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Theodore Mikheev
Theodore Mikheev

Download the Matrix Soundtrack Collection: All the Music from the Movies


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The dataset from Fadista et al. (2014)contains raw read counts data from bulk RNA-seq of human pancreaticislets to study glucose metabolism in healthy and hyper-hypoglycemicconditions. For the purpose of this vignette, the dataset ispre-processed and made available on the datadownload page. In addition to read counts, this dataset alsocontains HbA1c levels, BMI, gender and age information for eachsubject.


The single cell data are from Segerstolpe etal. (2016), which constrains read counts for 25453 genes across2209 cells. Here we only include the 1097 cells from 6 healthy subjects.The read counts are available on the datadownload page, in the form of anSingleCellExperiment.


The dataset GEOentry (GSE81492) (see Beckerman et al.2017) contains raw RNA-seq and sample annotation data. For thepurpose of this vignette, we will use the read counts dataMousebulkeset.rds from the datadownload page.


The single cell data are from GEOentry (GSE107585) (see Park et al.2018), which constrains read counts for 16273 genes across 43745cells. Due to the space limitation of Github, only a subset of the readcounts Mousesubeset.rds are available on the data download page, in the form of anExpressionSet. This subset contains 16273 genes across10000 cells.


In previous MuSiCestimation procedure, the first step is to produce design matrix,cross-subject mean of relative abundance, cross-subject variance ofrelative abundance and average library size from single cell reference.These are taken care of by the function music_basis. Theessential inputs of music_basisare:


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We then select genes that are differentially expressed within clusterC3 (Epithelial cells) and C4 (Immune cells),available on data download page. Functionmusic_prop.clusteris used for estimation with pre-clustering of cell types. The essentialinputs are the same as music_prop except two unique inputs:groups and group.markers. groupspasses the column name of higher-cluster in phenoData. The intra-clusterdifferentially expressed genes are passed bygroup.marker.


Benchmark dataset is constructed by summing up single cell data fromXinT2D.eset. The artificial bulk data is constructedthrough function bulk_construct.The inputs are single cell dataset, cluster name(clusters), sample name (samples) and selectedcell type (select.ct). bulk_constructreturns a ExpressionSet of artificial bulk datasetBulk.counts and a matrix of real cell type countsnum.real.


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The PLENA matrix System brings the benefits of the latest DSP technology to the fore. All DSP features of the PLENA matrix System can be accessed easily through a user-friendly user-friendly Windows GUI that searches the network automatically so there is no need to remember IP addresses. The Windows GUI is designed to give installers maximum control over the setup, while the iPad/iPhone GUI is designed for simplicity and ease of use for the end user. Both give end users the ability to select their own background music source and mix any microphone/line input without affecting other zones in the system.


There is a lot going on in your average gym these days. A yoga class in one studio, a squash game in another, a Zumba class upstairs and people hanging out in the restaurant and café. The PLENA matrix can handle it all with superbly tailored voice announcements and professional-level audio sound per zone.


With its stylish design and convenient iPad control, the PLENA matrix is all about the user experience: control a source selection from your iPad during the yoga class; page some extra help for the front desk or tap the wall station to start up the pre-game soundtrack. And the best part? Thanks to its prime energy-saving features, it pays for itself in the long run.


The right type of background or live music can make or break a dining experience. In popular spots, a quality audio and voice announcement system that can be heard loud and clear in noisy bars, dining areas and waiting areas is essential to set the right mood as well to get the guests to their tables and keep the waiting list short. In a busy restaurant with different sections and dining rooms, this can be challenging. But not for the PLENA matrix. This stylish system packs enough powerful audio quality to hit exactly the right notes for the perfect dining experience.


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