Abstract: The present invention provides a computer-implemented method for detecting variant nucleic acid from a cell-free nucleic acid-containing sample. The method comprises (a) providing data representing fragment sizes of nucleic acid fragments obtained from said sample and/or representing a measure of deviation from copy number neutrality of the nucleic acid fragments obtained from said sample; b) processing the data from step a) according to a classification algorithm, wherein said classification algorithm operates to classify sample data into one of at least a first class containing the variant nucleic acid and a second class not containing the variant nucleic acid, based on a plurality of cell-free nucleic acid fragment size features and/or a deviation from copy number neutrality feature; and c) outputting the classification of the sample from step b, thereby determining whether the sample contains the variant nucleic acid or not, or a probability that the sample contains the variant nucleic acid.

Abstract: A method for selective sequencing of a plurality of target regions from a patient is provided. A pool of oligonucleotides comprises a first sub-population targeting the plurality of target regions and a second sub-population. Each member of the first sub-population of oligonucleotides comprises a first sequence that is complementary to one of the plurality of target regions from the patient and an identifier sequence specific to the patient, and each member of the second sub-population of oligonucleotides comprises a first sequence that is complementary to one of the plurality of target regions from a second patient and an identifier sequence specific to the second patient. A test sample from the patient is contacted with the pool, and then contacted with oligonucleotides comprising a sequence that is complementary to the identifier sequence specific to the first patient. The plurality of target regions from the patient are then selected and sequenced.

Abstract: The present invention provides a computer-implemented method for analysing a urine sample from a subject. The method comprises providing the value of one or more cell-free DNA fragment size metrics for said sample, and determining whether the sample has a high or low likelihood of being from a brain cancer patient by providing said values of said cell-free DNA fragment size metrics as input to a machine learning model. The machine learning model is trained to classify sample data into one of at least two classes, the at least two classes comprising a first class having a high likelihood of being from a brain cancer patient and a second class having a low likelihood of being from a brain cancer patient. Methods for diagnosing or screening for brain cancer, detecting recurrence or residual disease, providing a prognosis or selecting a treatment for brain cancer are also described.

Abstract: Described herein is a method for detecting cancer DNA in a test sample of DNA from a patient. In some embodiments, the method may comprise: (a) sequencing multiple aliquots of the test sample to produce, for each aliquot, sequence reads corresponding to two or more target regions that each have one or more sequence variations present within the patient's cancer; (b) for each aliquot, for each target region: i. determining the number of sequence reads that have the sequence variation; ii. determining the total number of sequence reads; and iii. comparing i. and ii. to one or more error probability distribution models for the sequence variation, wherein the one or more models are obtained from DNA that does not contain the sequence variation; and (c) integrating the collective results of step (b) to determine if there is cancer DNA in the test sample.

Abstract: The present invention provides a computer-implemented method for detecting variant nucleic acid from a cell-free nucleic acid-containing sample. The method comprises (a) providing data representing fragment sizes of nucleic acid fragments obtained from said sample and/or representing a measure of deviation from copy number neutrality of the nucleic acid fragments obtained from said sample; b) processing the data from step a) according to a classification algorithm, wherein said classification algorithm operates to classify sample data into one of at least a first class containing the variant nucleic acid and a second class not containing the variant nucleic acid, based on a plurality of cell-free nucleic acid fragment size features and/or a deviation from copy number neutrality feature; and c) outputting the classification of the sample from step b, thereby determining whether the sample contains the variant nucleic acid or not, or a probability that the sample contains the variant nucleic acid.

Abstract: The present invention provides a method for detecting variant cell-free DNA (cfDNA) in a sample obtained from a subject, where analysis of the sample includes a size-selection step which separates out different fragment sizes of DNA. The sample may be a limited volume sample such as a blood, serum or plasma sample of less than 500 ?l (e.g. a blood or plasma sample of about 50 ?l), or other sample that has a low content of cfDNA. The sample may have been stored and/or dried and not have been processed to remove cells or cellular material prior to storage. The size-selection step may comprise filtering-out, depleting or removing genomic DNA (gDNA) fragments of >200 bp, >300 bp, >500 bp, >700 bp, >1000 bp, >1200 bp, >1500 bp, or >2000 bp prior to analysis, e.g. prior to DNA sequencing. The method may further comprise performing an analysis that summarises or combines data across multiple loci.

Abstract: The present invention provides a computer-implemented method for detecting cell-free DNA (cfDNA), such as circulating tumour DNA, in a DNA-containing sample obtained from a patient, the method comprising: (a) providing loci of interest comprising at least 2 mutation-containing loci representative of a tumour of the patient (“patient-specific loci”); (b) providing sequence data comprising sequence reads of a plurality of polynucleotide fragments from a DNA-containing sample from the patient, wherein said sequence reads span said at least 2 mutation-containing loci of step (a); (c) optionally, performing reads collapsing to group the sequence reads into read families; (d) calculating the mutant allele fraction across some or all of said at least 2 patient-specific loci, optionally wherein the mutant allele fraction is calculated by aggregating mutant reads and total reads; (e) classifying the sample as containing or not containing the target cfDNA based on the calculated mutant allele fraction.

