Supplementary Information for “ARK: Aggregation of Reads by K-means for Estimation of Bacterial Community Composition”.

This supporting information is available online. This supplementary material is included to address eight major points:

To compare ARK with the best performing bacterial community composition method to date, called BEBaC [8]. BEBaC employs a Bayesian estimation clustering framework along-with a stochastic search and sequence alignment.

To investigate the important question of finding the number of regions Q in ARK.

To independently verify ARK in two different geographic regions ((1) Sweden and Finland, and (2) USA) and also using different datasets.

To detail genera-level reconstructions of ARK SEK, ARK Quikr, and RDP’s NBC.

To detail the primers used to obtain the data in the main text.

To demonstrate the results are qualitatively independent of the error correction method chosen.

To detail the effect of changing the k-mer size.

To investigate the behavior of each method when sister taxa are excluded from the training database.

To compare ARK with the best performing bacterial community composition method to date, called BEBaC [8]. BEBaC employs a Bayesian estimation clustering framework along-with a stochastic search and sequence alignment.
To investigate the important question of finding the number of regions Q in ARK.
To independently verify ARK in two different geographic regions ((1) Sweden and Finland, and (2) USA) and also using different datasets.
To detail genera-level reconstructions of ARK SEK, ARK Quikr, and RDP’s NBC.
To detail the primers used to obtain the data in the main text.
To demonstrate the results are qualitatively independent of the error correction method chosen.
To detail the effect of changing the k-mer size.
To investigate the behavior of each method when sister taxa are excluded from the training database.
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