The modules for CRE
feature and promoter state analysis have been desgined to run in
combination AtREA CRE distribution module. While the AtREA CRE
distribution
module can analyse multiple functional classes and
microarray slides in a single run(batch mode) the CRE features and
states modules have been targetted to compare the features and states
in a single class only. The results obtained by using these two
modules for a single class, can however, be incorporated into the CRE
distribution module inputs which enable them to be analysed in batch
mode also. Table 1 shows how the single classes that can be used for
feature analysis should be selected from CRE distribution analysis
module and also how the results obtained from feature analysis
can again be incorporated into the CRE distribution analsis module (the
last column) .
The promoter state
analysis module have been desgined to run in
combination AtREA CRE distribution module. While the AtREA CRE
distribution
module can analyse multiple functional classes and
microarray slides in a single run(batch mode) the promoter state
analysis modules have been targetted to compare promoter states
in a single class only. The results obtained by using this
modules for a single class, can however, be incorporated into the CRE
distribution module inputs which enable them to be analysed in batch
mode also. Table 2
shows
how the single classes that can be used for state analysis should be
selected from CRE distribution analysis module and also how the
results obtained from state analysis can again be incorporated into the
CRE distribution analsis module (the last column) .
Outcome |
Outcome | |||||
Input CRE (Single consensus format) |
Distribution
analysis
------------------->
|
Identify putative
functional tagerts among GO, MIPS ,ARACYC pathway classes. |
Select
conditions or classes where the CRE shows high enrichment of the CRE |
CRE
Feature analysis
-----------------> |
if
positon preference detected |
select
position window in which the CRE shows maximum enrichment |
if
strand preference detected |
select strand in which CRE shows maximum enrichment | |||||
Identify conditions (
from microarray slide) where the CRE may be signifincat in expression
regulation |
if CRE frequency effects gene expression. | Select
a minimum frequency |
||||
if any of the variants shows significantly highenrichment | Incorporate the variations in original CRE
sequence |
|||||
<---------------------------------------------------------------------------------------------------------------------------------<
Change parameters (input CRE, Sequence
features and minimum freqeuncy) and perform CRE distribution analysis
|
Table 1. Relationship
between CRE distribution and CRE feature analysis modules
Outcome |
Outcome | |||||
Input CRE (Single consensus format) |
Distribution
analysis
------------------->
|
Identify putative
functional tagerts among GO, MIPS ,ARACYC pathway classes. |
Select
conditions or classes where the CRE shows high enrichment of the CRE |
CRE
State analysis
-----------------> Select one or more CREs from literature, experimental or computaional analysis known to function in association with the input CRE |
If expression of genes which contain a second
CRE along with the input CRE (CRE combination) differ from the
expression of genes which contain only the input CRE |
Select the CRE combination |
Identify conditions (
from microarray slide) where the CRE may be signifincat in expression
regulation |
||||||
<---------------------------------------------------------------------------------------------------------------------------------<
perform CRE distribution analysis with
multiple CRE option with the combination as input
|