Interpreting the MouseBLAST Output Report
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This help document answers the following questions:

What does the MouseBLAST output report contain?

The MouseBLAST output report contains:

Alignment summary of matching sequences

The alignment summary provides a listing of the:

From the alignment summary you can also:

To do either:

Pairwise Alignments

For each pairwise alignment for a matching sequence, the following appears. (Note: Plus strand alignments appear before minus strand alignments.)

Pairwise alignments between the query and matching sequence appear in blocks called High-Scoring Pairs or ASP. ASPs determine how BLAST detects whether two sequences are similar to one another. Gapped BLAST algorithms, such as WU-BLAST 2.0, attempt to extend all HSPs so that they join, if possible. However, sometimes there are multiple HSPs for a given matching sequence; for example, the alignment of the genomic sequence to a transcript results in an HSP for each exon represented in the transcript.

RepeatMasker Output

The RepeatMasker output section (appearing only when you run RepeatMasker) contains a table summarizing repeats detected in the query sequence. The following is an example of the table:

 SW     perc perc perc  query     position in query    matching repeat        position in  repeat
 score  div. del. ins.  sequence  begin  end (left)    repeat   class/family  begin  end (left)  ID
  225   20.0  0.0  0.0  M15131    1083   1127 (211) +  (TTTA)n  Simple_repeat    1   45    (0)      
This table contains:

Repeat Masked Sequence

The Repeat Masked Sequence section appears only when you run RepeatMasker and contains the masked sequence in FASTA format. Any regions of the query sequence that contain repeats found in the sequence are replaced with N characters.


How do I interpret the results of my search?

Most people judge the significance of a sequence alignment by two criteria: the length of the alignment and the percent of the identity. The questions to ask are:

To be sure that two sequences are similar to one another, you should do a bidirectional best hit comparison. In this comparison, the two sequences in question should be the best matches to one another in your database of sequences.

As an example, assume that you have two GenBank mouse sequences, Sequence A and Sequence B. You hypothesize that Sequence A is most similar to Sequence B. To support this hypothesis, you must first search Sequence A against all GenBank mouse sequences, and then search Sequence B against all GenBank mouse sequences. If Sequence A best matches Sequence B in the first alignment, and Sequence B best matches Sequence A, it suggests that these sequences are most similar to one another among all GenBank mouse sequences.


What can I do with a matching sequence?

You can: To do either:


Are there any sample searches?

See Using MouseBLAST - Sample Queries.