A method to correct amplification bias in amplicon sequencing is disclosed. Amplification efficiency is not constant among different loci in a sample, nor for the same locus in different samples. Differences in 3′-end stability, primer Tm, amplicon length, amplicon GC content, and GC content of amplicon flanking regions all may contribute to amplification bias. Such bias interferes with accurate calculation of copy number for a genomic region of interest and hinders the application of amplicon sequencing for detection of minor copy number variation. The methods of the invention allow correction of amplification bias and enable detection of minor copy number variation using amplicon sequence data.

A system, a method and a non-transitory computer readable storage medium for base calling are described. The base calling method includes processing through a neural network first image data comprising images of clusters and their surrounding background captured by a sequencing system for one or more sequencing cycles of a sequencing run. The base calling method further includes producing a base call for one or more of the clusters of the one or more sequencing cycles of the sequencing run.

Techniques are provided for generating an array-specific range of Tm values to be used for calling a sample in a given array positive or negative for a target nucleic acid sequence. A sample well in an array is provided with a control sample containing a control nucleic acid sequence. The control sample is amplified by thermal cycling the sample well. A Tm value for the control sample is identified and compared to an expected Tm value for the control nucleic acid sequence to calculate a relationship between the identified control Tm value and the expected control Tm value. By applying this relationship to an expected Tm value for a target nucleic acid sequence, an array-specific range of Tm values for the target nucleic acid sequence is generated and can be used for calling an experimental sample in the same array positive or negative for the target nucleic acid sequence.

Techniques are provided for generating an array-specific range of Tm values to be used for calling a sample in a given array positive or negative for a target nucleic acid sequence. A sample well in an array is provided with a control sample containing a control nucleic acid sequence. The control sample is amplified by thermal cycling the sample well. A Tm value for the control sample is identified and compared to an expected Tm value for the control nucleic acid sequence to calculate a relationship between the identified control Tm value and the expected control Tm value. By applying this relationship to an expected Tm value for a target nucleic acid sequence, an array-specific range of Tm values for the target nucleic acid sequence is generated and can be used for calling an experimental sample in the same array positive or negative for the target nucleic acid sequence.

A method is used for the qualitative evaluation of real-time PCR data, where a time/PCR amplification plot of an associated sample is classified as a negative plot or as a positive plot. The method involves providing a real-time PCR amplification plot to be classified, plotting at least 20 successive amplitude values of corresponding successive PCR cycle indices of the sample. Next, a quality metric is determined, on the basis of the at least one amplitude value. A first criterion is determined by a comparison of the quality metric with a first standard value. A sequence of values is then determined, which indicates a gradient of the PCR amplification plot to be classified, and a second criterion is determined as to whether the sequence of values exceeds a second standard value. Finally, the real-time PCR amplification plot is classified as a positive plot if all the criteria given above are satisfied.

A method is used for the qualitative evaluation of real-time PCR data, where a time/PCR amplification plot of an associated sample is classified as a negative plot or as a positive plot. The method involves providing a real-time PCR amplification plot to be classified, plotting at least 20 successive amplitude values of corresponding successive PCR cycle indices of the sample. Next, a quality metric is determined, on the basis of the at least one amplitude value. A first criterion is determined by a comparison of the quality metric with a first standard value. A sequence of values is then determined, which indicates a gradient of the PCR amplification plot to be classified, and a second criterion is determined as to whether the sequence of values exceeds a second standard value. Finally, the real-time PCR amplification plot is classified as a positive plot if all the criteria given above are satisfied.

A method for identifying a base in nucleic acid, a computer-readable storage medium, a computer program product, and a system. The method for identifying a base in nucleic acid comprises: mapping a coordinate of each bright spot in a bright spot set corresponding to a template onto an image to be inspected, and determining the position of a corresponding coordinate on said image (S11); determining the intensity of a signal at the position of the corresponding coordinate on said image, the intensity being a corrected intensity (S21); and comparing the intensity of the signal at the position of the corresponding coordinate on said image with the size of a first preset value, and determining a base type corresponding to the position on the basis of the comparison result, so as to achieve base calling (S31). The method may quickly and accurately identify a base, and achieve the determination of an order of nucleotides/bases of at least part of a sequence of a template.

Disclosed herein are methods for the direct readout of proteoforms and complexes thereof, such as immunoglobulins. The method may comprise ionizing a sample with an ionizer, wherein the sample comprises a mixture of different proteoforms or complexes thereof; detecting a multiplicity of ions generated by the ionization of the sample with a current detector; determining ion masses for each of the multiplicity of ions detected with the current detector with a mass analyzer; generating a mass-domain spectrum from the ion masses with the mass analyzer. The method may also comprise determining one or more metrics capturing the heterogeneity or relative abundance of proteoforms.

A method for identifying by mass spectrometry an unknown microorganism subgroup among a set of reference subgroups, including a step of constructing one knowledgebase and one classifying model per associated subgroup on the basis of the acquisition of at least one set of learning spectra of microorganisms identified as belonging to the subgroups of a group and including: constructing an adjusting model allowing mass-to-charge offsets of the acquired spectra to be corrected on the basis of reference masses-to-charges that are common to the various subgroups; adjusting the masses-to-charges of all of the lists of peaks of the learning spectra and constructing one classifying model per subgroup and the associated knowledgebase on the basis of the adjusted learning spectra.

A method for identifying by mass spectrometry an unknown microorganism subgroup among a set of reference subgroups, including a step of constructing one knowledgebase and one classifying model per associated subgroup on the basis of the acquisition of at least one set of learning spectra of microorganisms identified as belonging to the subgroups of a group and including: constructing an adjusting model allowing mass-to-charge offsets of the acquired spectra to be corrected on the basis of reference masses-to-charges that are common to the various subgroups; adjusting the masses-to-charges of all of the lists of peaks of the learning spectra and constructing one classifying model per subgroup and the associated knowledgebase on the basis of the adjusted learning spectra.