Figure 3.

Number of sequences required for taxonomic classification of samples with varying diversity. A series of samples were chosen to assess the effect of library complexity on the accuracy of taxonomy assignments and estimation of diversity of bacterial populations. Kefir represents the lowest point in the bacterial diversity spectrum, followed by a patient affected by Crohn's disease (CD), another one recovered from C. difficile infection (C. diff), a healthy individual (Hthy1) and three artificial mixes of bacteria (Mix7-9). (A,B) Libraries were randomly sampled at depths of 500, 1000, 5000, 10,000, 50,000 and 100,000 reads. End1 16S rRNA gene sequences were classified with QIIME using the closed reference method to cluster OTUs and a similarity threshold of 97%. Paired-end shotgun metagenomics sequences were aligned with LAST and taxonomically classified with MEGAN5. Each random sampling was repeated 20 times. As an example, the relative abundance of taxa for one of these samplings at a depth of 1000 or 50,000 sequences is presented for 16S and shotgun metagenomics libraries. A white asterisk indicates a group of bacterial sequences identified as Citrobacter in the shotgun panel and Klebsiella in the 16S panel. Bifidobacterium is indicated with a white plus sign. Propionibacterium is indicated with a white circle. (C,D) For each taxa detected and for each random sample, the proportion error was calculated as the difference between the proportion that each taxon represented in the whole library (i.e., with the maximum number of reads) and in the random sample. This difference was weighted by the proportion that each taxon represented in the whole library. We present the arithmetic mean of all weighted differences for each of the 20 random samples.