This algorithm is a re-implementation of algorithm based on R-loop detection algorithm called
<ahref="https://pubmed.ncbi.nlm.nih.gov/25883153/">QmRLFS finder</a>. R-loop tracker is a toll for prediction of
R-loops in nucleic acids. The algorithms search for R-loop initiation zone based on presence of G-clusters and
R-loop elongation zone containing at least 40% of Guanine density. Our tool offers integration with Genome
browser, enhanced visualization and export formats, as well on-line sorting, and statistical characteristic.
Thanks to new java-based architecture can process whole chromosomes as well as complete genomes by batch analyses.
</p>
<h1>Z-DNA Tracker Help Page</h1>
<p>Welcome to the Z-DNA Tracker, a specialized tool designed for the analysis and identification of Z-DNA regions within nucleic acid sequences. This tool is based on the methodologies and algorithms developed in the <ahref="https://github.com/abcsFrederick/non-B_gfa">non-B_gfa</a> project and the <ahref="https://nonb-abcc.ncifcrf.gov/apps/nBMST/default/">nBMST application</a> hosted by the National Cancer Institute. Our Z-DNA Tracker provides a user-friendly interface to analyze sequences for potential Z-DNA forming regions, contributing valuable insights into the structural dynamics and biological functions of these unique DNA conformations.</p>
<h2id="input">Input data</h2>
<hr/>
<p>
Sequence can be imported as a text, fasta file or directly from NCBI database, for details please check help part
for <ahref="/#/help/import">Import</a>. The choices are described in
The organism's first letter must be capital (upper-case). This is ideal format, which will result in smooth import
into Genome browser.
</p>
<h2>Model selection</h2>
<hr/>
<p>On the analysis page, you can select one of 2 models.</p>
<h2>Getting Started</h2>
<ol>
<li><strong>Sequence Input</strong>: Begin by inputting your DNA sequences into the tool. You can input multiple sequences at once for batch analysis. Ensure that your sequences are in a compatible format (e.g., FASTA).</li>
<li><strong>Analysis Parameters</strong>: Set the parameters for your analysis. While default settings are provided, you may adjust these based on your specific research needs or the recommendations from the underlying algorithms.
<ul>
<li><strong>Minimum sequence size</strong>: minimal length of searched sequences (equal or bigger than 10)</li>
<li><strong>Threshold</strong>: this is the minimum score of searched Z-DNA score (equal or bigger than 0)</li>
</ul>
</li>
<li><strong>Submission</strong>: Once your sequences and parameters are set, submit them for analysis. The processing time will vary depending on the complexity and number of sequences.</li>
</ol>
<h2>Score Calculation</h2>
<p>The Z-DNA Tracker calculates scores based on the propensity of sequence regions to form Z-DNA. The scoring system is as follows:</p>
<ul>
<li>
<b>RIZ 3G-cluster</b> RIZ (R-loop initiation zone) consists of <b>three</b> consecutive G-clusters which have at
least <b>3</b> Guanines in them.
</li>
<li>
<b>RIZ 4G-cluster</b>RIZ (R-loop initiation zone) consists of <b>two</b> consecutive G-clusters which have at
least <b>4</b> Guanines in them.
</li>
<li><strong>C/G and G/C pairs</strong>: These pairs are highly indicative of Z-DNA formation and are awarded <strong>25 points</strong> each.</li>
<li><strong>G/T, T/G, C/A, and A/C pairs</strong>: These pairs have a lower propensity for Z-DNA formation but are still significant, each receiving <strong>3 points</strong>.</li>
<li><strong>Other pairs</strong>: Any other base pairs are considered forbidden in the context of Z-DNA formation and are awarded <strong>0 points</strong>.</li>
</ul>
<p>
Both of the models are described in <ahref="https://pubmed.ncbi.nlm.nih.gov/25883153/">this article</a>.<br/>
You can of course select both of the models at once.
