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TSSAR: Transcription Start Site Annotation Regime Web Service

TSSAR is a tool for rapid screening of dRNA-seq data and de-novo annotation of Transcription Start Sites. This site gives a step-by-step list of tasks necessary to successfully conduct a TSSAR analysis.

TSSAR Workflow

  1. Conduct dRNA-seq experiment as described in literature. Map your sequencing reads to your reference genome. Reads might be stored in SAM/BAM or BED format. If you only want to test TSSAR and do not have a dRNA-seq data set at hand, you can try the TSSAR test data set.
  2. Open the TSSAR Java Client for pre-processing. You can download the Java client from the TSSAR Downloads section and start it manually from your hard drive.
  3. Within the Client, you are encouraged to provide your email address. This is a mandatory step since you will receive a confirmation email once your results are available. Any email address entered here will only be used to inform you about the progress of the calculation. We will not share your contact information with third parties, nor will we use it to contact you for purposes other than mentioned above. However, you can simply specify a fake email address in the form if you prefer to stay anonymous.
  4. Enter the NCBI accession number of your reference genome or the genome size of your reference sequence. If only the latter is provided, annotated TSS cannot be classified in the post processing step. The NCBI accession number for your species can be found at the NCBI Nucleotide Database and typically has the form NC_123456.
  5. Specify the window length which defines the length of the region that is locally modeled to identify significant enriched positions. The default value of 1000 has been chosen since it is approximately the average gene length in bacteria. If your species of interest has a considerably different gene length, you might want to modify the value.
  6. Provide the path to your mapped dRNA-seq data. 'plus library' expects the data for the TEX treated library, 'minus library' for the untreated library.
  7. Press 'Process Data'.
  8. The TSSAR client will process your NGS data and display a hyperlink to your TSSAR results upon success. In case you have not specified an email address in the previous step, please note that you have to bookmark this hyperlink since this is the only way to find and access your results later. If the processing and data upload was successful, you can close the TSSAR Client. The TSSAR analysis is now processed on the TBI server infrastructure and independent from your machine.
  9. Once the analysis is done, you will be notified by email (if an email address has been provided). You can find a general description of you analysis on the results page indicated by the hyperlink mentioned before.
  10. To get detailed results of the analysis you can specify 3 parameters that are used to filter relevant transcription start sites.
    • P-value - all positions with P-value lower than the threshold are reported (0.1 to 10-15)
    • background noise threshold - only positions with this number of reads in the TEX treated library are considered to be TSS (values: 2, 4 or 10)
    • merge range - consecutive positions which are annotated as TSS can be merged together. This parameter defines how close two positions must be in order to get clustered to the most prominent signal (values 1, 5 and 10 nt)
  11. Raw and clustered TSS lists can be screened. If a reference genome accession number was provided, a table describing the position of each TSS relative to annotated genes is provided, whose content is further prepared graphically, displaying the number of TSS for each category (Primary, Internal or Antisense) and the 5'UTR length distribution.
  12. Eventually, all results can be downloaded in the various file formats ([BED] [GFF] [CSV] [TSV] and [XLSX] for the tables and coordinate files; [PNG] and [SVG] for the graphic files). See TSSAR output for a detailed description of output files.

If TSSAR is useful for your work or if you use any figures or data procuced by TSSAR, please cite the original TSSAR publication: "TSSAR: TSS Annotation Regime for dRNA-seq data" F. Amman, M.T. Wolfinger, R. Lorenz, I.L. Hofacker, P.F. Stadler and S. Findeiß BMC Bioinformatics 2014 15:89 doi:10.1186/1471-2105-15-89 - Contact: