Abstract: The present invention relates to methods of determining a cancer treatment prognosis for a subject in need thereof by evaluating epigenetic and genetic changes within a tumor sample from the subject. The present invention further provides methods of treating cancer in a subject by evaluating epigenetic and genetic changes within a tumor sample from the subject. In addition, the present invention provides methods of screening test agents to identify agents that decrease tumor cell plasticity.

Abstract: A system and method for determining the exact pair of alleles corresponding to polymorphic genes from sequencing data and for using the polymorphic gene information in formulating an immunogenic composition. Reads from a sequencing data set mapping to the target polymorphic genes in a canonical reference genome sequence, and reads mapping within a defined threshold of the target gene sequence locations are extracted from the sequencing data set. Additionally, all reads from the set data set are matched against a probe reference set, and those reads that match with a high degree of similarity are extracted. Either one, or a union of both these sets of extracted reads are included in a final extracted set for further analysis. Ethnicity of the individual may be inferred based on the available sequencing data which may then serve as a basis for assigning prior probabilities to the allele variants. The extracted reads are aligned to a gene reference set of all known allele variants.

Abstract: The invention relates to method for identifying significantly mutated genes includes determining a false discovery rate for each of the genes. The method may include estimating local mutation rates for the genes by converting each covariate to a centered and normalized score. The method may also include estimating a local background mutation rate for each of the genes, which may be estimated from silent and/or noncoding mutations of each of the genes itself. In some embodiments, the local background mutation rate may be estimated additionally from one or more neighbor genes in a covariate space. Related systems, techniques, and articles are also encompassed by the present invention.

Abstract: Methods and apparatus for inferring purity and ploidy from a sample of cells (e.g., a sample comprising cancer and normal cells) are described. Copy number per cell of interest (e.g., cancer cell) is determined by optimizing purity and ploidy for the sample based, at least in part, on relative copy number profile information. One or more likelihood fit scores are determined for each of a plurality of candidate solutions generated by the methods described herein. A solution is selected based, at least in part on the likelihood fit score(s) and the copy number per cancer cell is determined in accordance with the selected solution.

Abstract: A system, method, and computer program product for detecting variants from sequencing data. Aligned sequencing data can be provided and filters can be applied to the aligned sequencing data. The filtered data can be used as input, and a first classifier can be applied to determine if any alteration is present beyond an expected threshold due to a sequencing error and candidate variants can be identified. The identified candidate variants can be passed through additional filters to remove false positives. A somatic status of the filtered candidate variants can be determined using a second classifier. The related apparatus, systems, techniques and articles are also described.

Abstract: The present invention provides methods and devices related to markers (or biomarkers) associated with chronic lymphocytic leukemia (CLL). Examples of these markers include drivers of CLL progression. The invention contemplates, inter alia, detecting the clonal, including subclonal, profile of CLL in a subject and the presence (or absence) of subclonal driver mutations, and utilizing this information in predicting disease progression, need, timing and/or nature of treatment regimen, and likelihood and frequency of relapse.

Abstract: Method, system and an article of manufacture for clustering and thereby identifying predefined antigens reactive with undetermined immunoglobulins of sera derived from patient subjects in need of diagnosis of disease or monitoring of treatment.

Abstract: Method, system and an article of manufacture for clustering and thereby identifying predefined antigens reactive with undetermined immunoglobulins of sera derived from patient subjects in need of diagnosis of disease or monitoring of treatment.

Abstract: Method, system and an article of manufacture for clustering and thereby identifying predefined antigens reactive with undetermined immunoglobulins of sera derived from patient subjects in need of diagnosis of disease or monitoring of treatment.

Abstract: Method, system and an article of manufacture for clustering and thereby identifying predefined antigens reactive with undetermined immunoglobulins of sera derived from patient subjects in need of diagnosis of disease or monitoring of treatment.

Abstract: Method, system and an article of manufacture for clustering and thereby identifying predefined antigens reactive with undetermined immunoglobulins of sera derived from patient subjects in need of diagnosis of disease or monitoring of treatment.

Abstract: A novel coupled two-way clustering approach to gene microarray data analysis, for identifying subsets of the genes and samples, such that when one of these items is used to cluster the other, stable and significant partitions emerge. The method of the present invention preferably uses iterative clustering in order to execute this search in an efficient way. This approach is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method of the present invention was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on these subsets, partitions and correlations were found that were masked and hidden when the full data set was used in the analysis.

Abstract: A novel coupled two-way clustering approach to gene microarray data analysis, for identifying subsets of the genes and samples, such that when one of these items is used to cluster the other, stable and significant partitions emerge. The method of the present invention preferably uses iterative clustering in order to execute this search in an efficient way. This approach is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method of the present invention was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on these subsets, partitions and correlations were found that were masked and hidden when the full data set was used in the analysis.

Abstract: A novel coupled two-way clustering approach to gene microarray data analysis, for identifying subsets of the genes and samples, such that when one of these items is used to cluster the other, stable and significant partitions emerge. The method of the present invention preferably uses iterative clustering in order to execute this search in an efficient way. This approach is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method of the present invention was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on these subsets, partitions and correlations were found that were masked and hidden when the full data set was used in the analysis.

Abstract: Method, system and an article of manufacture for clustering and thereby identifying predefined antigens reactive with undetermined immunoglobulins of sera derived from patient subjects in need of diagnosis of disease or monitoring of treatment.

Abstract: A novel coupled two-way clustering approach to gene microarray data analysis, for identifying subsets of the genes and samples, such that when one of these items is used to cluster the other, stable and significant partitions emerge. The method of the present invention preferably uses iterative clustering in order to execute this search in an efficient way. This approach is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method of the present invention was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on these subsets, partitions and correlations were found that were masked and hidden when the full data set was used in the analysis.