Abstract: The present invention provides a method for detecting a genetic variant in a region of interest in a DNA sample comprising (i) determining, for a given sequencing platform, sequencing process and sequencing depth, the distribution of the number of reads supporting a genetic variant or plurality of genetic variants expected to be observed in the sequencing results of amplification reactions due to amplification and sequencing error (read count distribution); (ii) based on the read count distribution determined in step (i), establishing a threshold frequency at or above which the genetic variant must be observed in sequencing results of amplification reactions to assign a positive determination for the presence of the genetic variant in a given amplification reaction; (iii) partitioning the DNA sample into a plurality of replicate amplification reactions, so that the mean number of amplifiable template molecules of the region of interest in a replicate amplification reaction is fewer than the reciprocal of the

Abstract: The present invention provides a method for detecting a genetic variant in a region of interest in a DNA sample comprising (i) determining, for a given sequencing platform, sequencing process and sequencing depth, the distribution of the number of reads supporting a genetic variant or plurality of genetic variants expected to be observed in the sequencing results of amplification reactions due to amplification and sequencing error (read count distribution); (ii) based on the read count distribution determined in step (i), establishing a threshold frequency at or above which the genetic variant must be observed in sequencing results of amplification reactions to assign a positive determination for the presence of the genetic variant in a given amplification reaction; (iii) partitioning the DNA sample into a plurality of replicate amplification reactions, so that the mean number of amplifiable template molecules of the region of interest in a replicate amplification reaction is fewer than the reciprocal of the

Abstract: The present invention provides a process for classification of cancers and tissues of origin through the analysis of the expression patterns of specific microRNAs and nucleic acid molecules relating thereto. Classification according to a microRNA tree-based expression framework allows optimization of treatment, and determination of specific therapy.

Abstract: The present invention provides a process for classification of cancers and tissues of origin through the analysis of the expression patterns of specific microRNAs and nucleic acid molecules relating thereto. Classification according to a microRNA tree-based expression framework allows optimization of treatment, and determination of specific therapy.

Abstract: The present invention provides a process for classification of cancers and tissues of origin through the analysis of the expression patterns of specific microRNAs and nucleic acid molecules relating thereto. Classification according to a microRNA tree-based expression framework allows optimization of treatment, and determination of specific therapy.

Abstract: The present invention provides nucleic acid sequences that are used for identification, classification and diagnosis of specific types of cancers. The nucleic acid sequences can also be used for prognosis evaluation of a subject based on the expression pattern of a biological sample.

Abstract: The present invention provides a process for classification of specific cancers and tumors origin through the analysis of the expression patterns of specific microRNAs and nucleic acid molecules relating thereto. Classification according to a microRNA expression framework allows optimization of treatment, and determination of specific therapy.

Abstract: The present invention provides a method for detecting a genetic variant in a region of interest in a DNA sample comprising (i) determining, for a given sequencing platform, sequencing process and sequencing depth, the distribution of the number of reads supporting a genetic variant or plurality of genetic variants expected to be observed in the sequencing results of amplification reactions due to amplification and sequencing error (read count distribution); (ii) based on the read count distribution determined in step (i), establishing a threshold frequency at or above which the genetic variant must be observed in sequencing results of amplification reactions to assign a positive determination for the presence of the genetic variant in a given amplification reaction; (iii) partitioning the DNA sample into a plurality of replicate amplification reactions, so that the mean number of amplifiable template molecules of the region of interest in a replicate amplification reaction is fewer than the reciprocal of the

Abstract: The present invention provides a method for classification of kidney tumors through the analysis of the expression patterns of specific microRNAs and nucleic acid molecules relating thereto. Classification according to a microRNA expression framework allows optimization of treatment, and determination of specific therapy.

Abstract: The present invention provides a process for classification of specific cancers and tumors origin through the analysis of the expression patterns of specific microRNAs and nucleic acid molecules relating thereto. Classification according to a microRNA expression framework allows optimization of treatment, and determination of specific therapy.

Abstract: The present invention provides a process for classification of cancers and tissues of origin through the analysis of the expression patterns of specific microRNAs and nucleic acid molecules relating thereto. Classification according to a microRNA tree-based expression framework allows optimization of treatment, and determination of specific therapy.

Abstract: The present invention provides nucleic acid sequences that are used for identification and diagnosis of specific cancers. The nucleic acid sequences can also be used for prognosis evaluation of a subject based on the expression profile of a biological sample.

Abstract: The present invention provides a process for classification of cancers and tissues of origin through the analysis of the expression patterns of specific microRNAs and nucleic acid molecules relating thereto. Classification according to a microRNA tree-based expression framework allows optimization of treatment, and determination of specific therapy.