (str | None) – File of per-position prior probabilities of being unpaired for the Eddy method (passed as –sp-data with –sp-strategy Pu); only used with –fold-energy-method=Eddy and –fold-backend=RNAFold [keyword-only, default: None]

  • fold_md (int) – Limit base pair distances to this number of bases (0 for no limit) [keyword-only, default: 0]

  • fold_mfe (bool) – Predict only the minimum free energy (MFE) structure [keyword-only, default: False]

  • fold_max (int) – Output at most this many structures (overriden by –fold-mfe) [keyword-only, default: 20]

  • fold_percent (float) – Stop outputting structures when the % difference in energy exceeds this value (overriden by –fold-mfe) [keyword-only, default: 20.0]

  • fold_isolated (bool) – Allow isolated (non-stacked) base pairs when folding [keyword-only, default: False]

  • draw (bool) – Draw secondary structures with RNArtist. [keyword-only, default: False]

  • struct_num (Iterable) – Draw the specified structure (zero-indexed) or -1 for all structures. By default, draw the structure with the best AUROC. [keyword-only, default: ()]

  • color (bool) – Color bases by their reactivity [keyword-only, default: True]

  • draw_svg (bool) – Output each drawing in a Scalable Vector Graphics file [keyword-only, default: True]

  • draw_png (bool) – Output each drawing in a Portable Network Graphics file [keyword-only, default: False]

  • update_rnartistcore (bool) – Check for and install updates to RNArtistCore. [keyword-only, default: False]

  • export (bool) – Export each sample to SEISMICgraph (https://seismicrna.org) [keyword-only, default: False]

  • samples_meta (str) – Add sample metadata from this CSV file to exported results [keyword-only, default: None]

  • refs_meta (str) – Add reference metadata from this CSV file to exported results [keyword-only, default: None]

  • all_pos (bool) – Export all positions (not just unmasked positions) [keyword-only, default: True]

  • cgroup (str) – Put each Cluster in its own file, each K in its own file, or All clusters in one file [keyword-only, default: ‘k’]

  • graph_quantile (float) – Normalize and winsorize ratios to this quantile (0 disables) [keyword-only, default: 0.0]

  • hist_bins (int) – Number of bins in each histogram; must be ≥ 1 [keyword-only, default: 10]

  • hist_margin (float) – Autofill margins of at most this width in histograms of ratios [keyword-only, default: 0.1]

  • struct_file (Iterable) – Compare mutational profiles to the structure(s) in this CT file [keyword-only, default: ()]

  • terminal_pairs (bool) – Include terminal base pairs (at the ends of stems) in ROC curves [keyword-only, default: True]

  • window (int) – Use a sliding window of this many bases [keyword-only, default: 45]

  • winmin (int) – Mask sliding windows with fewer than this number of data [keyword-only, default: 9]

  • csv (bool) – Output the data for each graph in a Comma-Separated Values file [keyword-only, default: True]

  • html (bool) – Output each graph in an interactive HyperText Markup Language file [keyword-only, default: True]

  • svg (bool) – Output each graph in a Scalable Vector Graphics file [keyword-only, default: False]

  • pdf (bool) – Output each graph in a Portable Document Format file [keyword-only, default: False]

  • png (bool) – Output each graph in a Portable Network Graphics file [keyword-only, default: False]

  • graph_mprof (bool) – Graph mutational profiles [keyword-only, default: True]

  • graph_tmprof (bool) – Graph typed mutational profiles [keyword-only, default: True]

  • graph_ncov (bool) – Graph coverages per position [keyword-only, default: True]

  • graph_mhist (bool) – Graph histograms of mutations per read [keyword-only, default: True]

  • graph_abundance (bool) – Graph abundance of each cluster [keyword-only, default: True]

  • graph_giniroll (bool) – Graph rolling Gini coefficients [keyword-only, default: False]

  • graph_roc (bool) – Graph receiver operating characteristic (ROC) curves [keyword-only, default: True]

  • graph_aucroll (bool) – Graph rolling areas under ROC curves (AUC-ROC) [keyword-only, default: False]

  • graph_poscorr (bool) – Graph phi correlations between positions [keyword-only, default: False]

  • graph_mutdist (bool) – Graph distances between mutations [keyword-only, default: False]

  • mutdist_null (bool) – Include the null distribution of distances between mutations [keyword-only, default: True]

  • collate (bool) – Collate HTML graphs and SVG drawings into an HTML report file. [keyword-only, default: True]

  • name (str) – Prefix the HTML report with this name. [keyword-only, default: ‘collated’]

  • verbose_name (bool) – Add collated file information to report name. [keyword-only, default: False]

  • include_svg (bool) – Include RNA structure drawings from the draw module. [keyword-only, default: True]

  • include_graph (bool) – Include graphs from the graph module. [keyword-only, default: True]

  • group (str) – Group collated graphs by one of ‘sample’, ‘graph’, ‘branches’, ‘region’, or ‘all’. [keyword-only, default: ‘sample’]

  • portable (bool) – Embed collated graphs into the output HTML file for portability at the expense of live updates and file size. [keyword-only, default: False]

  • collate_out_dir (str | pathlib._local.Path | None) – Write collated report to this directory. By default, write to the lowest level directory common to all input graphs. [keyword-only, default: None]

  • seed (int | None) – Seed for the random number generator [keyword-only, default: None]