The Experiment design module is the first module you will encounter after data upload. In this module you will annotate your data matrix if needed in the Algorithm box. Once this module is completed you will be able to edit the metadata in the next step
Completing Experiment design is necessary for all downstream analyses. You can complete it once at the begining of your experiment or you can come back anytime to annotate your data matrix.
1. Data set annotation module - Algorithm settings
1.1 Uploading data set
As a first step of the analysis, a dataset must be uploaded. In order to initiate the page click on "upload dataset" located under the start up with data management field.
1.2 Uploading dataset
In the first field you will come across is the "upload dataset" field where you can manually input a name for your dataset under "name your dataset". After which you can select the type of technology you would like to run under "technology".
1.4 Uploading data matrices
Under this field you can drag and drop files in order to upload the data matrices.
1.4 Setting paramaters - Annotating files
Under this field you will be able to annotate your files by assigning which of the files is related to what section. For example if an uploaded file is pertaining to the datamatrix it can be selected as "data matrix" or "metadata" using the pull down bar.
1.5 Proceeding to data staging
Once all the files are uploaded, named and annotated the "proceed to data staging" button should turn blue which can then be clicked in order to move to the data annotation phase
2 Setting paramaters - Annotate data
In the setting parameters tab you will be able to performs the following actions in the Experiment designmodule:
- Annotate data: specify data matrix type, organism of origin and gene name identifier.
In the Annotate data tab you can more precisely define your data matrix type and provide information that are used for certain downstream algorithms.
- Select data matrix type: specify data matrix type, meaning if the data matrix has been previously normalized or not. A data matrix can be either raw or normalized. You can check if your data matrix has been previously normalized by taking a look at the digits in your data matrix. If the numbers in your data matrix are predominantly integers, no normalization was previously performed. This means you should permorm data normalization in the subsequent Data pretreatment module. If the numbers are predominantly decimals the matrix is already normalized. In this case you can skip data normalization in the Data pretreatment module.
- Select organism: specify from which organism the data was derived from. Current options are: human, mouse or rat.
- Select gene identifier: select type of gene identifier used in the first column of the data matrix.
3. Completing dataset upload
Once the data has been successfully annotated the "complete dataset upload" button should turn blue and can be clicked to upload the dataset. Once this step is achieved the file will be ready for the experimental design module where the dataset can be edited
Was this article helpful?
Thank you for your feedback
Sorry! We couldn't be helpful
Thank you for your feedback
We appreciate your effort and will try to fix the article