This page last changed on January 28, 2016 by peterk.

The page provides download links to an R package for processing ChIP-seq data. The rational behind most of the methods is described in the following paper: Kharchenko PK, Tolstorukov MY, Park PJ "Design and analysis of ChIP-seq experiments for DNA-binding proteins" Nat. Biotech. doi:10.1038/nbt.1508

Releases and updates
version 1.13

Download. SPP is now on Github!

version 1.11

Download. Changes: several bug fixes (relative filenames, datasets with data missing for some of the chromosomes).

version 1.10

Download. Changes: added support for BAM files, scaling by the dataset size in the smoothed tag density, a new method for calculating smoothed estimates for enrichment ratios; made R 2.12 compatible.

version 1.8

Download. Changes: added support for Eland's multi format, full arachne format, helicos tab-delimited alignment output, fixed maq readin, build library requirements.

version 1.7

Download. Changes: fixed a step filtering problem with get.mser.interpolation (thanks to Joe Luquette), fixed remove.tag.anomalies flag in get.binding.characteristics which wasn't being checked.

version 1.6

Download. Changes: Changed header files to accommodate newer GCC versions; Fixed a big in

version 1.5

Download. Changes: Added support for the extended Eland format (extended=T option for read.eland.tags).

version 1.4

Download. Changes: Added support for bowtie output, basic routines for broader regions of enrichment.

version 1.3

Download. Changes: fixed topN threshold is used together with background anomaly subtraction.

version 1.2

Download. Changes: added ability to read in MAQ alignments, skip binding.characteristics calculations for select.informative.tag call, improved effective dataset size estimation.

version 1.1

Download. Change: capped reported FDR estimates for peaks taller than any control peaks at the lowest FDR reached by the dataset

version 1.0

Initial package release. Download Unix version.


  • Assess overall DNA-binding signals in the data and select appropriate quality of tag alignment.
  • Discard or restrict positions with abnormally high number of tags.
  • Calculate genome-wide profiles of smoothed tag density and save them in WIG files for viewing in other browsers.
  • Calculate genome-wide profiles providing conservative statistical estimates of fold enrichment ratios along the genome. These can be exported for browser viewing, or thresholded to determine regions of significant enrichment/depletion.
  • Determine statistically significant point binding positions
  • Assess whether the set of point binding positions detected at a current sequencing depth meets saturation criteria, and if does not, estimate what sequencing depth would be required to do so.

Installation instructions

  • You can use modtools to install SPP:
  • require(devtools)
    devtools::install_github('hms-dbmi/spp', build_vignettes = FALSE)
  • Alternatively, download a .tar.gz containing the latest release and use the standard R installation command, e.g.:
  • R CMD INSTALL spp_1.13.tar.gz

Brief Tutorial

A brief tutorial showing use of the main methods can be found here.

Document generated by Confluence on June 20, 2012 09:48