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and just click the tabs for some magic!

3. Verify guessed species. Change if neccessary.

Send an email to help make sure iDEP continue to exist. We are writing a grant proposal (due June 5th) to NIH to seek support for the development and maintenance of iDEP. A brief email on how this tool helped your research would go a long way to support our tiny team, even if you are a graduate student. Email

New v0.70 iDEP generates R and R Markdown codes for users to run in stand-alone!
R Markdown example.
New v0.68! Try the STRING-db API access on the DEG2 page that offer protein interaction networks and GO enrichment for thousands species, including bacteria.
Integrated Differential Expression and Pathway analysis (iDEP) of transcriptomic data. See documentation and manuscript. Based on annotation of 163 animal and 45 plant genomes in Ensembl BioMart as of 12/15/2017. STRING-db offer API access to protein interaction networks and annotations for 115 archaeal, 1678 bacterial, and 238 eukaryotic species. Additional data from KEGG, Reactome, MSigDB (human), GSKB (mouse) and araPath (arabidopsis). For feedbacks or data contributions (genes and GO mapping of any species), please contact us, or visit our homepage. Send us suggestions or any error message to help improve iDEP. Email

Loading R packages ... ...

Only keep genes above this level in at least n samples:
Keep genes with minimal counts per million (CPM) in at least n libraries:
Pseudo count c:

Processed data

Aspect ratios of figures can be adjusted by changing the width of browser window.

Customize hierarchical clustering (Default values work well):
Cut-off Z score
Heatmap data High-resolution figure

K-means data High-resolution figure
Pathway database
Enrichment details

Enriched pathways for each cluster

Coordinates High-resolution figure

Identifying Differential Expressed Genes (DEGs). See next tab for details.
Using the limma package


Numbers of differentially expressed genes for all comparisons. "B-A" means B vs. A. Interaction terms starts with "I:"

Examine the results of DEGs for each comparison

Gene list & data High-resolution figure
Enrichment analysis for DEGs:
Enrichment details
Also try ShinyGO

Enriched pathways in DEGs for the selected comparison:

Top Genes for selected comparison:

Pathway list w/ genes
* Warning! The many combinations can lead to false positives in pathway analyses.
Red and blue indicates activated and suppressed pathways, respectively.
Red and blue indicates activated and suppressed pathways, respectively.
Red and green represent up- and down-regulated genes, respectively.
This interactive map shows DEGs on the genome. Red and blue dots represent up- or down-regulated genes, respectively. Mouse over to see gene symbols. Click and drag to zoom in.

To identify genomic regions significatly enriched with up- or down-regulated genes, we can use PREDA. Very slow (5 mins), but may be useful in studying cancer or other diseases that might involve chromosomal gain or loss.
Biclustering can discover genes correlated on subset of samples. Only useful when sample size is large(>10). Uses methods implemented in the biclust R package.
Enrichment database
Download all biclusters


Enriched gene sets in selected bicluster

Genes in this cluster

Identify co-expression networks and sub-modules using WGCNA. Only useful when sample size is large(>15).

Enrichment database:
Download all modules Download network for selected module
The network file can be imported to VisANT or Cytoscape.

Enriched pathways among all genes in selected module

Email us for questions, suggestions, or data contributions. Stay connected via user group or Twitter .

R as in Reproducibility

To improve reproducibility, iDEP generates custom R code based on your data and choices of parameters. Users with some R coding experience should be able to re-run most analyses by downloading all of the files below. If Ensembl IDs is not used in users' original file, we should use the converted data file. Click through all the tabs and then download all these file to a folder. Run the Customized R code or the Markdown file. R Markdown example.
Customized R code Customized R code(Markdown) iDEP core functions Gene Info file Pathway file (large)


iDEP v0.62 2/5/2018: Add tree and networks to visualize overlaps between enriched gene sets, in K-means, DEG2, and pathway tags. Downloads of pathway analysis results and high-resolution figures.
2/6/2018: Fixed errors caused by gene symbol matching for unknown species. More user control of hierarchical clustering tree
2/9/2018: V 0.65 Added API access to STRINGdb website on the DEG2 tab. Supports thousands of bacterial species
2/10/2018: V 0.66 Improved API access to STRINGdb, by adding automatic species matching.
2/11/2018: V 0.67 Tested with larger dataset of 259 samples. Changed figure configurations.
2/14/2018: V 0.68 Fixed Pathview loading code. Connected Pathview to PGSEA.
2/25/2018: V 0.68 Fixed Fold-change, FDR data upload and parsing. Figure resolution using the res=150 option help improve readability of labels.
2/28/2018: V0.69 Change interactive heat maps to re-order columns
3/12/2018: V0.70 Generating R code and downloading annotation files used in analysis.
3/14/2018: V0.71 Improve R markdown file; add color to EDA plots; detect bias in sequencing depth
3/18/2018: v0.711 Fixed error caused by gene names containing characters such as ' or "
3/28/2018: v0.712 Fine tuned EDA plots
4/3/2018: V0.713 add permutations for fgsea. Expand quotes.
4/13/2018: V0.72 fixed bug caused error in R Markdown file when users choose species other than the default.
4/25/2018: V0.73 Fixed bug for GO terms tree in k-Means. Added layout button for network viz of GO terms
5/28/2018: V0.73 Enabled download of all FDR and fold-changes at the DEG1 tab.

In loving memory of my parents.