|
Tilescope
|
Bioconductor†
|
TAS‡
|
MAT§
|
TileMap
|
---|
Implementation
|
Web
|
R packages
|
Standalone
|
Standalone
|
Standalone
|
Graphic user interface
|
√
|
×
|
√
|
×
|
×
|
Intended usage
| | | | | |
Transcription data
|
√
|
√
|
√
|
×
|
√
|
ChIP-chip data
|
√
|
√
|
×
|
√
|
√
|
Applicable array platform
| | | | | |
Affymetrix
|
√
|
√
|
√
|
√
|
√
|
NimbleGen
|
√
|
×
|
×
|
×
|
×
|
Data normalization
| | | | | |
Mean/median
|
√
|
~
|
√
|
/
|
×
|
Loess
|
√
|
~
|
×
|
/
|
×
|
Quantile
|
√
|
~
|
×
|
/
|
√
|
Feature identification
| | | | | |
Max gap and min run
|
√
|
~
|
√
|
/
|
√
|
Iterative peak identification
|
√ (new)
|
×
|
×
|
/
|
×
|
Hidden Markov model
|
√
|
~
|
×
|
/
|
√
|
- *Only programs explicitly applicable to high-density tiling microarray data were considered. The websites of the compared programs are listed as follows: Tilescope at [35]; Bioconductor at [37]; TAS at [38]; MAT at [39]; TileMap at [40]. †Strictly speaking, Bioconductor is not a ready-to-run program. It is a collection of software packages/libraries written in R. As a tool box, the analysis methods that it provides need to be written in an R program to run. ‡TAS is previously known as GTRANS. §MAT standardizes the probe value through the probe model, which obviates the need for sample normalization. Comparison symbols used in the table: √, available; ×, not available; ~, available but need to be programmed; /, not applicable.