Abstract: In one aspect, disclosed herein are new hybridization probes that contain fluorinated carbon tags (F), methods of making these hybridization probes, and methods for using these hybridization probes for affinity capture of the probes both in purification during production and in the enrichment process using fluorous substrates. In certain embodiments, the hybridization probe comprises a) a polynucleotide having a 3? end and a 5? end and comprising about 20 to about 200 nucleotide units and b) one or more fluorinated affinity tags, wherein each affinity tag comprises one or more polyfluorinated carbon chains each comprising 3-30 carbon atoms; wherein the polynucleotide comprises a sequence complementary or substantially complementary to a target sequence within a target nucleic acid.

Abstract: Methods and systems that include training a machine learning model for detecting biological constituents in a sample are provided. A computer-implemented method, and systems executing the method, may include collecting metagenomic data that includes biological constituents obtained from a sample; generating a first molecular data set of covariates; generating a second molecular data set of covariates; generating a training set comprising the first and second covariates as well as combined covariates; and training the machine learning model using aggregate molecular covariates to predict biological constituents from metagenomics data.

Abstract: Systems and methods for identifying conditions in a sample obtain a set of sample sequence reads from the sample. For each respective read, or respective sample contig derived from a respective subset of the set, a corresponding sequence comparison between the respective read or contig and each reference sequence in a set of reference sequences is performed. There is calculated, from these sequence comparisons, a respective probability that the respective read or contig corresponds to a particular reference sequence in the set of reference sequences thereby computing a plurality of probabilities. The presence or an absence of each of the conditions in the sample is identified based at least in part on these probabilities. One condition is identification of a species present in the sample, and the percentage of the genome of this species identified in the reads is provided.

Abstract: Systems and methods for identifying a host of an AMR marker from one or more samples are provided, which include obtaining short-read sequence data derived from one or more samples; identifying one or more AMR markers from the short-read sequence data to obtain short-read metrics, the short-read metrics comprising quantitative metrics such as RPKM, median depth, read count, or others of any one or more of the AMR markers identified in the short-reads; obtaining one or more reference sequence data; identifying one or more AMR markers from the reference sequence data to obtain reference metrics, the reference metrics comprising quantitative metrics such as RPKM, median depth, read count, or others of any one or more of the AMR markers identified in the reference sequence; identifying a host of the one or more AMR markers in the sample when average ratios between the short-read metrics and the reference metrics are below a threshold ratio.

Abstract: Systems and methods for determining an amount of a predefined category are provided. A sample is obtained, including nucleic acids from the predefined category and nucleic acids from a source other than the predefined category. A known quantity of an internal control material comprising nucleic acids is added to the sample. The sample, including the internal control material, is sequenced. A sequencing dataset including sequence reads from the predefined category and sequence reads from the internal control material is obtained. A first read count, normalized using a first target nucleotide length, of sequence reads from the predefined category, and a second read count, normalized using a second target nucleotide length, of sequence reads from the internal control material are determined. The amount of the predefined category in the sample is calculated based on the first read count, the second read count, and the known quantity of the internal control material.

Abstract: A method for reviewing sequencing data for identifying microorganisms in a sample is provided. A request to display an analysis of a result set obtained from sequencing nucleic acids from the sample is received. The result set includes sequencing statistics, nucleotide sequences mapped against microorganism reference sequences, and mapping statistics for the mapping of nucleotide sequences to each respective reference sequence. A first customizable diagnostic template is applied to the result set. The customizable diagnostic template specifies a subset of sequencing statistics, a subset of microorganisms, and a subset of mapping statistics. A customizable user interface is displayed comprising a. review' status, a.

Abstract: Described herein are methods of identifying a plurality of polynucleotides, as well as detecting presence, absence, or abundance of a plurality of taxa in a sample. Also provided are systems for performing methods of the disclosure.

Abstract: Described herein are methods of identifying a plurality of polynucleotides, as well as detecting presence, absence, or abundance of a plurality of taxa in a sample. Also provided are systems for performing methods of the disclosure.

Abstract: The present disclosure provides methods and systems for providing and/or displaying information corresponding to a sample. The information may comprise the identity of one or more microorganisms within the sample and may be based on an analysis of sequencing reads corresponding to the sample.

Abstract: Described herein are methods of identifying a plurality of polynucleotides, as well as detecting presence, absence, or abundance of a plurality of taxa in a sample. Also provided are systems for performing methods of the disclosure.