Reading frames plays an important role in the process of translation of proteins from nucleotide sequences. Selection of a wrong reading frame could lead to the wrong protein products which might have lethal results. Though errors that alter the reading frame occur extremely rarely during translation, one such event is frame-shift. Frame-shift mutation is a genetic mutation caused generally by indels, i.e. insertion and deletion of nucleotides. Coding sequences lack stop codons, but many stop codons appear off-frame. Off-frame stops, i.e. stop codons in +1 and -1 shifted reading frames, are termed hidden stop codons or hidden stops. Even a single indel could completely mutate the sequence, which may result in the change of stop codons. A stop codon keeps a check on the translation process and hence controls the protein product. Frame-shifts lead to waste of energy, resources and activity of the biosynthetic machinery. In addition, some peptides synthesized after frame-shifts are probably cytotoxic. If a stop codon is not read, could lead to massive growth of proteins and might even lead to severe disease such as cancer. There are several cases of read through stop codons and have correlations with myriad of disorders.

Here we present a web server that is able to identify such hidden stop codons in the genomic DNA sequence. It will check hidden stops in both +1 and -1 frame-shift with respective genetic code systems. The server will calculate various categories of codons with their respective contribution to hidden stops. Further it will calculate correlation between codon usage frequencies and contribution of codons to hidden stops in off frame context, in the given sequence(s). Additionally, one tailed t-test will be performed to generate the t-values for statistically significant correlations. This server will help the computational and evolutionary biologists in the analysis of frame-shifted translation in coding genomic sequences and their evolutionary implications and applications.