mmgmos:
R package for gamma models for
oligonucleotide signal
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mmgmos:
R package for gamma models for
oligonucleotide signal
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mmgmos is an R package that estimates the expression levels and the confidence of measures for multiple arrays of the same type of Affymetrix GeneChips using the multi-chip modified gamma Model for Oligonucleotide Signal (multi-mgMOS) and the modified gamma Model for Oligonucleotide Signal (mgMOS). It is a part of PUMA project.
Affymetrix microarrays adopt multiple probes to measure the
abundance of transcription, so it is possible to apply various
statistical and probabilistic methods to provide confident gene
expression results. The most popular probe-level analysis methods are
statistic models which are able to calculate gene expression levels
accurately. However, these methods are incapable of providing the
credibility of the expression values that may be very useful for
further statistical analyses. mmgmos
is specifically designed to address this limitation.
There are two version of gMOS implemented in this package, modified
gMOS (mgMOS) and multi-chip modified gMOS (multi-mgMOS). The original
gMOS uses two gamma distributions to model Perfect Match intensities and
Mismatch intensities with shared scale parameters on each chip. The
mgMOS changes the scale parameters into latent variables to reflect
the different binding affinity of probes within the probe-set. This
modified distribution accurately captures the correlated changes in
the binding affinity of probe-pairs within the probe-set. Both gMOS and
mgMOS are single chip models. The multi-mgMOS is an extended version of
gMOS and mgMOS. It shares the scale parameters in gamma distributions
across all chips to reflect the intrinsic characteristic of probe
sequences of the same type of chip. It also allows for a fraction of
true
signal binding to Mismatch probe. The likelihood function of all
versions of gMOS can be written in closed form and the computation is
therefore very fast compared with other probabilistic models.
The package mmgmos implements mgMOS in function mgmos and multi-mgMOS in function mmgmos. The fast C program donlp2 is used to optimist parameters. Both mgmos and mmgmos functions output the mean, median, standard deviation, 5%, 25%, 75% and 95% credibility intervals of the expression level for each gene.
| Version |
Linux
add-on package |
Windows
add-on package |
R version requirement |
Description |
| 1.5.1 |
mmgmos_1.5.1.tar.gz |
mmgmos_1.5.1.zip |
2.3.x |
Re-build for R 2.3.1 and modify to meet the new Affy import package affyio. The normalisation algorithms include mean centering on both raw and log scale, and median centering. |
| 1.3.3 |
mmgmos_1.3.3.tar.gz |
mmgmos_1.3.3.zip |
2.2.0 |
Adding a global scaling normalisation option. |
| 1.3.2 |
mmgmos_1.3.2.tar.gz |
mmgmos_1.3.2.zip |
2.2.0 |
Adding function justmmgMOS() and justmgMOS() to avoid the call of ReadAffy().
The new functions use memory more efficient and make process of large data sets possible. |
| 1.3.1 |
mmgmos_1.3.1.tar.gz |
mmgmos_1.3.1.zip |
2.2.0 |
Adding an option to save
parameters of mgMOS in mgmos. |
| 1.3.0 |
mmgmos_1.3.0.tar.gz |
mmgmos_1.3.0.zip |
2.2.0 |
When \phi is unknown, set it
zero. |
| 1.2.0 |
mmgmos_1.2.0.tar.gz |
mmgmos_1.2.0.zip |
2.2.0 |
Implementation as in
Bioinformatics 21: 3637-3644 |