[PDF] Top 20 Splatter: simulation of single cell RNA sequencing data
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Splatter: simulation of single cell RNA sequencing data
... Camp data (many cell types) and the full-length protocols used by both may have contributed to Splat’s poorer perform- ...Camp data. Interestingly, the Simple simulation was the best performer ... See full document
15
Simulation based benchmarking of isoform quantification in single cell RNA seq
... the simulation method) ...or Splatter and Poly- ester were used to generate the simulated ...on single-cell RNA-seq data, care needs to be taken when interpreting this ... See full document
14
EmptyDrops: distinguishing cells from empty droplets in droplet based single cell RNA sequencing data
... a simulation based on a real dataset containing peripheral blood mononuclear cells (PBMCs), Empty- Drops detected the most cells from both groups ...little RNA have similar total counts as barcodes ... See full document
9
Application of single cell RNA sequencing in optimizing a combinatorial therapeutic strategy in metastatic renal cell carcinoma
... sensitivity data as a training set [31]. For the PDX- mRCC and pRCC bulk cell population samples, we found strong positive correlations between predicted and mea- sured drug sensitivity ...all single ... See full document
17
MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single cell RNA sequencing data
... in cell size (among other factors) [11], as well as technical variation due to fac- tors such as cell viability and efficiency in first strand synthe- ...MAIT data set and 4.8 % in the mDC ... See full document
13
A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications
... of single nuclei for RNA-seq [34–36] and ‘split-pooling’ (Box 1) scRNA-seq approaches, based on combinatorial indexing of single cells [37, 38], provide certain benefits over isolation of ... See full document
12
Light-induced injury in mouse embryos revealed by single-cell RNA sequencing
... Meanwhile, single-cell transcriptomes from the 2-cell to blastocyst stage were analyzed after high-intensity light ...These data show that cells at each embryonic stage can be categorized into ... See full document
8
Extraction of total RNA from single oocytes and single cell mRNA sequencing of swine oocytes
... generation sequencing, single-oocyte RNA sequencing data have been generated for mice [4–6], cattle [7], goats [8], and humans ...of single oocytes are essen- tial for a fine ... See full document
5
Single cell RNA sequencing identifies inflammatory tissue T cells in eosinophilic esophagitis
... Th2 cell–associated ...of single-cell data uncovered by our study, we hope that our reported findings will impact the understanding of the mechanisms modulating T cell fate in health ... See full document
16
CellFishing jl: an ultrafast and scalable cell search method for single cell RNA sequencing
... database, Cell- ...selection, cell-wise normalization, variance stabilization, feature standardization, and dimensionality ...two data points by their hashed representation ... See full document
23
Single cell RNA sequencing to dissect the molecular heterogeneity in lupus nephritis
... Independent of specific biopsy class, an IFN response signature was detectable in the tubular cells of every patient. However, tubular IFN response scores differed between patients and were found to correlate with chro- ... See full document
13
clonealign: statistical integration of independent single cell RNA and DNA sequencing data from human cancers
... We supplemented our differential expression analysis with a variance component analysis ([19] and see the “Methods” section) to partition gene expression varia- tion into either clone-specific or intrinsic/residual. This ... See full document
12
UMI count modeling and differential expression analysis for single cell RNA sequencing
... each cell. The dis- tribution of the total number of UMIs captured in a cell is an important characteristic for UMI-based scRNA-seq ...physical cell size, proliferation status, and cell-cycle ... See full document
17
Single cell RNA sequencing identifies unique inflammatory airspace macrophage subsets
... Strikingly, despite existing in drastically different microenvironments during homeostasis, peak inflammation, and lung repair, RAMs displayed remarkably stable programing. The largest differences among RAMs were ... See full document
18
Revealing cellular and molecular transitions in neonatal germ cell differentiation using single cell RNA sequencing
... stem cell-progenitor-differentiation-primed spermatogonia transition is reminiscent of the adult differentiation trajectory reported recently (Green et ...the cell fate decision of adult SSCs to either ... See full document
15
SCOPE Seq: a scalable technology for linking live cell imaging and single cell RNA sequencing
... live cell imaging data, and co-encapsulate the cells with dual-barcoded beads ...on-chip cell lysis, mRNA capture, reverse transcription, and exonuclease di- ... See full document
5
SCALE: modeling allele specific gene expression by single cell RNA sequencing
... scRNA-seq data, whether the paternal and maternal alleles of a gene are independently ...non-homogeneous cell populations, ...ASE data, how to define cell sub-types and how to quantify ... See full document
15
Defining the Transcriptional Landscape during Cytomegalovirus Latency with Single Cell RNA Sequencing
... using single-cell ...next-generation sequencing (29, 35, ...this data set further reveals a significant correlation between viral gene expression in latent HPCs and viral gene expres- sion in ... See full document
17
A comparison of automatic cell identification methods for single cell RNA sequencing data
... 34 cell popula- tions (18 experiments, see the “Methods” ...major cell types was easy, where almost all classifiers showed high performance ...34 cell populations turned out to be a more challenging ... See full document
19
Pooling across cells to normalize single cell RNA sequencing data with many zero counts
... cells from one group, e.g., oligodendrocytes in the Zeisel et al. data set. We assume that no DE is present within the group, such that the only differences in the mean counts between cells are due to ... See full document
14
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