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This is the beta version of PIIKA 2.5, featuring new quality control capabilities.

Click here for a tutorial/demonstration of the usage of PIIKA 2.5.
The sample files mentioned below correspond to the sample data mentioned in the paper describing PIIKA 2.

Click here for cleaning up raw files

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Step #1: Input files

(Required) Main input file
Contains the intensity values for your arrays.
Sample file
(Optional) Treatment-control combinations
Specifies the treatment-control combinations in your dataset.
Sample file
(Optional) Treatment-control combinations for P-value visualizations
Specifies the treatment-control combinations for P-value visualization files.
Sample file

Step #2: Required parameters

(Optional) If you are using a commercial off-the-shelf array, choose it here, and the number of technical replicates and the number of peptides will be automatically filled in. If you are using a custom array, ignore this option.
Number of technical replicates per unique peptide on the same array
Number of treatments
Number of unique peptides on the array
Number of inter-array replicates
Note: if you entered a value greater than 1 for this option, please use the button below to indicate whether the inter-array replicates represent biological replicates or technical replicates.

Step #3: Optional parameters

Background correction method
If you choose "None", instead of correcting for the background measurements, only the foreground measurements will be used (although the background measurements must still be provided).
Normalization method
Distance metric for hierarchical clustering
Linkage method for hierarchical clustering
Perform chi-square test?
***Note that the default choice for this option is now "no".***
Perform F-test?
Applies only if your dataset contains 2 or more biological replicates.
Perform biological subtraction before performing F-test?
Applies only if you are performing an F test.
Perform random tree analysis? (REMINDER: If you select this option, you must name your samples as described in the input guide (e.g., A-1, A-2, B-1, B-2, etc.). Also, please expect to wait a few hours for your job to finish if you select this option).
Note that to perform the random tree analysis, the number of inter-array replicates must be 1 (and thus the number of treatments must be equal to the number of arrays).

If you selected Yes for this option, please enter the number of random trees to generate (default = 2000).

Perform peptide subset analysis? (REMINDER: If you select this option, you must name your samples as described in the input guide (e.g., A-1, A-2, B-1, B-2, etc.). Also, please expect to wait a few hours for your job to finish if you select this option).
Note that to perform the peptide subset analysis, the number of inter-array replicates must be 1 (and thus the number of treatments must be equal to the number of arrays).

If you selected Yes for this option, please enter the number of random trees to generate for the random tree tests (default = 1000).

If you selected Yes for this option, please enter the maximum number of peptides to incude in a peptide subset. The smaller the number, the faster your job will complete (default = 50).

Value of alpha (false positive rate) for statistical significance testing
Estimated background probability that a peptide will be differentially phosphorylated

Step #4: E-mail address

(Required) Please enter your e-mail address here. Once your job is finished running, you will receive an e-mail with a link where you can download the results. Please note that your e-mail address may be saved for the purposes of tracking usage and of informing you of updates and bug fixes to PIIKA 2.5.


ATTENTION: If confirmation page is not displayed after clicking the "Submit" button then please reload the confirmation webpage.

Step #5: Submit!

Image credit: Flickr user wildxplorer.

Creative Commons LicensePIIKA 2 and PIIKA 2.5 are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. If you would like to use it for commercial purposes, please contact us.