Get two dimensional arrayInstead, what if you have to use pyexcel.get_array to do the same:>>> for row in p.get_array(file_name="your_file.xls", start_row=1): ... print(f"{row[2]} are from {row[0]} period ({row[1]})") Machaut, Landini are from Medieval period (c....
However, nanowell array chips do not efficiently scale in cell or sample number; the planar arrays capture cells on a two-dimensional surface and, thus, cannot compete with emulsions or combinatorial indexing using a three-dimensional volume that easily scales to millions of cells. Moreover, ...
In three-dimensional integrated quantum processors40, these individual bolometers may be placed on the wiring layer below the qubits owing to the small footprint of the bolometers. To take the first steps in demonstrating the feasibility of using bolometers for multiplexed qubit readout, we have...
Three-dimensional (3D) imaging of thin, extended specimens at nanometer resolution is critical for applications in biology, materials science, advanced synthesis, and manufacturing. One route to 3D imaging is tomography, which requires a tilt series of a local region. However, capturing images at ...
The full dynamical model was then solved for all genes to obtain a high dimensional velocity vector for every cell. Given that populations of cells may have different mRNA splicing and degradation kinetics, we performed a likelihood ratio test for differential kinetics on the clusters identified ...
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...
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 ...
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)...
Fig. 1: In vivo scCRISPR screening of intratumoral CTLs reveals connectivity of co-functional modules and gene programmes. a, Schematic of the scCRISPR screening strategy.b, Relative ratio (log2(fold-change (FC))) of cells with gene-level perturbation compared with sgNTC. Vertical line, TFs...