LOCAS - A Low Coverage Assembler for Resequencing Figure 5. Number of detected insertion regions in homology-guided assembly on simulated data. For the artificial A. thaliana strain in the simulated resequencing study, the total insertion regions in the target genome are plotted for different lengths of these regions. In addition, the number of error-free regions assembled by VELVET and by SUPERLOCAS are shown. doi:10.1371/journal.pone.0023455.g005 the blocks were performed separately using the assembly tools LOCAS, ABySS, EULER-SR, VELVET and SOAPdenovo. Besides other measures (see Methods), we primarily compared the N50 size averaged over all local assemblies, denoted as avgN50, and the average error rate of the contigs, denoted as avgERR. In our study, the N50 size is defined as the length of the longest contig such that all contigs of equal or longer length cover at least 50% of the positions of the block sequence. For the calculation of avgN50, we considered only valid contigs that have a global alignment to the target sequence with at most 10% mismatches. The error rate is the total number of errors divided by total length of all contigs. The total number of errors comprises the number of mismatches in the alignment of all valid contigs plus the lengths of other contigs. We ran all assemblers using a wide range of parameter settings to show the achievable avgN50 and avgERR values with the respective assembler (see Table S1). This is a common approach to optimize the assembly. For example the method is implemented in VelvetOptimizer to be used for VELVET. The results are shown in Figure 3. For avgERR values lower than 1.5%, LOCAS performed best with a maximum avgN50 size of 4,558 bp. For an avgERR higher than 1.5%, VELVET performed best with a maximum avgN50 size of 5,500 bp. EULER-SR performed well with respect to avgN50 size, but had a high avgERR of at least 5%. The avgERR values of ABySS were with at most 1.2% very low, but the tool showed an avgN50 size of at most 2,577 bp. The avgERR values were even lower for SOAPdenovo, while its avgN50 size was the lowest for all assemblers with a maximum of 1,991 bp. We also examined CPU time and RAM needed to assemble the whole data set for each tool. The best performing method regarding CPU time was VELVET with 10 min in average, followed by LOCAS with 19 min, SOAPdenovo with 22 min and EULER-SR with 140 min. LOCAS and EULER-SR used only 18 MB of RAM, VELVET used 87 MB and SOAPdenovo used 236 MB. (See Figure S1 and S2 for results of this performance study with a sequencing depth of 56 and for the fourth chromosome, respectively.) Evaluation of Homology-Guided Assembly To evaluate performance in a homology-guided assembly approach, we simulated a resequencing study of an artificial A. thaliana strain using a sequencing depth of 7.56. First, we artificially generated a target genome by introducing SNPs, insertions and deletions into the reference sequence (see Text S1). Then we used this target genome to simulate Illumina reads similar to the previous study. Reads were aligned to the reference genome and partitioned into blocks of 25 kb length using SHORE [6], a short read analysis framework supporting several alignment tools like BWA [27], Bowtie [28] and GenomeMapper. For this study, we preferred GenomeMapper [29] to the other tools because it allows for high edit distances including gaps and has a high sensitivity thus improving homology information generated by read alignments in highly diverged regions. PLoS ONE | www.plosone.org 6 August 2011 | Volume 6 | Issue 8 | e23455