New paper accepted: Megraft

Yesterday, our paper on Megraft – a software tool to graft ribosomal small subunit (16S/18S) fragments onto full-length SSU sequences – became available as an accepted online early article in Research in Microbiology. Megraft is built upon the notion that when examining the depth of a community sequencing effort, researchers often use rarefaction analysis of the ribosomal small subunit (SSU/16S/18S) gene in a metagenome. However, the SSU sequences in metagenomic libraries generally are present as fragmentary, non-overlapping entries, which poses a great problem for this analysis. Megraft aims to remedy this problem by grafting the input SSU fragments from the metagenome (obtained by e.g. Metaxa) onto full-length SSU sequences. The software also uses a variability model which accounts for observed and unobserved variability. This way, Megraft enables accurate assessment of species richness and sequencing depth in metagenomic datasets.

The algorithm, efficiency and accuracy of Megraft is thoroughly described in the paper. It should be noted that this is not a panacea for species richness estimates in metagenomics, but it is a huge step forward over existing approaches. Megraft shares some similarities with EMIRGE (Miller et al., 2011), which is a software package for reconstruction of full-length ribosomal genes from paired-end Illumina sequences. Megraft, however, is set apart in that it has a strong focus on rarefaction, and functions also when the number of sequences is small, which is often the case in 454 and Sanger-based metagenomics studies. Thus, EMIRGE and Megraft seek to solve a roughly similar problem, but for different sequencing technologies and sequencing scales.

Megraft is available for download here, and the paper can be read here.

  1. Bengtsson, J., Hartmann, M., Unterseher, M., Vaishampayan, P., Abarenkov, K., Durso, L., Bik, E.M., Garey, J.R., Eriksson, K.M., Nilsson R.H. (2012). Megraft: A software package to graft
  2. Miller, C. S., Baker, B. J., Thomas, B. C., Singer, S. W., & Banfield, J. F. (2011). EMIRGE: reconstruction of full-length ribosomal genes from microbial community short read sequencing data. Genome Biology, 12(5), R44. doi:10.1186/gb-2011-12-5-r44