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Enrichr
Enrichr Demo
Enrichr Demo
Enrichr Demo
Enrichr Demo
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Enrichr Demo
Enrichr Demo
Enrichr Demo
Enrichr Demo
Enrichr Demo
Enrichr Demo
Enrichr Demo
Enrichr Demo
Enrichr Demo
Enrichr Demo
Enrichr Demo
Enrichr Demo
Enrichr Demo
Enrichr Demo
Enrichr Demo
Enrichr Demo
Enrichr Demo
Enrichr Demo
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Enrichr Demo
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Enrichr Demo

Editor's Notes

  1. Enrichr is a web-based gene list enrichment analysis tool that include gene sets libraries, an alternative way to rank enriched terms and various types of interactive visualization.
  2. In ‘Libraries’ tab we provide a list of libraries we’ve created and use for analysis and sources of these libraries. To download a library press the red icon in rightmost column.
  3. To find a gene of interest in these libraries you can use ‘Find a gene’ tab. Input name of gene or select it from the autocomplete list.
  4. Then you gene of interest will be shown in categories tree-view. In libraries you can view relationships between this gene and terms.
  5. Depending on your data format there’s three options. BED format, quantitative set and regular gene list. To process your BED data select ‘choose file’ and upload your file.
  6. In right field you can past quantitative gene set – set with weight for each gene in range from 0 to 1, where weight 0 discard the gene and 1 is maximum weight.
  7. Or you could past here regular list of genes. If you don’t have one you could past an example gene set.
  8. If you put a tick in checkbox ‘Contributed’ in the bottom left corner your list will be used in out crowdsourcing dataset.
  9. To continue you have to enter a description of contributed gene set and click on the red arrow in the bottom right corner.
  10. If you click on the sheet-shaped icon in the top right corner you can view list of submitted genes.
  11. If you click on the share icon in the top right corner you’ll get a link on your dataset to return to it later or send it to your colleagues.
  12. Libraries in Enrichr are divided into several categories with self-explanatory names.
  13. Libraries that are represented in ‘Legacy’ category are not relevant as we already have latest versions. We have them as we don’t want people to lose their data and we want to let them compare their results between old and new data and update them.
  14. Libraries form ‘Crowdsourcing’ category were created by crowd efforts.
  15. Let’s return to analysis. These bars are sorted by combined score in descending order. The more bright and long a bar is – the more score is. Combined score is our alternative score for ranking enriched terms and its value is equal to log (p) * z. You can sort bar graph by different score methods by clicking on it.
  16. Click the bars again and you’ll see them sorted by p-value which is computed using Fisher exact test
  17. And once again. Now the bars are sorted by their rank based score. It is z-score computed by assessing the deviation from the expected rank.
  18. If you click on the cog-shaped icon in the top right corner you can change the color scheme for bar graph, network and grid.
  19. Table view gives you explicit view for p-value, z-score and combined score. You could sort terms in ascending or descending order by clicking on a header of a column. Also you can filter results by specific term by searching it.
  20. Hover the pointer over name of term gives you a view list of genes that are associated with it.
  21. And if you want to download the whole result of analysis in tab-delimited format by clicking the link ‘Export entries to table’.
  22. In grid view all terms from a gene-set library are represented by squares on a grid which is organized based on the terms gene content similarity where an area of high similarity is made brighter. The grid can be clicked to set view where the enriched terms are highlighted with circles, colored from bright white to gray based on their p-values.
  23. Z-score and p-value shows how dense the top ten elements are clustered on the grid.
  24. In the network view top ten terms are displayed as a network where the nodes represent the enriched terms and the links represent the gene content similarity among the enriched terms.
  25. Logging in and clicking on your user name in the top right corner gives you a view on your previously uploaded gene sets. You can filter results for a particular sets by searching them. Clicking on the set name will return you to analysis.
  26. If you have any questions we provided the detailed tutorial and FAQ in Enrichr’s ‘Help’ tab.