YeastPhenome.org is a collaborative project that aims at constructing a comprehensive compendium of systematic phenotypic data for budding yeast Saccharomyces cerevisiae.

Our goal is to collect, process and share in a standardized format the results of all genome-scale experiments that have examined the yeast deletion collection for any given phenotype under any given experimental condition.

In order to be included in the compendium, a study must meet all of the following criteria:

  1. use any current or past version of the Mat-a, Mat-alpha, homozygous diploid or heterozygous diploid deletion collection
  2. test at least 1,000 mutants
  3. record a quantitative (continuous) or qualitative (binary, discrete, categorical) phenotype (or the lack thereof) for all mutants
  4. report data on all of the tested mutants or just the most extreme/significant hits (studies that report an arbitrary subset of the hits based on biological interest are excluded)
  5. be described in a Pubmed-indexed journal article

Our primary source of data are the supplementary materials of the relevant publications. On top of that, many authors have contributed more complete and previously unpublished versions of their datasets (e.g., raw quantitative values from which the published hit list was derived). These datasets are explicitly flagged to emphasize their special status.

The individual datasets are available for download as soon as they are curated (e.g., see the green "Download all data" button for Bleackley MR~MacGillivray RT, 2011). The full compendium of all datasets will be accessible later on, as soon as we finalize the standardized nomenclature of phenotypes and experimental conditions.

Yeastphenome.org was created and is being maintained by:

  • Anastasia Baryshnikova (principal investigator, www.baryshnikova-lab.org)
  • Rose Oughtred (literature curator)
  • Christie Chang (literature curator)
  • Jennifer Rust (literature curator)
  • Brianna Richardson (curator, programmer)
  • Sven Heinicke (database and website support)
  • Fan Kang (database support)
  • Mark Schroeder (server support)

Data usage and citation policy

If you use yeast phenome data in a talk or a manuscript, please acknowledge the data source by citing the original publication from which the data is derived, as well as the yeast phenome database. The database should be cited as follows:

— The Yeast Phenome Database, www.yeastphenome.org, accessed on XXXX-XX-XX.

Current stats

Updated automatically on Nov. 3, 2020.

  • Total publications: 450 (+ 33 for which data could not be recovered)
  • Total labs who published papers: 328
  • Data loaded for:
    • Publications: 428 (95%)
    • Phenotypes: 6,723
    • Environments: 5,197
    • Datasets: 16,006
  • Recovered unpublished information for:
    • Datasets: 344 (2% of all)
    • More complete data: 180 datasets (36% of those that needed it)
    • List of tested strains: 333 datasets (52% of those that needed it)
Strain background Number of datasets
Haploid Mat-a 920 (6%)
Haploid Mat-alpha 6,221 (39%)
Homozygous diploid 4,457 (28%)
Heterozygous diploid 4,391 (27%)
Mixed 17 (0%)
Total 16,006 (100%)
Data type Number of datasets
Quantitative 15,352 (96%)
Quantitative only for hits 254 (2%)
Discrete 400 (2%)
Total 16,006 (100%)
Condition type Number of papers Number of datasets
temperature 30 106 (49 q + 3 qofh + 54 d)
MMS 18 28 (21 q + 4 qofh + 3 d)
sodium chloride 17 58 (48 q + 1 qofh + 9 d)
HU 14 32 (25 q + 2 qofh + 5 d)
ethanol 13 17 (4 q + 1 qofh + 12 d)
rapamycin 12 34 (29 q + 0 qofh + 5 d)
tunicamycin 12 20 (15 q + 1 qofh + 4 d)
hydrogen peroxide 12 21 (17 q + 1 qofh + 3 d)
cycloheximide 11 18 (13 q + 1 qofh + 4 d)
camptothecin 11 21 (18 q + 2 qofh + 1 d)
Phenotype class Number of datasets (hap/hom) Number of papers (hap/hom) Number of datasets (het) Number of papers (het)
Growth 4,824 (42%) 283 4,372 (100%) 44
Expression 6,125 (53%) 6 0 (0%) 0
Other 663 (6%) 131 19 (0%) 6

Frequenty Asked Questions (FAQ)

Why is the drug name on this dataset different from the drug name in the paper?

What you see on this website is the ChEBI or the PubChem name of the drugs. Whenever possible, we associate chemical compounds with a ChEBI ID (preferentially) or a PubChem ID (if ChEBI ID was not available) and display, by default, their ChEBI or PubChem names, respectively. This sometimes results in an unusual name (e.g., the ChEBI name of rapamycin is sirolimus), but it greatly facilitates the consistency of the data. The original drug names (those used in the paper) are still available through search and will soon be displayed on the condition page.