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HapFABIA: identification of very short segments of identity by descent characterized by rare variants in large sequencing data. - Abstract - Europe PMC
Europe PMC is an archive of life sciences journal literature.
High Performance, Cloud and Symbolic Computing in Big-Data problems applied to mathematical modeling of Comparative Genomics | MR.SYMBIOMATH Project | FP7 | CORDIS | European Commission
HapFABIA: Identification of very short segments of identity by descent characterized by rare variants in large sequencing data | Nucleic Acids Research | Oxford Academic
Abstract. Identity by descent (IBD) can be reliably detected for long shared DNA segments, which are found in related individuals. However, many studies contain
Guidance Documents Please download IALA Technical documents Catalogue Edition 2.0 that covers the technical guidance and contains an over-all view of the standards, recommendations, guidelines, and model courses in force […]
How DTW (Dynamic Time Warping) algorithm works - YouTube
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In this video we describe the DTW algorithm, which is used to measure the distance between two time series. It was originally proposed in 1978 by Sakoe and Chiba for speech recognition, and it has been used up to today for time series analysis. DTW is one of the most used measure of the similarity between two time series, and computes the optimal global alignment between two time series, exploiting temporal distortions between them.
Source code of graphs available at
https://github.com/tkorting/youtube/blob/master/how-dtw-works.m
The presentation was created using as references the following scientific papers:
1. Sakoe, H., Chiba, S. (1978). Dynamic programming algorithm optimization for spoken word recognition. IEEE Trans. Acoustic Speech and Signal Processing, v26, pp. 43-49.
2. Souza, C.F.S., Pantoja, C.E.P, Souza, F.C.M. Verificação de assinaturas offline utilizando Dynamic Time Warping. Proceedings of IX Brazilian Congress on Neural Networks, v1, pp. 25-28. 2009.
3. Mueen, A., Keogh. E. Extracting Optimal Performance from Dynamic Time Warping. available at: http://www.cs.unm.edu/~mueen/DTW.pdf
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How to install AFNI for nipype · Issue #1067 · nipy/nipype
Hi, I am currently writing some packages for AFNI/FSL/SPM for my favourite distro (Gentoo). I plan to use these toolkits via nipype. On the example of AFNI: I am currently placing everything into /...
MSIWarp: A General Approach to Mass Alignment in Mass Spectrometry Imaging | Analytical Chemistry
Mass spectrometry imaging (MSI) is a technique that provides comprehensive molecular information with high spatial resolution from tissue. Today, there is a strong push toward sharing data sets through public repositories in many research fields where MSI is commonly applied; yet, there is no standardized protocol for analyzing these data sets in a reproducible manner. Shifts in the mass-to-charge ratio (m/z) of molecular peaks present a major obstacle that can make it impossible to distinguish one compound from another. Here, we present a label-free m/z alignment approach that is compatible with multiple instrument types and makes no assumptions on the sample’s molecular composition. Our approach, MSIWarp (https://github.com/horvatovichlab/MSIWarp), finds an m/z recalibration function by maximizing a similarity score that considers both the intensity and m/z position of peaks matched between two spectra. MSIWarp requires only centroid spectra to find the recalibration function and is thereby readily applicable to almost any MSI data set. To deal with particularly misaligned or peak-sparse spectra, we provide an option to detect and exclude spurious peak matches with a tailored random sample consensus (RANSAC) procedure. We evaluate our approach with four publicly available data sets from both time-of-flight (TOF) and Orbitrap instruments and demonstrate up to 88% improvement in m/z alignment.
New Experiments on ICP-Based 3D Face Recognition and Authentication | Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
