coalispr.count_analyze.annot¶

Module for annotating counted segments with gen_id’s from GTFs

Attributes¶

`annotate_clust_file`(path, kind, ref, heading)	Return dataframe with annotated clusters read from file.
`annotate_count_frame`(df, kind, ref, heading)	Return dataframe with annotations for counts in the input frame.
`annotate_libtotals`(rdkind, strand, kind, ref, ...)	Annotate library counts

coalispr.count_analyze.annot.annotate_clust_file(path, kind, ref, heading)¶

Return dataframe with annotated clusters read from file.

Parameters:

path (str) – Path to count file with segments and counts (after clustering).
kind (str) – Kind of data, SPECIFIC (default) or UNSPECIFIC.
ref (bool) – Include general REFERENCE annotations.
heading (str) – Name of dataframe column with annotations.

coalispr.count_analyze.annot.annotate_count_frame(df, kind, ref, heading)¶

Return dataframe with annotations for counts in the input frame.

Parameters:

coalispr.count_analyze.annot.annotate_libtotals(rdkind, strand, kind, ref, showdiscards, log2, sortval)¶

Annotate library counts

Relevant file-titles: “{kind}{COU}_{strand}{TSV}”.

Parameters:

rdkind (str) – One of LIBR, UNIQ, COLLR. Choose all (LIBR), only uniquely-mapped reads (UNIQ, leaving out repetitive sequences, MULMAP, like tRNA, rRNA or common transposons).
strand (str) – One of {ALL_COMBI, COMBI, MUNR, CORB}
kind (str) – Name determining kind of reads, SPECIFIC or UNSPECIFIC or FRACTION
ref (bool) – Include general REFERENCE GTF for annotations (slow) if True.
showdiscards (bool) – Include discarded samples.
log2 (bool) – Use log2 scale if True.
sortval (bool) – Sort table with respect to values, descending from highest if True.