In this section, we will explain how to start your journey with UniApp. In the first step, the data and metadata of your experiment should be uploaded from your device by clicking on Upload dataset.
This will bring you to a wizard that helps you to upload and annotate your dataset
1 Dataset name
In the first step, you have to provide your dataset name. You can choose any name, but it is a good practice to have a unique and informative name.
2Creating a new experiment and data upload - Analysis technology
In the second step, the technology used to generate the experiment's data must be stated.
In case you are uploading data that needs to be processed by our consulting team, select 'Upload to Unicle consulting'.
3 Upload data matrices
The data matrix and metadata need to be uploaded in the second column. If you upload data to our consulting team, please upload one compressed/zipped file as this will decrease upload time.
How to compress files on your computer: select all files that you would like to upload, right click for the context menu and select 'Compressed (zipped) folder). This will create a compressed folder with all your selected files. Alternatively, you can use software such as https://www.7-zip.org/ .
For all other uploads you have to upload exactly two files: data matrix and metadata. But first, ensure that your data matrix and metadata are formatted correctly.
3.1 Data matrix format
The data matrix must be in the following form:
Feature | Observation 1 | Observation 2 | Observation 3 | Observation 4 |
---|---|---|---|---|
Feature 1 | 0 | 2 | 0 | 56 |
Feature 2 | 20 | 12 | 20 | 0 |
Feature 3 | 0 | 25 | 31 | 15 |
Feature 4 | 7 | 32 | 7 | 40 |
Feature 5 | 6 | 0 | 6 | 0 |
Feature 6 | 7 | 0 | 7 | 17 |
The features and observations should be unique (if there are duplicates, UniApp will take care of that, but it is not recommended to have duplicated names). Empty and missing values are not allowed but for metabolomics and proteomics and in this case they should be indicated with: NA. The data must be uploaded as a .csv or a .txt file. Any other formats are not supported. The first column of the data is dedicated to the feature IDs, while all the other columns are dedicated to the expression/abundance of each feature in each sample. The features can be your genes, metabolites, or protein IDs (or names), while the observations are your sample names or cell names.
The expression/abundance of each feature must be in plain numeric format (using the scientific notation is not allowed).
3.2 Metadata format
The metadata should be in the following form:
Observation | Condition | Batch |
---|---|---|
Observation 1 | Control | 1 |
Observation 2 | Control | 2 |
Observation 3 | Treatment | 1 |
Observation 4 | Treatment | 2 |
As for the data, the metadata can be uploaded as a CSV or a TXT file. Any other formats are not supported (like the Excel format or raw data files). In case of the example presented above only the Condition and Batch columns are present however, your metadata can have many columns (e.g. clinical data). The first column of the metadata is dedicated to the observation names, while all the other columns are dedicated to any relevant information associated with the observations (groups, progress-free survival, clusters, etc.). The more columns containing relevant information, the better.
Check if your data and metadata match before uploading.
The observation names in the metadata must match with the observation names in the data file. If the observations do not match, the data file will be used as the ground truth to generate a metadata file that is consistent with the data. These means that observations that are in the metadata but not in the data will be removed, and observations that are in the data but not in the metadata will be added (with empty entries).
After you have selected your data matrices, click upload files.
When working with large files, making a compressed/zipped csv or txt (.csv.zip/.txt.zip) file for upload will result in shorter uploading times.
4. Creating a new experiment and data upload - Annotate your files
Once you have annotated your file click on the "Proceed to data staging" button. This will take you to the data staging page where you can annotate your data matrix and finalize your data upload.
For information on data staging, see Data staging.
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