ContextTRAP

You can analyze two types of data.
1. Gene expression data

The significance of pathway is calculated by Time-series RNA-seq Aalysis Package (TRAP).
The relevance of pathway is calculated by Biomedical Entity Search Tool (BEST).

2. Pathway p-value data

TRAP is time-consuming algorithm.
So, if you already analyzed gene expression data, you can integrate the results, pathway p-value data, with the relevance derived by BEST.
Also, you can prioritize result of any pathway analysis methods, using context information.

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Gene expression
Pathway p-value

1. Email address

2. Select keywords representing the context of data.

Select

Sorry, No results found.

Result

3. File for gene expression

4. Select a species

5. Number of time points

6. Number of replicates

7. Cutoff value for DEGs

8. Time-lag factor

3. File for pathway p-value

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Enter your email address.

We will send the link of result via email.

To calculate the relevance of a pathway and a context, Keywords representing the context are required.
1. Search

Keyword should be one of entries of BEST.
Select a category of the context.
Search keywords and find keyword associated to the context in Select Tab.

2. Select

From searching result, select keywords that have strong association with the context.
You can add various keywords from multiple categories.

3. Result

It shows the selected keywords.
You can remove some keywords from the selected.

Finally, the keywords in Result Tab are used for calculating the relevance of pathways.

File should follow the rules below:

Tab-delimited file.
First column is a pathway name.
Second column is a p-value of the pathway, deriving from any pathway analysis.
Without header.

For example,

Pathway p-value

Apoptosis 0.003
TNF signaling pathway 0.019
PI3K-Akt signaling pathway 0.211

File should follow the rules below:

Tab-delimited file.
First column is a gene name.
Gene name should be Entrez ID or gene name found in the second column of http://rest.kegg.jp/list/*** where *** is an organism code in KEGG database.
From the second column, first M*N columns are expression values of control samples (M replicates, N time points) and next M*N columns are of treatment samples (M replicates, N time points).
Control/Treatment samples should follow ascending order of time.
Without header.

If there are 2 replicates(R) for 2 timepoints(T) of Control(c)/Treatment(t) samples,

Gene c_T1_R1 c_T1_R2 c_T2_R1 c_T2_R2 t_T1_R1 t_T1_R2 ...

BRCA1 1.1 1.5 4.5 5.5 1.1 2.3 ...
BRCA2 3.3 4.5 10.1 9.9 3.1 6.2 ...

*It is parameter for TRAP. For more information, visit http://epigenomics.snu.ac.kr/TRAP

Select a species existing in KEGG database.
*It is parameter for TRAP. For more information, visit http://epigenomics.snu.ac.kr/TRAP

Enter the number of time points of data.

The number of time points should be equal for control and treatment.

*It is parameter for TRAP. For more information, visit
http://epigenomics.snu.ac.kr/TRAP

Enter the number of sample replicates.

The number of replicates should be equal for control and treatment.
Also, it should be equal for each time point.

*It is parameter for TRAP. For more information, visit http://epigenomics.snu.ac.kr/TRAP

When finding DEGs by fold-change, TRAP uses user-defined cutoff value.

The cutoff value should be greater than or equal to 0.
TRAP calculates fold-change as logarithm of (exp_treatment/exp_control) with base 2.

*It is parameter for TRAP. For more information, visit http://epigenomics.snu.ac.kr/TRAP

Time-lag factor determines how much influence is made from pervious or current time point.

It is value for [0, 1].
If time-lag factor is 1, the interaction is only made between previous upstream genes and current downstream gene in the pathway.
If time-lag factor is 0.5, downstream genes are affected by previous and current upstream genes at the same degree.

*It is parameter for TRAP. For more information, visit http://epigenomics.snu.ac.kr/TRAP