YACHT: an ANI-based statistical test to detect microbial presence/absence in a metagenomic sample.In metagenomics, the study of environmentally associated microbial communities from their sampled DNA, one of the most fundamental computational tasks is that of determining which genomes from a reference database are present or absent in a given sample metagenome.  In this work, we present solutions for these issues by introducing the algorithm YACHT : Y es/No A nswers to C ommunity membership via H ypothesis T esting.  Code implementing this approach, as well as all experiments performed, is available at https://github.com/KoslickiLab/YACHT .
YACHT
YACHT: an ANI-based statistical test to detect microbial presence/absence in a metagenomic sample.In metagenomics, the study of environmentally associated microbial communities from their sampled DNA, one of the most fundamental computational tasks is that of determining which genomes from a reference database are present or absent in a given sample metagenome.  In this work, we present solutions for these issues by introducing the algorithm YACHT : Y es/No A nswers to C ommunity membership via H ypothesis T esting.  Code implementing this approach, as well as all experiments performed, is available at https://github.com/KoslickiLab/YACHT .
YACHT
YACHT: an ANI-based statistical test to detect microbial presence/absence in a metagenomic sample.In metagenomics, the study of environmentally associated microbial communities from their sampled DNA, one of the most fundamental computational tasks is that of determining which genomes from a reference database are present or absent in a given sample metagenome. 
metagenomics
YACHT: an ANI-based statistical test to detect microbial presence/absence in a metagenomic sample.In metagenomics, the study of environmentally associated microbial communities from their sampled DNA, one of the most fundamental computational tasks is that of determining which genomes from a reference database are present or absent in a given sample metagenome.  Furthermore, no tools to date account for the fact that reference databases are often incomplete and rarely, if ever, contain exact replicas of genomes present in an environmentally derived metagenome. 
metagenome
YACHT: an ANI-based statistical test to detect microbial presence/absence in a metagenomic sample.In metagenomics, the study of environmentally associated microbial communities from their sampled DNA, one of the most fundamental computational tasks is that of determining which genomes from a reference database are present or absent in a given sample metagenome.  Furthermore, no tools to date account for the fact that reference databases are often incomplete and rarely, if ever, contain exact replicas of genomes present in an environmentally derived metagenome. 
reference database
YACHT: an ANI-based statistical test to detect microbial presence/absence in a metagenomic sample.In metagenomics, the study of environmentally associated microbial communities from their sampled DNA, one of the most fundamental computational tasks is that of determining which genomes from a reference database are present or absent in a given sample metagenome. 
sample metagenome
While tools exist to answer this question, all existing approaches to date return point estimates, with no associated confidence or uncertainty associated with it. 
confidence
While tools exist to answer this question, all existing approaches to date return point estimates, with no associated confidence or uncertainty associated with it. 
uncertainty
This has led to practitioners experiencing difficulty when interpreting the results from these tools, particularly for low abundance organisms as these often reside in the "noisy tail" of incorrect predictions. 
low abundance organisms
This approach introduces a statistical framework that accounts for sequence divergence between the reference and sample genomes, in terms of average nucleotide identity, as well as incomplete sequencing depth, thus providing a hypothesis test for determining the presence or absence of a reference genome in a sample. 
sequence divergence
This approach introduces a statistical framework that accounts for sequence divergence between the reference and sample genomes, in terms of average nucleotide identity, as well as incomplete sequencing depth, thus providing a hypothesis test for determining the presence or absence of a reference genome in a sample. 
average nucleotide identity
In this work, we present solutions for these issues by introducing the algorithm YACHT : Y es/No A nswers to C ommunity membership via H ypothesis T esting.  This approach introduces a statistical framework that accounts for sequence divergence between the reference and sample genomes, in terms of average nucleotide identity, as well as incomplete sequencing depth, thus providing a hypothesis test for determining the presence or absence of a reference genome in a sample. 
hypothesis test
After introducing our approach, we quantify its statistical power as well as quantify theoretically how this changes with varying parameters. 
statistical power
Subsequently, we perform extensive experiments using both simulated and real data to confirm the accuracy and scalability of this approach. 
real data