2ndscore in.fasta > out.hairpins


For every position in the sequence this will output a line:

-0.6 52 .. 62 TTCCTAAAGGTTCCA GCG CAAAA TGC CATAAGCACCACATT (score) (start .. end) (left context) (hairpin) (right contenxt)

For positions near the ends of the sequences, the context may be padded with 'x' characters. If no hairpin can be found, the score will be 'None'.

Multiple fasta files can be given and multiple sequences can be in each fasta file. The output for each sequence will be separated by a line starting with '>' and containing the \s-1FASTA\s0 description of the sequence.

Because the hairpin scores of the plus-strand and minus-strand may differ (due to \s-1GU\s0 binding in \s-1RNA\s0), by default 2ndscore outputs two sets of hairpins for every sequence: the \s-1FORWARD\s0 hairpins and the \s-1REVERSE\s0 hairpins. All the forward hairpins are output first, and are identified by having the word '\s-1FORWARD\s0' at the end of the '>' line preceding them. Similarly, the \s-1REVERSE\s0 hairpins are listed after a '>' line ending with '\s-1REVERSE\s0'. If you want to search only one or the other strand, you can use:

--no-fwd Don't print the FORWARD hairpins --no-rvs Don't print the REVERSE hairpins

You can set the energy function used, just as with transterm with the --gc, --au, --gu, --mm, --gap options. The --min-loop, --max-loop, and --max-len options are also supported.

\s-1FORMAT\s0 \s-1OF\s0 \s-1THE\s0 .BAG \s-1FILES\s0

The columns for the .bag files are, in order:

1. gene_name 2. terminator_start 3. terminator_end 4. hairpin_score 5. tail_score 6. terminator_sequence

7. terminator_confidence: a combination of the hairpin and tail score that takes into account how likely such scores are in a random sequence. This is the main "score" for the terminator and is computed as described in the paper.

8. APPROXIMATE_distance_from_end_of_gene: The *approximate* number of base pairs between the end of the gene and the start of the terminator. This is approximate in several ways: First, (and most important) TransTermHP doesn't always use the real gene ends. Depending on the options you give it may trim some off the ends of genes to handle terminators that partially overlap with genes. Second, where the terminator "begins" isn't that well defined. This field is intended only for a sanity check (terminators reported to be the best near the ends of genes shouldn't be _too far_ from the end of the gene).

\s-1USING\s0 \s-1TRANSTERM\s0 \s-1WITHOUT\s0 \s-1GENOME\s0 \s-1ANNOTATIONS\s0

TransTermHP uses known gene information for only 3 things: (1) tagging the putative terminators as either \*(L"inside genes\*(R" or \*(L"intergenic,\*(R" (2) choosing the background GC-content percentage to compute the scores, because genes often have different \s-1GC\s0 content than the intergenic regions, and (3) producing slightly more readable output. Items (1) and (3) are not really necessary, and (2) has no effect if your genes have about the same GC-content as your intergenic regions.

Unfortunately, TransTermHP doesn't yet have a simple option to run without an annotation file (either .ptt or .coords), and requires at least 2 genes to be present. The solution is to create fake, small genes that flank each chromosome. To do this, make a fake.coords file that contains only these two lines:

fakegene1 1 2 chome_id fakegene2 L-1 L chrom_id

where L is the length of the input sequence and L-1 is 1 less than the length of the input sequence. \*(L"chrom_id\*(R" should be the word directly following the \*(L">\*(R" in the .fasta file containing your sequence. (If, for example, your .fasta file began with \*(L">seq1\*(R", then chrom_id = seq1).

This creates a \*(L"fake\*(R" annotation with two 1-base-long genes flanking the sequence in a tail-to-tail arrangement: --> <--. TransTermHP can then be run with:

transterm -p expterm.dat sequence.fasta fake.coords

If the G/C content of your intergenic regions is about the same as your genes, then this won't have too much of an effect on the scores terminators receive. On the other hand, this use of TransTermHP hasn't been tested much at all, so it's hard to vouch for its accuracy.

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Alex Mestiashvili <[email protected]>