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SSAHA Search with Speed Nick Altemose, Kelvin
Gu, Tiffany Lin, Kevin Tao, Owen Astrachan Duke
University Focus Program The Genome Revolution
and Its Impact on Society
How Does a Hash Table Work?
Introduction
APT k-tuple Coordinates in a Hash Table
SSAHA Step-by-Step

• The Human Genome contains an immense amount of
  information 3 Billion base pairs, 3 Gigabytes of
  storage space. In fact, if you were to read it
  aloud continuously at the alarming rate of 10
  base pairs per second, it would take you 9.5
  years to get through it all.
• When you want to search for a sequence in the
  genome, you must use smart search methods like
  those used by internet search engines. If you
  were to search through the entire genome one base
  pair at a time, it could take hours to get back
  any results, even with the best computers.
• SSAHA is a search method that was developed with
  one goal in mind speed.
• SSAHA takes a database of data, like the 3
  Gigabase human genome reference sequence, and
  organizes it into a fast searchable index, known
  as a hash table.
• This organization is the key to SSAHAs speed,
  and the origin of its name Sequence Search and
  Alignment by Hashing Algorithm.
• The hash table is like a dictionary to the
  English language, or an index to an encyclopedia.
  It allows for fast lookup of organized
  information. After making this hash table, it is
  then very easy to search for a given sequence.

• Problem Statement
• In this APT, you will generate a string similar
  to a single hash table entry. Given an array of
  DNA strings (our database) and a dimer string
  (our 2-tuple), output a string containing the
  positions of every occurrence of that 2-tuple in
  the database (not limited to a single reading
  frame). Positions will be in the form of
  (0-initiated array element index, 0-initiated
  character index) and should be ordered ascending
  numerically first by array element index, then by
  character index. Note that these positions will
  be 0-initiated and not 1-initiated like actual
  SSAHA positions.
• Notes
• Positions should be space-delimited in the
  string. For example, an output string containing
  5 positions should have this format
• (0,2) (1,3) (2,5) (5,3) (6,7)
• Constraints
• database can contain strings of any length,
  including 0 and 1.
• All input strings will contain only the
  characters A, G, C,or T in any
  combination.
• twotuple will always have exactly 2 characters.
• Examples
• 1. ATTCGT, TACGG, GAATCA, G
• CG
• Returns (0, 3) (1, 2)
• 2. TTCGT, AAATC, ATATATTTA, TCGAAATG
• AT
• Returns (1, 2) (2, 0) (2, 2) (2, 4)
  (3, 6)
• 3. TTTTT, ATTCG
• TT
• Returns (0,0) (0, 1) (0, 2) (0, 3)
  (1, 1)

1) Break sequences in database into
k-tuples. 2) Make a hash table. Ideally,
each cell in the hash table is allotted for one
particular unique k-tuple. Each cell
contains the locations where that particular
unique k-tuple occurs. The location specifies the
sequence where the k-tuple occurs, and the index
in the sequence where the k-tuple occurs. 3) The
query sequence is also broken into
k-tuples. 4) These query k-tuples are
matched to k-tuples in the database. Matches are
noted. 5) SSAHA returns search results,
listing sequences from the database that best
match the query sequence. The degree of
similarity is based on the amount of matching
k-tuples, the successiveness in which they match
(this involves pathingnot explained here) etc.
and attempts to account for insertions, deletions
and SNPs.

• The hash table stores positions at which
  different short sequences, called k-tuples, occur
  in the database. A position looks like this
  (index, offset), where index identifies which DNA
  strand contains the k-tuple, and offset
  identifies at what position in the DNA strand the
  k-tuple begins.
• In lay terms, SSAHA likes to keep things
  organized, like an anal retentive woman who puts
  everything in labeled Tupperware, which she then
  organizes into labeled drawers. The index is like
  the labeled drawer, and the offset is like the
  labeled Tupperware. If you tell her to get
  something from the third drawer, fourth
  Tupperware, she can quickly and easily locate
  what youre looking for. Or, if you ask her where
  you can find something, she can easily tell you
  in which drawer and Tupperware youll find it.
• You only have to make a hash table once for a
  given database, kind of like you only have to
  tidy your room up once, then you can find things
  extremely easily thereafter.

Visual of Hash Table Search
How Does SSAHA Code for Base Pairs?

• SSAHA stores individual nucleotide base
  information as 2-bits of information per base
• A is stored as 00
• C is stored as 01
• G is stored as 10
• T is stored as 11
• This allows for fast and efficient storage and
  processing, using less memory and less processor
  power
• However, the drawback is that only 4 characters
  are possible, and sometimes real DNA data has
  gaps and ambiguous characters
• Other search engines treat these ambiguities as
  separate letters, like R or N (N means it could
  be any base)
• SSAHA reverts all ambiguities to A, since AAAAA
  is the most common word in the genome, and the
  search can easily recognize it as uninformative

Contact Information
Nick Altemose, Student, Duke University Trinity
College of Arts and Sciences email
nick.altemose_at_duke.edu Owen Astrachan,
Professor, Duke University Department of Computer
Science email ola_at_cs.duke.edu Kelvin
Gu, Student, Duke University Trinity College of
Arts and Sciences email
kelvin.gu_at_duke.edu Tiffany Lin, Student, Duke
University Trinity College of Arts and Sciences
email tiffany.lin_at_duke.edu Kevin Tao,
Student, Duke University Pratt School of
Engineering email kevin.tao_at_duke.edu
Works Referenced
Genome Size Data from Department of Energy Website http//www.ornl.gov/sci/techresources/Human_Genome/faq/faqs1.shtml SSAHA data from Genome Research 2001 volume 11, pages 1725-1729 SSAHA A Fast Search Method for Large DNA Databases