Multiple sequence alignment (MSA), which is of fundamental importance for comparative genomics, is a difficult problem and error-prone. Therefore, it is essential to measure the reliability of the alignments and incorporate it into downstream analyses. Many studies have been conducted to find the extent, cause and effect of the alignment errors [4], and to heuristically estimate the quality of alignments without using the true alignment, which is unknown [2]. However, it is still unclear whether the heuristically chosen measures are general enough to take into account all alignment errors. In this paper, we present a new alignment reliability score, called PSAR (Probabilistic Sampling-based Alignment Reliability) score.
CITATION STYLE
Kim, J., & Ma, J. (2011). PSAR: Measuring Multiple Sequence Alignment Reliability by Probabilistic Sampling: (Extended Abstract). In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6577 LNBI, pp. 134–135). Springer Verlag. https://doi.org/10.1007/978-3-642-20036-6_14
Mendeley helps you to discover research relevant for your work.