You can create new comparisons without them or upload a new copy of the experiment without them
There is no way to completely remove individual samples from an existing analysis without creating a new experiment. Therefore, here are 2 available options:
1. Leave them in, but create new Comparisons that do not have those samples
2. Upload a New Experiment:
- If you have an annual paid subscription, you can use our free Sample Re-use service. Only RNA-seq and smallRNA-seq qualify for this. You would upload a new experiment using the Raw Rosalind Ready for Re-uploading as Processed Counts and then remove the unwanted or outlier samples prior to submitting. Rosalind will provide the Analysis Units to unlock the re-used samples (please see Option 2 in this article for more detailed instructions)
- If your subscription or data does not qualify for Sample Re-use, you can upload a new experiment but will need to unlock it with your own Analysis Units. You could still upload a Processed Counts experiment following the instructions outlined here (this processes much faster) or alternatively, you could upload a new experiment with only the FASTQ of the samples you want.
Option 1: Leaving them in and Creating New Comparisons
You can create new comparisons that only contain the samples that you prefer to compare and remove the unwanted samples.
- When creating comparisons using Attributes, you can click 'Edit' to bring up a menu and select which to keep
Option 2: Upload a New Experiment using the Raw Processed Counts
You can quickly and easily create a new Processed Counts experiment with data you have already uploaded to ROSALIND instead of re-processing all of your FASTQ files. See below for instructions:
Steps for re-uploading processed counts:
- Raw Counts (make sure to choose RAW, not Normalized)
- Attributes File
- Using the Processed Counts file will be faster than re-submitting the FASTQ files
- If needed, you can view and download the QC plots without spending any Analysis Units to confirm you are ready to unlock the analysis for these samples