FAQ
Where does the interaction data available for search and download on this web portal come from?
The interaction data comes from multiple sources. PPIs detected in systematic studies comes from Uetz library screens (Uetz et al, Nature 2000), Ito core (Ito et al, PNAS 2001) and two systematic screens performed in the Vidal lab at Dana-Farber Cancer Institute/Harvard Medical School, YI-I (Yu et al, Science 2008) and YI-II (data unpublished), and a multi-environment systematic screens performed in the Roth lab at University of Toronto, EYRI (data unpublished). YI-I and YI-II was generated via inhouse screens were performed using a systematic binary mapping pipeline based upon primary screens using a high-throughput yeast two-hybrid assay, followed by validation of the dataset using two or more orthogonal assays. EYRI was generated and verified via fluorescence Barcode Fusion Genetics - Yeast-Two Hybrid (fBFG-Y2H) technology, followed by validation of the dataset with an orthogonal assay in matching environments.
The remainder of the data comes from a curated set of interactions reported in the literature reported in the databases IntAct, BioGRID, DIP and MINT. This data was combined and filtered to identify the high-quality binary interactions as described in Rolland et al. Cell 2014 (http://www.cell.com/abstract/S0092-8674(14)01422-6).
Does the interaction data originate from experiments and/or predictions?
All of the systematic data come from systematic screening pipelines and have at least one piece of experimental data.
The literature curated dataset has been filtered to identify the high-quality binary set of interactions, and each interaction is required to have at least three pieces of experimental evidence in the original publications.
What are the apparently static and dynamic interactions?
PPIs that do not respond to environmental perturbations are static, and PPIs that do respond to environmental perturbations are dynamic. In systematic large-scale screens a simple approach for annotating PPI dynamicity is establishing number of environments that a given PPI is detected. Thus, in EYRI PPIs observable across all four environments are static, while PPIs detected in some but not all environments are dynamic. However, establishing careful quality controls over the past 15 years, we are now fully aware that in large-scale screens PPI may be lost due to sampling sampling sensitivity. We have devised High Saturation Retest scheme to verify our hits and achieve nearly 100% sampling sensitivity. However, effects of sampling sensitivity can be exacerbated for weakly-detectable PPIs scoring at the lower bound threshold of assay sensitivity. Thus, some truly static PPIs may still appear as dynamic merely because they are harder to detect and therefore more likely to “drop out” in at least in one environmental screen. Therefore, categorize interactions from our screens as “apparently dynamic” and “apparently static”, while reserving the “dynamic” and “static” for PPIs for which we can control detectibility either by using quantitative scores or an independent assay.
I have my query genes in a different identifier format (neither gene symbols nor Uniprot IDs). What can I do to still use them as query on this web portal?
Currently our portal can only be searched using either gene symbols or Uniprot identifiers but we are working on very much diversifying the set of allowed gene identifiers to search with. In the meantime, you can convert your list of query genes into gene symbols or Uniprot IDs at these website (http://www.uniprot.org/uploadlists/).
Why does my search not return any PPIs?
Even if most yeast genes have been screened in our binary interaction mapping pipeline, and also in published maps (a full list of the genes we have screened will be available soon), we may not have screened your gene of interest yet because we don’t currently have an ORF clone available for this gene.
The other possibility is that even though we have screened for PPIs with an ORF of your gene of interest, this ORF may not have resulted in any PPIs. While our binary interaction mapping pipeline is designed to be systematic and unbiased, there are some proteins which may prove to be refractory to the assays used. For example, (i) proteins that are secreted or require significant post-translational modification may not form stable interactions under our assay conditions, or (ii) some proteins may only interact as parts of large complexes and not as binary pairs.
In which format do I need to save the search results for upload into Cytoscape?
To upload the search results into Cytoscape, export them as a .csv file.
Can I use your unpublished interaction data in my publication?
Yes, there are no restrictions on using small numbers of our unpublished interactions in your publications. We have a narrow 12 month moratorium on the publication of global analyses on the full unpublished dataset. For more details please see the Guidelines on the use of preliminary data (Download Page)
How should I cite the web portal?
A manuscript to describe the web portal is in preparation. Please, check back for updates. To cite the interaction data, please, see below.
How should I cite the published interaction data?
If you use published interaction data please cite the relevant publication (Documentation).
How should I cite the unpublished interaction data?
Users are expected to acknowledge the following in all oral or written presentations, disclosures, or publications of the analyses:
The Center for Cancer Systems Biology (CCSB) at the Dana-Farber Cancer Institute
The funding organization(s) that supported the work:
(1) The National Human Genome Research Institute (NHGRI) of NIH
How can I get information on the clone used to identify an interaction returned from my search?
The clones used in our screens come from the ORFeome clone collection assembled at CCSB. Details on the cloning strategy, the source material and the nucleotide sequence of the clones are described in the manuscript. Part of our next update will be the possibility to obtain more detailed experimental information on every interaction displayed on the results page including the ORFs, fusion constructs, orientations, and Y2H assay versions used to detect this PPI.
Isn't yeast two-hybrid data full of false positives?
No! Like any other experimental approach, the quality of the data generated is dependent on the careful design of the experiment and rigorous attention to detail in performing the experiments. We have been developing our binary interaction mapping pipeline for over 15 years and established numerous quality control measures. All of our primary yeast two-hybrid datasets are validated by testing a subset of interactions in at least two orthogonal assays to ensure that the quality of the dataset is equal to, or greater than, a representative sample of interactions selected from the literature (Venkatesan et al)