wPGSA

Estimate relative activities of transcriptional regulators from transcriptome data by weighted Parametric Gene Set Analysis: wPGSA.

Upload your transcriptome data to run wPGSA

It takes a few minutes or longer depend on your data size.

About input data format

Log fold change data should be prepared in an ASCII tab delimited text file. It is organized as follows.

To create and edit the log fold change file, use a text editor or Excel. When you use Excel, be aware of a problem as described in Zeeberg et al 2004 .

dataformat

The first line contains the identifiers for each sample in the dataset.

Line format:
Gene Symbol(tab)(sample1 name)(tab)(sample2 name)(tab) … (sampleN name)
Example:
Gene Symbol(tab)K_Virus_0(tab)K_Virus_3(tab) … K_Virus_D7

The remainder of the lines contains log fold change (LFC) data for each of the genes.

Line format:
(gene name)(tab)(LFC of sample1)(tab)(LFC of sample2)(tab) … (LFC of sampleN)
Example:
Plekhg2(tab)-0.092(tab)0.170(tab) … 0.047

Change Log

10 October 2016
Fixed a bug in analysing data containing +/- inf
6 October 2016
Fixed a bug in analysing data containing NA
10 August 2016
Fixed a bug in uploading data from only one sample.
5 April 2016
Implemented table view. Bug report is welcome, please send your problem or thoughts via GitHub issue!
3 March 2016
Added input data format description
29 February 2016
Publish data download page
4 February 2016
Launch website, upload data to run wPGSA, heatmap view

Future Work

  • Faster execution of wPGSA
  • Heatmap view threshold feature (currently whole result data only)
  • Documentation of algorithm

Contributors

wPGSA is being developed by the Laboratory for Disease Systems Modeling at the RIKEN-IMS and Database Center for Life Science . This work was supported by JSPS KAKENHI Grant Number 15K21631 and 15KT0147.

Citation

  • Kawakami, E., Nakaoka, S., Ohta, T., & Kitano, H. (2016). Weighted enrichment method for prediction of transcription regulators from transcriptome and global chromatin immunoprecipitation data. Nucleic acids research, gkw355. doi.org/10.1093/nar/gkw355