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Shotgun metagenomics is a powerful platform to characterize human microbiomes. However, to translate such survey data into consumer-relevant products or services, it is critical to have a robust metagenomics workflow. We present a tool - spike-in DNA - to assess performance of metagenomics workflows. The spike-in is DNA from two organisms - Alivibrio fischeri and Rhodopseudomonas palustris, in a ratio of 4:1 added to samples before DNA extraction. With a valid workflow, the output ratio of relative abundances of these organisms should be close to 4. This expectation was tested in samples of varying diversities (n = 110), and the mean ratio was 4.73 (99% CI [4.0, 5.24]). We anticipate this tool to be a relevant community resource for assessing the quality of shotgun metagenomics workflows and thereby enable robust characterization of microbiomes.

When small biological samples are collected by microdissection or other methods, amplification techniques are required to provide sufficient target for hybridization to expression arrays. One such technique is to perform two successive rounds of T7-based in vitro transcription. However the use of random primers, required to regenerate cDNA from the first round of transcription, results in shortened copies of cDNA from which the 5' end is missing. In this paper we describe an experiment designed to compare the quality of data obtained from labeling small RNA samples using the Affymetrix Two-Cycle Eukaryotic. Target Labeling procedure to that of data obtained using the One-Cycle Eukaryotic Target Labeling protocol. We utilized different preprocessing algorithms to compare the data generated using both labeling methods and present a new algorithm that improves upon existing ones in this setting.