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https:// rvista . dcode . org

Finding potential regulatory elements in noncoding regions of the human genome is a challenging problem. Analyzing novel sequences for the presence of known transcription factor binding sites or their weight matrices produces a huge number of false positive predictions that are randomly and uniformily distributed. rVista combines database searches with comparative sequence analysis, reducing the number of false positive predictions by ~95% while maintaining a high sensitivity of the search.

G. Loots and I. Ovcharenko, rVista 2.0: evolutionary analysis of transcription factor binding sites.
Nucleic Acids Research, 32(Web Server Issue), W217-W221 (2004) [PDF]


There are 4 diffrent ways to run rVista 2.0:

If you have two sequence files in FASTA format then you can align them using fast and interactive alignment tool zPicture located at https://zpicture.dcode.org. zPicture alignments could be automatically submitted to rVista 2.0.

If you know the location (or gene name) in either human, mouse, rat, or Fugu genome then you can forward precalculated alignments for the rVista processing from the ECR Browser located at https://ecrbrowser.dcode.org

Precalculated blastz alignments. (blastz alignments could be obtained through the use of multiple tools developed in Webb Miller's lab. Please verify that the alignment format is the same as the example format.)
blastz textual alignment file (example):
Sequence FASTA files (example - seq1.txt and seq2.txt):
        base sequence:   
        second sequence:
Optional gene annotation (example):
        base seq annotation:   
        second seq annotation:

GALA (Genome Alignment and Annotation Database) automatically forwards genome scans to rVista 2.0
            Thanks to Belinda Giardine and Ross C. Hardison from Penn State University for making this possible!



Return to previously submitted request. ID:

Instructions: rVista version 2.0
Questions or comments: email dcode@ncbi.nlm.nih.gov
Citing rVista 2.0: G. Loots and I. Ovcharenko, rVista 2.0: evolutionary analysis of transcription factor binding sites.
Nucleic Acids Research, 32(Web Server Issue), W217-W221 (2004)