Year: 2011
Type: book-chapter
Abstract: biological correctness' of MSAs.It remains for the end user to incorporate the statistics into their evaluation of this 'biological correctness'.Due to its significant impact on many bioinformatics and molecular evolutionary studies, MSA is one of the most scrutinized bioinformatics fields (Kemena & Notredame, 2009;Thompson et al., 2011).However, assessment of MSAs is usually reserved for power users.Often regular users simply run one MSA method and proceed to the next analysis without examining their alignment output (Morrison, 2009b).Considering how MSA quality affects the outcomes of further analysis, assessment of MSAs, however, should be included as regular part of sequence analysis.In order to facilitate comparative analysis of MSAs, we recently developed a software package called SuiteMSA (Anderson et al., 2011).SuiteMSA provides several alignment-viewing tools that allow the user to compare MSAs both visually and quantitatively.SuiteMSA also includes a feature-rich biological sequence simulator, indel-Seq-Gen v2.1 (Strope et al., 2009), with a user-friendly graphical interface, allowing the users to generate their own benchmark alignments for testing various MSAs.In this chapter, we first review some of the statistics used to assess the quality of MSAs focusing on those used in SuiteMSA.We then describe how MSA comparison can be actually performed using various MSA viewers available in SuiteMSA.Five examples are chosen from diverse types of alignment problems: proteins with secondary structures, transmembrane proteins, proteins with length variation, simulated protein sequences, and ribosomal DNAs.These comparisons illustrate how various MSA methods perform differently based on their underlying assumptions.We also discuss how different alignment statistics should be used for assessing MSAs and their limitations.
Source: InTech eBooks
DOI: 10.5772/22831
Authors: Catherine L., Cory L., Etsuko N.
Institution: University of Nebraska–Lincoln
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W1545488957