Skip to main content

Table 1 Comparison of different peak-calling algorithms

From: BayesPeak: Bayesian analysis of ChIP-seq data

Method A B C D E F G
CSPF control or IP only read length
no orientation
merge strands
no shift
N simple height criteria ROC curve (empirically) both
XSET IP only fragment length
orientation
merge strands
no shift
Y simple height criteria FDR estimate using Poisson distribution both
Mikkelsen et al. IP only no orientation no merge
no shift
Y p-values from permutations no official FDR both
MACS control or IP only fragment length
orientation
no duplicated reads
shift reads
merge strands
N Poisson p-values FDR estimate by peaks in control:IP both
QuEST control orientation shift reads
merge strands
N kernel density estimation FDR estimate by permutations of the control better for TF
FindPeaks IP only fragment length
orientation
no merge
no shift
N simple height criteria FDR estimate by permutations of the IP both
SISSR control or IP only fragment length
orientation
no merge
no shift
N compares reads on different strands FDR estimate by peaks in background:IP better for TF
Kharchenko et al. control orientation no merge
no shift
N Poisson distribution FDR estimate by permutations of the control better for TF
PeakSeq control fragment length
orientation
merge strands Y sample normalisation Binomial distribution FDR estimate, q-values (BH correction) both
BayesPeak control or IP only fragment length
orientation
no merge
no shift
N negative binomial distribution, Bayesian posterior probabilities posterior enrichment probabilities both
  1. The methods shown are compared with respect to the following features:
  2. A. whether they require a control sample (control) or whether they only use the ChIP sample (IP only)
  3. B. whether they take into account the (average) length of the reads/fragments and their orientation
  4. C. whether they take into account the different DNA strands or if they merge the reads, and whether the reads are shifted towards the 3' end
  5. D. whether an externally estimated mappability file is used
  6. E. how the scores, on which the classifications are based, are estimated
  7. F. whether/how any FDR or sensitivity/specificity estimates are calculated
  8. G. whether or not the method is applicable to both transcription factor (TF) and histone mark data.