</p>
<p>This scoring system is designed to highlight regions within the DNA sequence that have a higher likelihood of adopting the Z-DNA conformation, based on the specific base pairings and their known propensities for such structural formations.</p>
<h2>Output formats</h2>
<hr/>
<h3>Website</h3>
Website offers visualization of R-loop distribution in analyzed sequence. Each sequence is coloured: red is used for
Gs and blue for Cs. Brighter tone is used for longer Gs/Cs sequences. Results are shown as a table with following
sortable columns:
<h2>Understanding Your Results</h2>
<p>Upon completion of the analysis, the Z-DNA Tracker presents the results in an intuitive format, including:</p>
<ul>
<li><b>Position</b></li>
- start of the R-loop in given sequence
<li><b>Length</b></li>
- length of the R-loop
<li><b>Model</b></li>
- which model was used to detect the R-loop
<li><b>Strand</b></li>
- DNA strand (direction)
<li><b>RIZ</b></li>
- R-loop initiation zone sequence
<li><b>Linker length</b></li>
- length of a linker (0 if none is detected)
<li><b>REZ</b></li>
- R-loop elongation zone sequence. Altogether, RIZ+linker+REZ represents the whole R-loop
<li><b>RIZ Guanine richness</b></li>
- percentage of Guanine in RIZ area
<li><b>Rloop Guanine richness</b></li>
- percentage of Guanine in whole R-loop
<li><b>Number of 3G clusters</b></li>
<li><b>Number of 4G clusters</b></li>
<li><b>Number of 5G clusters and more</b></li>
<li><strong>Heatmap</strong>: A visual representation showing the distribution and intensity of potential Z-DNA forming regions across your sequences.</li>
<li><strong>Analysis Settings</strong>:
</li>
<li><strong>Analysis Results</strong>:
<ul>
<li>Z-DNAs found</li>
<li>Frequency on 1000 bp</li>
</ul>
</li>
<li><strong>Export Options</strong>: Results can be exported in CSV and Bedgraph formats for further analysis or record-keeping.</li>
<li><strong>Sequence Info</strong></li>
</ul>
<p>The detailed list of results includes the following columns:</p>
<ul>
<li><strong>Position</strong>: The starting position of the Z-DNA region within the sequence.</li>
<li><strong>Length</strong>: The length of the Z-DNA region.</li>
<li><strong>Sequence</strong>: The actual nucleotide sequence of the Z-DNA region.</li>
<li><strong>Z-DNA GC Richness</strong>: The GC content within the Z-DNA region, indicative of its stability and propensity for Z-DNA formation.</li>
<li><strong>Z-DNA GT Richness</strong>: The GT content within the Z-DNA region, which can also influence Z-DNA formation.</li>
<li><strong>Z-DNA Score</strong>: The overall score calculated based on the specific base pairings and their propensities for Z-DNA formation.</li>
</ul>
<h3id="file-export">File export</h3>
All results can be exported into two possible file formats:
<ol>
<li>
<b>CSV</b> common file format with the following fields:
<ul>
<li>
position, length, RIZ, linker, REZ, model, strand (same as on website)
</li>
<li>
RIZGRICHNESS (percentage of Guanine nucleotides in RIZ sequence)
</li>
<li>
RLOOPGRICHNESS (percentage of Guanine nucleotides in whole R-loop)
</li>
<li>
G3 (count of 3G clusters in the sequence)
</li>
<li>
G4 (count of 4G clusters in the sequence)
</li>
<li>
GN (count of 5G and more clusters in the sequence)
</li>
</ul>
</li>
<li>
<b>bedGraph</b>
<br/>
BedGraph is a special
<ahref="https://genome.ucsc.edu/goldenPath/help/bedgraph.html">file format for Genome Browser integration</a>.
We have to improve our score rating for R-loops, which will result in better visualisation in Genome Browser.
<br/>
In order to integrate your analysis into <ahref="https://genome.ucsc.edu/">Genome Browser</a>, you have to
follow these steps:
<ol>
<li>
Navigate to the <ahref="https://genome.ucsc.edu/cgi-bin/hgCustom">Custom tracks page</a> (Home -> My Data
-> Custom Tracks)
</li>
<li>Upload the bedGraph file downloaded from DNA analyser and hit the <code>Submit</code> button</li>
<li>
You should see the table with your track and now You can view it in Genome Browser (after hitting
<code>Go</code> button
</li>
<li>
The tracks will have green color shade according to their score and the track itself will be named
DNA-analyser
</li>
</ol>
</li>
</ol>
<h3>Example</h3>
The most basic example is to use the pre-imported sequence <code>Myc_chr8:128748315-128753680</code> available when
you are not logged in. You can find already imported sequences in the navigation by clicking on
<ahref="/#/analyse/rloopr">Analyses -> R-loop tracker</a>. If you do not see the sequence, try logging out
beforehand. After this, just hit the green <b>Analyse</b> button, which starts the <em>RIZ 3G-cluster</em>
analysis for you.
<h4>Troubleshooting</h4>
If the track does not upload succesfully, try to follow the name specification described in
