Editing Sequence assembly (section)

== Assembly algorithms ==

Different organisms have a distinct region of higher complexity within their genome. Hence, the need of different computational approaches is needed. Some of the commonly used algorithms are:

; Graph Assembly: is based on Graph theory in computer science. The [[De Bruijn graph|de Bruijn Graph]] is an example of this approach and utilizes [[k-mers]] to assemble a contiguous from reads.<ref>{{cite journal | vauthors = Compeau PE, Pevzner PA, Tesler G | title = How to apply de Bruijn graphs to genome assembly | journal = Nature Biotechnology | volume = 29 | issue = 11 | pages = 987–991 | date = November 2011 | pmid = 22068540 | pmc = 5531759 | doi = 10.1038/nbt.2023 }}</ref>
; Greedy Graph Assembly: this approach score each added read to the assembly and selects the highest possible score from the overlapping region. 
:Given a set of sequence fragments, the object is to find a longer sequence that contains all the fragments (see figure under ''Types of Sequence Assembly''):
:# Сalculate pairwise alignments of all fragments.
:# Choose two fragments with the largest overlap.
:# Merge chosen fragments.
:# Repeat step 2 and 3 until only one fragment is left.
:The result might not be an optimal solution to the problem.