dynast.count

Module Contents

Functions

count(bam_path: str, gtf_path: str, out_dir: str, strand: typing_extensions.Literal[forward, reverse, unstranded] = 'forward', umi_tag: Optional[str] = None, barcode_tag: Optional[str] = None, gene_tag: str = 'GX', barcodes: Optional[List[str]] = None, control: bool = False, quality: int = 27, conversions: FrozenSet[FrozenSet[str]] = frozenset({frozenset({'TC'})}), snp_threshold: Optional[float] = None, snp_min_coverage: int = 1, snp_csv: Optional[str] = None, n_threads: int = 8, temp_dir: Optional[str] = None, velocity: bool = True, strict_exon_overlap: bool = False, dedup_mode: typing_extensions.Literal[auto, exon, conversion] = 'auto', by_name: bool = False, nasc: bool = False, overwrite: bool = False)

Main interface for the count command.

dynast.count.count(bam_path: str, gtf_path: str, out_dir: str, strand: typing_extensions.Literal[forward, reverse, unstranded] = 'forward', umi_tag: Optional[str] = None, barcode_tag: Optional[str] = None, gene_tag: str = 'GX', barcodes: Optional[List[str]] = None, control: bool = False, quality: int = 27, conversions: FrozenSet[FrozenSet[str]] = frozenset({frozenset({'TC'})}), snp_threshold: Optional[float] = None, snp_min_coverage: int = 1, snp_csv: Optional[str] = None, n_threads: int = 8, temp_dir: Optional[str] = None, velocity: bool = True, strict_exon_overlap: bool = False, dedup_mode: typing_extensions.Literal[auto, exon, conversion] = 'auto', by_name: bool = False, nasc: bool = False, overwrite: bool = False)[source]

Main interface for the count command.

Parameters
bam_path

Path to BAM

gtf_path

Path to GTF

out_dir

Path to output directory

strand

Strandedness of technology

umi_tag

BAM tag to use as UMIs

barcode_tag

BAM tag to use as barcodes

gene_tag

BAM tag to use as genes

barcodes

List of barcodes to consider

control

Whether this is a control sample

quality

Quality threshold in detecting conversions

conversions

Set of conversions to quantify

snp_threshold

Call genomic locations that have greater than this proportion of specific conversions as a SNP

snp_min_coverage

Only consider genomic locations with at least this many mapping reads for SNP calling

snp_csv

CSV containing SNPs

n_threads

Number of threads to use

temp_dir

Temporary directory

velocity

Whether to quantify spliced/unspliced RNA

strict_exon_overlap

Whether spliced/unspliced RNA quantification is strict

dedup_mode

UMI deduplication mode

by_name

Whether to group counts by gene name instead of ID

nasc

Whether to match NASC-seq pipeline behavior

overwrite

Overwrite existing files