Which method is the best for using in "dba.count" in Diffbind R package
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20 months ago
sadman.sakib ▴ 80

I am analyzing ChIP seq data using diffbind. In dba.count(), there are many parameters, including many scoring functions as follows:

  1. DBA_SCORE_READS raw read count for interval using only reads from ChIP
  2. DBA_SCORE_READS_FOLD raw read count for interval from ChIP divided by read count for interval from control
  3. DBA_SCORE_READS_MINUS raw read count for interval from ChIP minus read count for interval from control
  4. DBA_SCORE_RPKM RPKM for interval using only reads from ChIP
  5. DBA_SCORE_RPKM_FOLD RPKM for interval from ChIP divided by RPKM for interval from control
  6. DBA_SCORE_TMM_READS_FULL TMM normalized (using edgeR), using ChIP read counts and Full Library size
  7. DBA_SCORE_TMM_READS_EFFECTIVE TMM normalized (using edgeR), using ChIP read counts and Effective Library size
  8. DBA_SCORE_TMM_MINUS_FULL TMM normalized (using edgeR), using ChIP read counts minus Control read counts and Full Library size
  9. DBA_SCORE_TMM_MINUS_EFFECTIVE TMM normalized (using edgeR), using ChIP read counts minus Control read counts and Effective Library size
  10. DBA_SCORE_TMM_READS_FULL_CPM same as DBA_SCORE_TMM_READS_FULL, but reported in counts-per-million.
  11. DBA_SCORE_TMM_READS_EFFECTIVE_CPM same as DBA_SCORE_TMM_READS_EFFECTIVE, but reported in counts-per-million.
  12. DBA_SCORE_TMM_MINUS_FULL_CPM same as DBA_SCORE_TMM_MINUS_FULL, but reported in counts-per-million.
  13. DBA_SCORE_TMM_MINUS_EFFECTIVE_CPM same as DBA_SCORE_TMM_MINUS_EFFECTIVE, but reported in counts-per-million.
  14. DBA_SCORE_SUMMIT summit height (maximum read pileup value)
  15. DBA_SCORE_SUMMIT_ADJ summit height (maximum read pileup value), normalized to relative library size
  16. DBA_SCORE_SUMMIT_POS summit position (location of maximum read pileup)

As a naive user, my question is, which method is the best to generate counts from ChIP seq data? Also, if you do not select anything, which is the default behaviour? Thank you in advance!

ChIP-Seq diffbind • 1.4k views
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Difficult to tell without details on your experiment. As a beginner it is typically recommended to extensively read the manual and leave everything at default until you have the experience and undertanding to change options.

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20 months ago
Rory Stark ★ 1.1k

One important thing to note is that the score computed by dba.count() is only used for plotting the entire binding matrix. The values used for the differential analysis (using dba.analyze()) are determined at analysis time based on the values of certain parameters (method, bSubControl, and bFullLibrarySize).

The default score is DBA_SCORE_TMM_MINUS_FULL (as described in the help page for dba.count()), but this is only used for global plots. This score represents TMM normalized read counts after the control reads have been subtracted. Using something like DBA_SCORE_RPKM gives what are probably the least "biased" scores for use in these plots.

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