Where do I find data that was shared with me?

If the files were linked into the group folder, you will find them there. You can access the group folder from the file browser, under the “Shared with me” section. Otherwise, the files can be found via search, if you know their name or accession.

How do I reuse a data flow?

Open a data flow you would like to run in the “Run Dataflow” application. On the application page you can set input files and additional files (e.g. reference genome) that are required for analysis.

How can I initialize files?

Generally speaking, there are many ways to initialize files in Genestack. Firstly, you can use File Initializer app that can accept multiple files. To do so, select files of your interest, right-click on them and go to Manage section. Then, you can start initialization when run data flow. On the “Data Flow Runner” page when all inputs are set, all files are created and you are happy with parameters of each app, you will be suggested to start computations right away or delay it. Finally, you can right-click file name wherever you are in the platform (on Data Flow Runner, File Manger, Task Manager, any bioinformatic app etc.) and select “Start initialization” option in the context menu.

How do I create a data flow?

To create a data flow, select the data you wish to analyse and choose the first application you wish to use in your analysis. On the application page, using the “add step” button, add the rest of the desired steps. Once you are done, click on the name of the file (or files) at the top of the page, go to Manage, and click on Create New Data Flow. Your new data flow can be found in the Created Files folder

If you do not want to create a data flow from scratch, but rather re-use the same analysis pipeline used to create a file, click on the name of that file, go to Manage, and select Create New Data Flow.

Selecting File Provenance instead of Create New Data Flow will show you the pipeline (in the form of a data flow) that was used to create this file. Read more about data flows in this tutorial.

What is the difference between BWA and Bowtie2?

The biggest differences between the two aligners are:

  • the way of accepting or rejecting an alignment
    BWA counts the number of mismatches between the read and the corresponding genomic position; Bowtie2 aligner uses a quality threshold bases on the probability of the occurrence of the read sequence given an alignment location.
  • accepting colorspace data
    BWA tool does not support data in colorspace data, while Bowtie2 is able to align such files.

How does Genestack process paired-end reads?

There are three types of raw sequencing reads that our platform supports:

  • single-end (1 file locally, 1 file in Genestack);
  • paired-end (2 files locally, 1 file in Genestack);
  • paired-with-unpaired (3 or 4 files locally, 2 files in Genestack).

During import, Genestack recognises them and imports them in their respective format-free form. If the platform cannot recognise the files automatically, you can allocate the files manually.

What is the difference between an Datasets and a folder?

Datasets are a special kind of folder, which can only contain assays, e.g. “raw” experimental data.

What is the difference between masked and unmasked reference genomes?

In general, when a genomes is “masked” it means that all repeats and low complexity regions of your reference genome (detected by RepeatMasker tool) are hidden away and replaced with “N”s, so that they will not be aligned to.

We do not recommend using a masked genome, as it always  results in a loss of information. Masking can never be 100% accurate, and can lead to an increase in the number of falsely mapped reads. If you would like to perform filtering, it is better to do it after the mapping step.

In soft-masked genomes, repeated and low complexity regions are still present, but they have been replaced with lowercased versions of their nucleic base.

Unmasked genomes contain all repeats and low complexity regions without any changes.

What is the difference between Data Flow Runner and Data Flow Editor?

Data Flow Editor is used to create data flow templates, e.g. selecting source files.

When you want to use the data flow to run your analysis, on the Data Flow Editor page you can click on “Run Data Flow” button, which will take you to Data Flow Runner. Here you can not only edit source files and parameters, but also start initialization of your files.