Independent Components Analysis with the JADE algorithm

Rutledge, Douglas N.; Bouveresse, Delphine Jouan-Rimbaud

doi:10.1016/j.trac.2013.03.013

Cited by 185 publications

(98 citation statements)

References 24 publications

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“…This mixing matrix can be used to select signatures among components with distinct gene expression profiles across the set of samples. The R implementation of the core JADE (Joint Approximate Diagonalization of Eigenmatrices) algorithm (Rutledge and Bouveresse 2013; https://cran.r-project.org/ web/packages/JADE/index.htm; https://www.bioconductor.org/ packages/release/bioc/html/MineICA.html) was used along with custom R utilities. The P-value for the knockout-specific (IC2) signature was P = 0.0119 (Mann-Whitney U-test directional P-value).…”

Section: Rna-seq Data Analysismentioning

confidence: 99%

PHF6 regulates phenotypic plasticity through chromatin organization within lineage-specific genes

et al. 2017

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Developmental and lineage plasticity have been observed in numerous malignancies and have been correlated with tumor progression and drug resistance. However, little is known about the molecular mechanisms that enable such plasticity to occur. Here, we describe the function of the plant homeodomain finger protein 6 (PHF6) in leukemia and define its role in regulating chromatin accessibility to lineage-specific transcription factors. We show that loss of Phf6 in B-cell leukemia results in systematic changes in gene expression via alteration of the chromatin landscape at the transcriptional start sites of B-cell-and T-cell-specific factors. Additionally, Phf6KO cells show significant downregulation of genes involved in the development and function of normal B cells, show up-regulation of genes involved in T-cell signaling, and give rise to mixed-lineage lymphoma in vivo. Engagement of divergent transcriptional programs results in phenotypic plasticity that leads to altered disease presentation in vivo, tolerance of aberrant oncogenic signaling, and differential sensitivity to frontline and targeted therapies. These findings suggest that active maintenance of a precise chromatin landscape is essential for sustaining proper leukemia cell identity and that loss of a single factor (PHF6) can cause focal changes in chromatin accessibility and nucleosome positioning that render cells susceptible to lineage transition.

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Section: Rna-seq Data Analysismentioning

confidence: 99%

PHF6 regulates phenotypic plasticity through chromatin organization within lineage-specific genes

et al. 2017

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“…This is done by assuming that the data variables are linear mixtures of some unknown LVs. The LVs are assumed to be non-Gaussian and mutually independent, and are called the independent components of the observed data [106]. Linear ICA can be presented as [Equation (5)]:…”

Section: Independent Component Analysismentioning

confidence: 99%

Multivariate calibration of NIR spectroscopic sensors for continuous glucose monitoring

Goodarzi

Sharma

Ramón

et al. 2015

TrAC Trends in Analytical Chemistry

124

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Diabetes, a disorder in the control of blood-glucose levels, is one of the most serious metabolic diseases worldwide. Among the investigated technologies for continuous glucose monitoring (CGM), near-infrared spectroscopy (NIR) has received the most attention. There have been many attempts to develop NIR-based CGM systems with promising in-vitro results, but they lacked robustness for in-vivo use. We critically review the application of chemometrics for CGM and the research needed. Pre-processing and multivariate-calibration techniques, which allow exploiting expert knowledge on the potential interferences, are possible solutions. The combination and first overtone bands in the ranges 2050-2300 nm and 1500-1800 nm, respectively, are the most informative regions. We therefore recommended selecting the most informative variables and exploiting the available expert knowledge on known interferences in pre-processing or multivariate calibration to develop an NIR-based CGM sensor for in-vivo use.

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“…According to the Central Limit Theorem, the measured signals, which are mixtures of several independent sources, should be ''more Gaussian'' than the source signals. Hence, the objective of ICA is to search for the least Gaussian sources (Rutledge and Jouan-Rimbaud Bouveresse, 2013). Let us suppose a mixed signal gives a data matrix X (r Â c) where r is the number of observed mixed spectra in X and c is the number of points in the signal, or variables corresponding to the matrix columns.…”

Section: Ica By the Jade Algorithmmentioning

confidence: 99%

Application of independent components analysis with the JADE algorithm and NIR hyperspectral imaging for revealing food adulteration

Mishra

Cordella

Rutledge

et al. 2016

Journal of Food Engineering

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a b s t r a c tIn recent years, Independent Components Analysis (ICA) has proven itself to be a powerful signal-processing technique for solving the Blind-Source Separation (BSS) problems in different scientific domains. In the present work, an application of ICA for processing NIR hyperspectral images to detect traces of peanut in wheat flour is presented. Processing was performed without a priori knowledge of the chemical composition of the two food materials. The aim was to extract the source signals of the different chemical components from the initial data set and to use them in order to determine the distribution of peanut traces in the hyperspectral images. To determine the optimal number of independent component to be extracted, the Random ICA by blocks method was used. This method is based on the repeated calculation of several models using an increasing number of independent components after randomly segmenting the matrix data into two blocks and then calculating the correlations between the signals extracted from the two blocks. The extracted ICA signals were interpreted and their ability to classify peanut and wheat flour was studied. Finally, all the extracted ICs were used to construct a single synthetic signal that could be used directly with the hyperspectral images to enhance the contrast between the peanut and the wheat flours in a real multi-use industrial environment. Furthermore, feature extraction methods (connected components labelling algorithm followed by flood fill method to extract object contours) were applied in order to target the spatial location of the presence of peanut traces. A good visualization of the distributions of peanut traces was thus obtained.

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Independent Components Analysis with the JADE algorithm

Cited by 185 publications

References 24 publications

PHF6 regulates phenotypic plasticity through chromatin organization within lineage-specific genes

PHF6 regulates phenotypic plasticity through chromatin organization within lineage-specific genes

Multivariate calibration of NIR spectroscopic sensors for continuous glucose monitoring

Application of independent components analysis with the JADE algorithm and NIR hyperspectral imaging for revealing food adulteration

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