A method of correcting an expression level(s) of a target small RNA(s) for comparative analysis of the expression level(s) in a plurality of samples includes adding at least one kind of standard substance to each of the plurality of samples, extracting nucleic acids from each sample to obtain a nucleic acid sample; measuring the amounts of the target small RNA(s) and the standard substance(s) present in each extracted nucleic acid sample; obtaining a representative value from the measured value(s) of the amount(s) of the standard substance(s) extracted; obtaining the difference or the ratio between a reference value arbitrarily set in connection with the amount(s) of the standard substance(s) extracted and the representative value of the standard substance(s) obtained for each sample; and correcting the expression level(s) of the target small RNA(s).

Methods for identifying and classifying differences between biological samples are based on replication timing (RT) data. By comparing RT data for a test sample(s) to RT data for already characterized samples, one can identify differences and profile any new cell type or disease. These new methods allow for the detection of all the changes between distinct samples, many of which would escape detection by previous methods that discard any features showing any intra-sample variation.

Technology provided herein relates in part to methods, processes, machines and apparatuses for detecting genetic variations. In some embodiments, the technology is related to non-invasive assessment of aneuploidies.

This disclosure provides methods and compositions for removing one or more high abundance species from a plurality of nucleic acid molecules. In some embodiments, the methods and compositions can be used for normalizing nucleic acid libraries. In some embodiments, molecular labels are used in conjunction with the methods and compositions disclosed herein to improve sequencing efficiency.

The present invention relates to compositions and methods for molecular profiling and diagnostics for genetic disorders and cancer, including but not limited to gene expression product markers associated with cancer or genetic disorders. In particular, the present invention provides algorithms and methods of classifying cancer, for example, thyroid cancer, methods of determining molecular profiles, and methods of analyzing results to provide a diagnosis.

A diagnostic analysis method and system is provided for identifying a microorganism from a genome sequence. Partially or fully assembled microbial genomes or short reads from whole-genome sequencing of microbial genomes are processed into a 4 MB Boolean array while preserving 1% of the genomic information in a way that allows for rapid comparison of a query genome to a large reference database. This represents a critical savings in storage space and speed by which large reference libraries can be queried.

Methods, software, and systems are provided for determining the probability of an overlap set of entities having an overlap size, where the overlap set is independently selected from two sets of non-identical entities. Applications of the invention to microarrays are provided. Probability distributions are provided for determining the probability that the size of an overlap gene set from two different microarrays occurs by chance. Microarray analysis for determining the size of a statistically significant overlap gene set given two different microarrays is described. Overlap set size probability determinations that account for the total number of genes in two different microarrays and not just the common genes are described.

Provided herein are methods for determining the presence of a mutant of target polynucleotides in a sample solution by contacting the sample solution and a reference solution containing the target nucleotide with identical probe sets and then comparing the hybridization intensities of corresponding probes of the probe sets. The probes provide a varying complementarity to the target sequence so that a range of hybridization intensities for the hybridization between the target polynucleotide and the probes is covered.

The present invention relates to peptides, proteins, nucleic acids and cells for use in immunotherapeutic methods. In particular, the present invention relates to the immunotherapy of cancer. The present invention furthermore relates to tumor-associated T-cell peptide epitopes, alone or in combination with other tumor-associated peptides that can for example serve as active pharmaceutical ingredients of vaccine compositions that stimulate anti-tumor immune responses, or to stimulate T cells ex vivo and transfer into patients. Peptides bound to molecules of the major histocompatibility complex (MHC), or peptides as such, can also be targets of antibodies, soluble T-cell receptors, and other binding molecules.

Methods, computer-accessible medium, and systems for generating a genome wide probe map and/or a genome wide haplotype sequence are provided. In particular, a genome wide probe map can be generated by obtaining a plurality of detectable oligonucleotide probes hybridized to at least one double stranded nucleic acid molecule cleaved with at least one restriction enzyme, and detecting the location of the detectable oligonucleotide probes. For example, genome wide haplotype sequence can be generated by analyzing at least one genome wide restriction map in conjunction with at least one genome wide probe map to determine distances between restriction sites of the genome wide restriction map(s) and locations of detectable oligonucleotide probes of the genome wide probe map(s) and defining a consensus map indicating restriction sites based on the genome wide restriction map(s) and/or locations of detectable oligonucleotide probes based on each of the genome wide probe map(s).