PMID- 18230160
OWN - NLM
STAT- MEDLINE
DCOM- 20080310
LR  - 20220409
IS  - 1471-2105 (Electronic)
IS  - 1471-2105 (Linking)
VI  - 9
DP  - 2008 Jan 29
TI  - E-CAI: a novel server to estimate an expected value of Codon Adaptation Index 
      (eCAI).
PG  - 65
LID - 10.1186/1471-2105-9-65 [doi]
AB  - BACKGROUND: The Codon Adaptation Index (CAI) is a measure of the synonymous codon 
      usage bias for a DNA or RNA sequence. It quantifies the similarity between the 
      synonymous codon usage of a gene and the synonymous codon frequency of a 
      reference set. Extreme values in the nucleotide or in the amino acid composition 
      have a large impact on differential preference for synonymous codons. It is 
      thence essential to define the limits for the expected value of CAI on the basis 
      of sequence composition in order to properly interpret the CAI and provide 
      statistical support to CAI analyses. Though several freely available programs 
      calculate the CAI for a given DNA sequence, none of them corrects for 
      compositional biases or provides confidence intervals for CAI values. RESULTS: 
      The E-CAI server, available at http://genomes.urv.es/CAIcal/E-CAI, is a 
      web-application that calculates an expected value of CAI for a set of query 
      sequences by generating random sequences with G+C and amino acid content similar 
      to those of the input. An executable file, a tutorial, a Frequently Asked 
      Questions (FAQ) section and several examples are also available. To exemplify the 
      use of the E-CAI server, we have analysed the codon adaptation of human 
      mitochondrial genes that codify a subunit of the mitochondrial respiratory chain 
      (excluding those genes that lack a prokaryotic orthologue) and are encoded in the 
      nuclear genome. It is assumed that these genes were transferred from the 
      proto-mitochondrial to the nuclear genome and that its codon usage was then 
      ameliorated. CONCLUSION: The E-CAI server provides a direct threshold value for 
      discerning whether the differences in CAI are statistically significant or 
      whether they are merely artifacts that arise from internal biases in the G+C 
      composition and/or amino acid composition of the query sequences.
FAU - Puigbo, Pere
AU  - Puigbo P
AD  - Evolutionary Genomics Group, Department of Biochemistry and Biotechnology, Rovira 
      i Virgili University (URV), Campus Sescelades, c/Marcelli Domingo s/n, 43007 
      Tarragona, Spain. ppuigbo@urv.cat
FAU - Bravo, Ignacio G
AU  - Bravo IG
FAU - Garcia-Vallve, Santiago
AU  - Garcia-Vallve S
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20080129
PL  - England
TA  - BMC Bioinformatics
JT  - BMC bioinformatics
JID - 100965194
RN  - 0 (Codon)
SB  - IM
MH  - Adaptation, Physiological/genetics
MH  - *Algorithms
MH  - Base Sequence
MH  - Codon/*genetics
MH  - Computer Simulation
MH  - Data Interpretation, Statistical
MH  - Genetic Variation/*genetics
MH  - *Internet
MH  - *Models, Genetic
MH  - Models, Statistical
MH  - Molecular Sequence Data
MH  - Sequence Analysis, DNA/*methods
MH  - *Software
PMC - PMC2246156
EDAT- 2008/01/31 09:00
MHDA- 2008/03/11 09:00
PMCR- 2008/01/29
CRDT- 2008/01/31 09:00
PHST- 2007/03/30 00:00 [received]
PHST- 2008/01/29 00:00 [accepted]
PHST- 2008/01/31 09:00 [pubmed]
PHST- 2008/03/11 09:00 [medline]
PHST- 2008/01/31 09:00 [entrez]
PHST- 2008/01/29 00:00 [pmc-release]
AID - 1471-2105-9-65 [pii]
AID - 10.1186/1471-2105-9-65 [doi]
PST - epublish
SO  - BMC Bioinformatics. 2008 Jan 29;9:65. doi: 10.1186/1471-2105-9-65.