TAMA GO: Degradation Signature

This tool in TAMA-GO is used to assess degradation signature of cDNA libraries and get useful stats about the annotation.

tama_degradation_signature.py

To run tama_degradation_signature.py you first need to run TAMA Collapse with both the "Capped" and "No Cap" algorithms. Both runs should otherwise have identical parameters. The inputs for this tool are the trans_read.bed files from these runs.

USAGE:

python tama_degradation_signature.py -c capped_trans_read.bed -nc nocap_trans_read.bed -o outfile_name

Input explanation:

capped_trans_read.bed - This is the trans_read.bed file that was output from the TAMA Collapse capped run.

nocap_trans_read.bed - This is the trans_read.bed file that was output from the TAMA Collapse no_cap run.

outfile_name - This is the name of the output file which will contain a summary of stats including the degradation signature.

The output will look like this:

  Degradation Signature = 0.41700034321
  Capped multi-exon, multi-read, transcript count = 61187
  No-cap multi-exon, multi-read, transcript count = 35672
  Capped total transcript count = 76518
  No-cap total transcript count = 49544
  Capped single exon trans count = 28755
  No-cap single exon trans count = 15854
  Capped multi exon trans count = 47763
  No-cap multi exon trans count = 33690
  Capped total gene count = 21722
  No-cap total gene count = 21722
  Capped single exon gene count = 11158
  No-cap single exon gene count = 11158
  Capped multi exon gene count = 10564
  No-cap multi exon gene count = 10564
  Capped single exon single read gene count = 9794
  No-cap single exon single read gene count = 9794
  Capped multi exon single read gene count = 2019
  No-cap multi exon single read gene count = 2019

Note that gene counts should be the same for the capped and no_cap runs. These numbers are shown for trouble shooting in case the wrong input files are used.

A degradation signature higher than 0.25 is considered high and indicates a large number of degraded products in the sequenced RNA.