Select any dataset from the Transcriptome, Metabolome, Proteome or Acetylome dropdowns. Datasets are added to the dropdown menu title "Selected Datasets". Clicking the yellow dataset name will display information about the dataset including the citation, species, omic type, and any others datasets included in the study in a pop-up window. Remove a dataset by selecting the red "X" button. All queries will be run against all the datasets that are currently selected
Further details for each dataset are included on the Dataset page. This can be accessed from any location by clicking on the "Datasets" button in the navigation bar on the upper left of the page. There are four separate tabs for each omic type. Details include a brief description, species, tissue type, experimental condition, GEO accession, experiment type, a link to the original publication, and timepoints. Keyword search can be performed on any category for available information.
Type the name of a species for the omic type in the main search bar.
Clicking "Display" will show trends for the current query in the currently selected datasets. Clicking "Clear" will clear the main display and statistics table and remove all previous queries.
Adding multiple datasets to the "Selected Datasets" dropdown allows the user to perform a query for a given species on several datasets at once. Any combination of datasets can be added to the current "Selected Datasets" list. See Selecting Datasets for more information on using the dropdown menus.
To query multiple species against the currently selected datasets at once, separate each species symbol by a semi-colon.
Selecting the "Remove" option for a particular species / dataset trend will remove this result from the main display and the statistics table.
Toggling the "Normalization" between Off and On will update the main display between expression results provided in the public available datasets and the same values normalized between 0 and 1. This feature is useful when experiments have diverse reported expression values.
Toggling the "Software" tab between "BIO_CYCLE" and "JTK_CYCLE" will update the current display table with statistics produced from the respective software packages. For more information on these statistics, see Statistics.
The user can filter datasets by species, broad tissue classification (Liver, Muscle, Brain, etc.), and dataset experimental type (Control, Knock-Out, Knock-Down, Drug Treatment, etc.). Selecting the "Clear Filters" option at the very top of the filter menu removes all of the currently applied filters.
Adjusted p-value as reported from BIO_CYCLE or JTK_CYCLE. Generally, a p-value < 0.05 is considered statistically significant.
Benjamini-Hochbeg FDR as reported from BIO_CYCLE or JTK_CYCLE.
Amplitude of periodic signal from peak to trough.
Phase shift of periodic signal from sine function.
BIO_CYCLE can now search for statistically significant signals with any periods.
The current display image can be downloaded in PNG or SVG format by clicking the buttons within the query search bar.
The current table of statistics results can be downloaded in an excel compatible format by clicking the "Excel" button on the upper right side of the statistics table. The downloaded excel will be produced for the current selected "Software" toggle setting.
Users can upload data to the BIO_CYCLE web portal to produce the statistics described here. Results are generated for all included symbols in the user provided file at 3 period searches (8, 12, 24). The user can quickly view trends using these provided symbols under the "Visualization" tab. Distribution of the previously described statistics can be examined in histograms displayed under the "Histogram" tab.
File must be a tab separated file (*.tsv) with a single ID in the first column followed by the molecular concentrations at each timepoint. An example file format is provided in the link below. BIO_CYCLE can handle variable numbers of replicates, uneven timepoints, and missing replicates (as long as each row has at least one value per timepoint).
| ID | ZT_0_REP_1 | ZT_0_REP_2 | ZT_4_REP_1 | ZT_4_REP_2 |
|---|---|---|---|---|
| Per1 | 4.25 | 3.08 | 9.17 | 8.90 |
| Per2 | 3.45 | na | 9.50 | 9.93 |
| Per3 | 1.40 | 1.53 | 10.70 | 10.55 |
| Cry1 | 4.35 | 5.78 | 14.87 | 12.21 |
BIO_CYCLE is a Neural Network based approach which predicts rhythmicity in biological species. It is the default method used by CircadiOmics. For information on provided statistics and how to upload user data follow the links.
Raw single-cell RNA-seq data are annotated using the indicated atlas, and the resulting annotation files can be downloaded by clicking the atlas/annotation download buttons in the Single-Cell dataset table.
For datasets already annotated by the original study, we provide only the annotations and data as reported by the authors, which can be accessed through the same download buttons.
Annotation results and BIO_CYCLE-derived gene periodicity statistics can be explored interactively by choosing a dataset, viewing the corresponding UMAPs, selecting cell types and one or more genes, and examining the trajectories and statistics in the plots.
Annotation .tar.gz archives include annotated data in .h5ad format together with .png images showing UMAP representations of the annotations, all extracted when you unpack the archive.
BIO_CYCLE .tar.gz archives, downloaded from the Single-Cell dataset table, contain periodicity results computed for all cell types in the corresponding single-cell study.
Is currently being developed to examine metabolomic networks through identification of correlated trends in the metabolome datasets found inside CircadiOmics.
For further help, contact kchangiz@uci.edu