gaia-package: GAIA: An R package for genomic analysis of significant...

In gaia: GAIA: An R package for genomic analysis of significant chromosomal aberrations.

Description

GAIA (Genomic Analysis of Important Aberrations) allows to assess the statistical significance of chromosomal aberrations. A permutation test is used to compute the probability distribution of the normal case (no significant aberrations are present in the data) so that we can estimate the statistical significance of the observed data. In order to correct for multiple hypothesis testing the False Discovery Rate approach proposed by Storey et al. (2004) is used. Finally an iterative "peel-off" procedure is used to identify the most significant independent regions.

GAIA is described in Morganella et al. (2011).

Details

Package:	gaia
Type:	Package
Version:	1.0.1
Date:	2010-09-13
License:	GNU GPL
LazyLoad:	yes

Author(s)

Sandro Morganella et al.

Maintainer: S. Morganella <[e-mail]>

References

Morganella S. et al. (2011). Finding recurrent copy number alterations preserving within-sample homogeneity. Bioinformatics. DOI: 10.1093/bioinformatics/btr488.

Storey JD. et al. (2004). Strong control, conservative point estimation, and simultaneous conservative consistency of false discovery rates: A unified approach. Journal of the Royal Statistical Society. 66:187-205.

Examples

# Load the matrix containing the informations about the markers
data(synthMarkers_Matrix)

# Use the function load_markers to obtain the marker descriptor data object
markers_obj <- load_markers(synthMarkers_Matrix)

# Load the matrix containing the informations about the aberrant regions
data(synthCNV_Matrix)

# Use the function load_cnv to obtain the aberrant region descriptor data object
cnv_obj <- load_cnv(synthCNV_Matrix, markers_obj, 10)

# run GAIA algorithm and save the results within the file "results.txt"
runGAIA(cnv_obj, markers_obj, "results.txt")

Example output

Loading Marker Informations
........................
Done
Loading Copy Number Data
........................................................................
Done

Performing Data Preprocessing

Homogeneous cannot be applied on the data (data must contain exactly two different kinds of aberrations)


Done
Computing Probability Distribution
................................................................................................................................................
Done
Assessing the Significance of Observed Data
........................................................................
Done
Running Standard peel-off Algorithm With Significance Threshold of 0.25
........................................................................
Done

Writing Output File 'results.txt' Containing the Significant Regions

File 'results.txt' Saved

   Chromosome Aberration Kind Region Start [bp] Region End [bp]
1  "1"        "0"             "301"             "700"          
2  "2"        "0"             "301"             "700"          
3  "3"        "0"             "301"             "700"          
4  "4"        "0"             "301"             "700"          
5  "10"       "1"             "1"               "700"          
6  "11"       "1"             "1"               "700"          
7  "12"       "1"             "1"               "700"          
8  "20"       "2"             "801"             "1000"         
9  "21"       "2"             "801"             "1000"         
10 "22"       "2"             "801"             "1000"         
11 "23"       "2"             "801"             "1000"         
12 "24"       "2"             "801"             "1000"         
   Region Size [bp] q-value             
1  "400"            "0.00025"           
2  "400"            "0.00125"           
3  "400"            "0.00775"           
4  "400"            "0.06825"           
5  "700"            "0.0388571428571429"
6  "700"            "0.0791428571428571"
7  "700"            "0.158142857142857" 
8  "200"            "0"                 
9  "200"            "0"                 
10 "200"            "0"                 
11 "200"            "0.0055"            
12 "200"            "0.198"             

gaia documentation built on Nov. 8, 2020, 8:02 p.m.