The Needleman-Wunsch algorithm is a member of the class of algorithms that can calculate the best score and alignment in the order of mn steps, (where 'n' and 'm' are the lengths of the two sequences). These dynamic programming algorithms were first developed for protein sequence comparison by Needleman and Wunsch, though similar methods were independently devised during the late 1960's and early 1970's for use in the fields of speech processing and computer science.
What is the optimal alignment? Dynamic programming methods ensure the optimal global alignment by exploring all possible alignments and choosing the best. It does this by reading in a scoring matrix that contains values for every possible residue or nucleotide match. Needle finds an alignment with the maximum possible score where the score of an alignment is equal to the sum of the matches taken from the scoring matrix.
An important problem is the treatment of gaps, i.e., spaces inserted to optimise the alignment score. A penalty is subtracted from the score for each gap opened (the 'gap open' penalty) and a penalty is subtracted from the score for the total number of gap spaces multiplied by a cost (the 'gap extension' penalty).
Typically, the cost of extending a gap is set to be 5-10 times lower than the cost for opening a gap.
% needle sw:hba_human sw:hbb_human Gap opening penalty [10.0]: Gap extension penalty [0.5]: Output file [hba_human.needle]:
Mandatory qualifiers: [-sequencea] sequence Sequence USA [-seqall] seqall Sequence database USA -gapopen float The gap open penalty is the score taken away when a gap is created. The best value depends on the choice of comparison matrix. The default value assumes you are using the EBLOSUM62 matrix for protein sequences, and the EDNAFULL matrix for nucleotide sequences. -gapextend float The gap extension, penalty is added to the standard gap penalty for each base or residue in the gap. This is how long gaps are penalized. Usually you will expect a few long gaps rather than many short gaps, so the gap extension penalty should be lower than the gap penalty. An exception is where one or both sequences are single reads with possible sequencing errors in which case you would expect many single base gaps. You can get this result by setting the gap open penalty to zero (or very low) and using the gap extension penalty to control gap scoring. -outfile outfile Output file name Optional qualifiers: -datafile matrixf Matrix file Advanced qualifiers: -[no]similarity bool Display percent identity and similarity -fasta bool Output overlap as fasta sequences -showinternals bool Show debugging information on the internal state of the search. General qualifiers: -help bool report command line options. More information on associated and general qualifiers can be found with -help -verbose
|Mandatory qualifiers||Allowed values||Default|
|Sequence USA||Readable sequence||Required|
|Sequence database USA||Readable sequence(s)||Required|
|-gapopen||The gap open penalty is the score taken away when a gap is created. The best value depends on the choice of comparison matrix. The default value assumes you are using the EBLOSUM62 matrix for protein sequences, and the EDNAFULL matrix for nucleotide sequences.||Floating point number from 1.0 to 100.0||10.0 for any sequence|
|-gapextend||The gap extension, penalty is added to the standard gap penalty for each base or residue in the gap. This is how long gaps are penalized. Usually you will expect a few long gaps rather than many short gaps, so the gap extension penalty should be lower than the gap penalty. An exception is where one or both sequences are single reads with possible sequencing errors in which case you would expect many single base gaps. You can get this result by setting the gap open penalty to zero (or very low) and using the gap extension penalty to control gap scoring.||Floating point number from 0.0 to 10.0||0.5 for any sequence|
|-outfile||Output file name||Output file||<sequence>.needle|
|Optional qualifiers||Allowed values||Default|
|-datafile||Matrix file||Comparison matrix file in EMBOSS data path||EBLOSUM62 for protein
EDNAFULL for DNA
|Advanced qualifiers||Allowed values||Default|
|-[no]similarity||Display percent identity and similarity||Yes/No||Yes|
|-fasta||Output overlap as fasta sequences||Yes/No||No|
|-showinternals||Show debugging information on the internal state of the search.||Yes/No||No|
Global: HBA_HUMAN vs HBB_HUMAN Score: 290.50 HBA_HUMAN 1 VLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFP 44 |:| :|: | | |||| : | | ||| |: : :| |: :| HBB_HUMAN 1 VHLTPEEKSAVTALWGKV..NVDEVGGEALGRLLVVYPWTQRFFE 43 HBA_HUMAN 45 HF.DLS.....HGSAQVKGHGKKVADALTNAVAHVDDMPNALSAL 83 | ||| |: :|| ||||| | :: :||:|:: : | HBB_HUMAN 44 SFGDLSTPDAVMGNPKVKAHGKKVLGAFSDGLAHLDNLKGTFATL 88 HBA_HUMAN 84 SDLHAHKLRVDPVNFKLLSHCLLVTLAAHLPAEFTPAVHASLDKF 128 |:|| || ||| ||:|| : |: || | |||| | |: | HBB_HUMAN 89 SELHCDKLHVDPENFRLLGNVLVCVLAHHFGKEFTPPVQAAYQKV 133 HBA_HUMAN 129 LASVSTVLTSKYR 141 :| |: | || HBB_HUMAN 134 VAGVANALAHKYH 146 %id = 45.32 %similarity = 63.31 Overall %id = 43.15 Overall %similarity = 60.27
The %id is the percentage of identical matches between the two sequences over the reported aligned region.
The %similarity is the percentage of matches between the two sequences over the reported aligned region where the scoring matrix value is greater or equal to 0.0.
The Overall %id and Overall %similarity are calculated in a similar manner for the number of matches over the length of the longest of the two sequences.
EMBOSS data files are distributed with the application and stored in the standard EMBOSS data directory, which is defined by EMBOSS environment variable EMBOSS_DATA.
Users can provide their own data files in their own directories. Project specific files can be put in the current directory, or for tidier directory listings in a subdirectory called ".embossdata". Files for all EMBOSS runs can be put in the user's home directory, or again in a subdirectory called ".embossdata".
The directories are searched in the following order:
A true Needleman Wunsch implementation like needle needs memory proportional to the product of the sequence lengths. For two sequences of length 10,000,000 and 1,000 it therefore needs memory proportional to 10,000,000,000 characters. Two arrays of this size are produced, one of ints and one of floats so multiply that figure by 8 to get the memory usage in bytes. That doesn't include other overheads. Therefore only use water and needle for accurate alignment of reasonably short sequences.
If you run out of memory, try using stretcher instead.
Uncaught exception Assertion failed raised at ajmem.c:xxx
Probably means you have run out of memory. Try using stretcher if this happens.
|est2genome||Align EST and genomic DNA sequences|
|stretcher||Finds the best global alignment between two sequences|
When you want an alignment that covers the whole length of both sequences, use needle.
When you are trying to find the best region of similarity between two sequences, use water.
stretcher is a more suitable program to use to find global alignments of very long sequences.
Completed 8th July 1999. Modified 26th July 1999 - scoring tweaked. Modified 22 Oct 2000 - %ID and %Similaritty scores added.