millions of cells. Moreover, unless combined with multiplexing13,14, nanowell chips are poorly suited for processing many separate samples because they require one array per sample and thus hundreds of arrays fo
In particular, SATURN integrates scRNA-seq datasets generated from different species with different genes by mapping them to a joint low-dimensional embedding space using gene expression and protein representations. SATURN takes as input: (i) scRNA-seq count data from one or multiple species, (ii)...
Get two dimensional arrayInstead, what if you have to use pyexcel.get_array to do the same:>>> for row in p.iget_array(file_name="your_file.xls", start_row=1): ... print(f"{row[1]} of {row[0]} has {row[2]} mg") venti(20 oz) of Starbucks Coffee Blonde Roast has ...
Although feature selection is a common preprocessing step in single-cell analysis72with the potential to reveal cell-type transitions that would have been masked in the original high-dimensional feature space45, there has been no systematic evaluation of feature selection method performance on identifyin...
While several commercial platforms have enabled researchers to use single-cell sequencing methods with relative ease and at reasonable cost, the analysis of the high-dimensional scRNA-seq data still remains challenging [6,7]. The main technical downside of single-cell sequencing that impedes downstream...
First, when two lines are coplanar in 3D, the projected 2D lines are also coplanar. In addition, when the intersection of a three-dimensional coplanar pair is projected onto a two-dimensional image, the intersection of the projection is also the intersection of a three-dimensional coplanar pair...
The variable genes were projected onto a low-dimensional subspace using principal component analysis. The number of principal components (Npcs) were selected based on inspection of the plot of variance explained (Npcs = 20). A shared-nearest-neighbors graph was constructed based with metric the ...
Diffusion maps for high-dimensional single-cell analysis of differentiation data. Bioinformatics. 2015;31(18):2989–98. https://doi.org/10.1093/bioinformatics/btv325. Article PubMed CAS Google Scholar Rizvi AH, Camara PG, Kandror EK, Roberts TJ, Schieren I, Maniatis T, et al. Single-cell...
(which depends on the mapping case, for example 200 µm when mapping with the Allen Brain Atlas, individual cells when mapping with MERFISH, and so on), and index the voxels in an arbitrary one-dimensional fashion. We then introduce two quantities: the\(n_{voxels} \times n_{genes}...
Notably, our approach captures the full spectrum of cell states in the data, including rarer states. We base SEACells on a few key assumptions: (1) single-cell profiling data can be approximated by a lower-dimensional manifold (phenotypic manifold); (2) much of the observed variability ...