RAP - Faq: RAP: RNA-Seq Analysis Pipeline






FAQ

Frequently asked questions
We warmly invite you to read our Help section too. If you still have some doubts about our tool, please write us from our feedback page.

Analysis

  1. What input files are supported?
  2. How many samples can be uploaded and analyzed? How many analysis can be run? Are there any time limits?
  3. Can I upload multiple files? And multiple samples?
  4. How long does a typical analysis take?

Analysis Monitor

  1. Inside my paired-end analysis i have found "unpair" folders produced in the Tophat step. What are they?

Archive

  1. What is a study? What's the difference with a project?

Results

  1. How can I quickly learn how to browse results?
  2. Is it possibile to download the results of my analysis?
  3. Why Cufflinks and Cuffdiff can report different FPKM values for a same transcript?

Other

  1. I used the RAP tool for my project. How can I cite it?



Analysis

1. What input files are supported?
The RAP tool supports:
  • short-read data-sets produced by Illumina sequencing platforms (FASTQ)
  • several standard file formats (SRA, BAM)
  • compressed archives (zip1, tar, gzip, bz or bz2 compression are admitted)

RAP automatically detects the type of uploaded file and chooses the necessary program to decompress it.

[1] Warning: compressed archives obtained with Mac OS X require the windows-compatibility flag
2. How many samples can be uploaded and analyzed? How many analysis can be run? Are there any time limits?
An account with User rank can:
  • create up to 2 studies
  • upload up to 12 files
  • build up to 2 analyses
  • run 1 analysis at a time
3. Can I upload multiple files? And multiple samples?
Each sample has to be uploaded as a single file: you can upload multiple files if you have multiple samples.
The general rule is: 1 sample = 1 file, no merge operation will be executed by our system.
4. How long does a typical analysis take?
The amount of time required by an analysis execution is influenced by different factors, such as:
  • The amount of files uploaded
  • The sequencing region (genome-wide or targeted)
  • The number of jobs waiting for execution on our servers
However, you can find an estimated execution time in your analysis monitoring page.

Analysis Monitor

1. Inside my paired-end analysis i have found "unpair" folders produced in the Tophat step. What are they?
NGSQCToolkit filters low quality reads. In the paired end case this action may lead to a subset of unpaired reads, when only one element of the pair passes the filter. To recover information from unpaired reads we first align them with Tophat producing a junctions file. Then we supply these junctions to align properly paired reads.
More information can be found in Tophat User Manual

Archive

1. What is a study? What's the difference with a project?
According to the EBI/ENA data format standard, a study contains information about the a single sequencing project (more analysis can be run in a single study). So, in practice, a study contains all the information about a project.

Results

1. How can I quickly learn how to browse results?
Click on Results example (on the top navigation menu) to follow a guided tour of the results pages.
2. Is it possibile to download the results of my analysis?
Yes, you have two options:
  • Downloading the results directly from the analysis monitoring page.
  • From the Results page, after applying any filter, with the DOWNLOAD link.
Warning!
Data browsing and downloading has been optimized with caching/sessioning.
While this ensures better performance in page loading, as a drawback opening different tabs on different samples may lead to data misconfiguration.
Please ensure to filter and download one sample at the time.
3. Why Cufflinks and Cuffdiff can report different FPKM values for a same transcript?
By default Cufflinks counts all hits towards the FPKM denominator while Cuffdiff counts only those fragments compatible with some reference transcript. This different behavior can lead to significantly different results.
Counting only compatible hits avoids certain types of bias that arise when one sample contains far more hits that aren't compatible with any transcript than the other sample does. For example, if one sample contains vastly more mapped ribosomal RNA hits, FPKM values will appear lower in that sample, potentially leading to false positive differential expression calls.
Due to contraints in Cufflinks algorithms, to enable this 'compatible hits normalization' the option Novel-Transcripts should be disabled in your analysis.

Other

1. I used the RAP tool for my project. How can I cite it?

BMC Genomics. 2015 16(Suppl 6):S3 (1 June 2015)
RAP: RNA-Seq Analysis Pipeline a new cloud-based NGS web application
Mattia D'Antonio, Paolo D'Onorio De Meo, Matteo Pallocca, Ernesto Picardi, Anna Maria D'Erchia, Raffaele A Calogero, Tiziana Castrignanò and Graziano Pesole

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