RAD - Region Associated DEG : Identify Region Associated Differentially Expressed Genes
Welcome!

Region Associated DEG (RAD) is a tool to find region associated differentially expressed genes.

The algorithm behind RAD has been implemented in recent publications (Liu et al., Nat. Commun., 2021. ; Pastor, W.A. et al., Nat. Cell Biol., 2018; Harris, C.J. et al., Science, 2018; Gallego-Bartolomé, J. et al., Cell, 2019).

See supported format for upload in the example.


News
  • Feb. 2, 2021:RAD: a web application to identify region associated differentially expressed genes was published online on Bioinformatics.

  • Jan. 28, 2021:The associated paper "RAD: a web application to identify region associated differentially expressed genes" was accepted by Bioinformatics.

  • Dec. 30, 2020: RAD v1.2 is released. RAD now supports both hypergeometric or binomial test for statistical inference.

  • Oct. 24, 2020: RAD v1.1 is released. RAD now supports user-defined extended distance. We also update the illustrative diagram in the introduction.

  • Jul. 10, 2020: RAD v1.0 is launched.

Upload Data
DEGs List

Please upload your DEG data (either gene symbols or ENSEMBL ID)

Up-regulated genes:

Down-regulated genes:

Genomic Regions of Interest (gROI) File

Please upload your gROI file in Bed format:


For gROI input data, make sure that your data is tab separated.
Submit Options

Reference Genome

Please choose the reference genome you want to use

Peak Extended Distance

Please choose the distance you want to analyze (in bp):

Or customize the distance in comma separated format:

Statistical Test

Please choose the statistical test to be used

Color

Please choose a set of colors you want to use in the plot:

Title for PDF to Export

Please type in the title for pdf file to export:

Your email

Please type in your email (optional):

  Example Figure
 Example Data
  • p < 0.05: *; p < 0.01: **; p < 0.001: ***; p < 0.0001: ****
  • RAD_genename_distance.txt
  • RAD_genecount_pvalue.txt
  •    List of Publications Used RAD
    1. Liu, W., J. Gallego-Bartolomé, Y. Zou, Z. Zhong, M. Wang, S. P. Wongpalee, J. Gardiner, S. Feng, P. H. Kuo and S. E. Jacobsen., 2021. Ectopic targeting of CG DNA methylation in Arabidopsis with the bacterial SssI methyltransferase. Nature Communications 12(1): 3130. doi: 10.1038/s41467-021-23346-y
    2. Pastor, W.A., Liu, W., Chen, D., Ho, J., Kim, R., Hunt, T.J., Lukianchikov, A., Liu, X., Polo, J.M., Jacobsen, S.E. & Clark, A.T. (2018) TFAP2C regulates transcription in human naive pluripotency by opening enhancers. Nature cell biology, 20, 553-564. doi: 10.1038/s41556-018-0089-0
    3. Harris, C.J., Scheibe, M., Wongpalee, S.P., Liu, W., Cornett, E.M., Vaughan, R.M., Li, X., Chen, W., Xue, Y., Zhong, Z., Yen, L., Barshop, W.D., Rayatpisheh, S., Gallego-Bartolome, J., Groth, M., Wang, Z., Wohlschlegel, J.A., Du, J., Rothbart, S.B., Butter, F. & Jacobsen, S.E. (2018) A DNA methylation reader complex that enhances gene transcription. Science, 362, 1182-1186. doi: 10.1126/science.aar7854
    4. Gallego-Bartolomé, J., Liu, W., Kuo, P.H., Feng, S., Ghoshal, B., Gardiner, J., Zhao, J.M., Park, S.Y., Chory, J. & Jacobsen, S.E. (2019) Co-targeting RNA Polymerases IV and V Promotes Efficient De Novo DNA Methylation in Arabidopsis. Cell, 176, 1068-1082.e19. doi: 10.1016/j.cell.2019.01.029