iCLIP.meta.meta_gene

iCLIP.meta.meta_gene(gtf_filelike, bam, bins=[10, 100, 10], flanks=100, output_matrix=False, calculate_flanks=False, pseudo_count=0, row_norm=True)

Produce a metagene across a gtf file from CLIP data, where each gene is divided into the same number of bins.

Parameters:
  • gtffile_like (file or buffer or similar) – Handle to a GTF file containing annotations to count across
  • bam (func) – getter function, as created by make_getter(), from which to retrieve cross-link data
  • bins (sequence of int, optional) – Length 3 sequence containing the number of bins in the 5’ flank, the body of each transcripts and the 3’ flank.
  • flanks (int, optional) – Length, in bp of the flanking regions.
  • output_matrix (False, optional) – Output the whole (#transcripts, #bins) matrix alongside the averaged profile.
  • calculate_flanks (bool, optional) – Calculate the size of the flanks seperately for each transcript so that each flank bin is the same width as each transcript body bin.
  • pseudo_count (int, optional) – pseudocount to add to each bin, , minimizing the effect of transcripts with a single or small number of cross-linked bases in a row_norm-ed profile.
  • row_norm (bool, optional) – Divide counts in each bin by the row-sum for each transcript?
Returns:

Averaged profile over all transcripts. Will have pandas.MultiIndex with first level corresponding to the region [“flank5”, “exons”, “flank3”]. Second level is the bin within the regions.
Return type:

pandas.Series of float