[PDF] Top 20 A comparison of automatic cell identification methods for single cell RNA sequencing data

... and cell populations (annotation level), in order to represent different levels of challenges in the clas- sification task and to evaluate how each classifier performs in each case (Table ...the sequencing ... See full document

... for cell-to-cell differences in capture efficiency, sequencing depth, and other technical con- ...of methods for scaling normalization are available: those using spike-in RNA sets and ... See full document

... Camp data (many cell types) and the full-length protocols used by both may have contributed to Splat’s poorer perform- ...real data, which is unsurprising as this simulation is de- signed to produce ... See full document

... between methods in more detail, we generated t-stochastic neighbor embedding (t- SNE) plots [13] of all barcodes that were detected by either CellRanger or EmptyDrops in several ...distinct cell types, ... See full document

... 1 Comparison of major RNA sequencing ...platforms. RNA-Seq of polyadenylated RNAs (A) or total RNA after rRNA depletion (B) enables profiling at a high resolution but requires a ... See full document

... In the preprocessing step, biological signals are extracted from a DGE matrix. When building a database of refer- ence cells, CellFishing.jl takes a DGE matrix of M rows and N columns, with the rows being features ... See full document

... A direct consequence of properly modeling scRNA-seq counts is the power to accurately conduct differential expression analyses. Based on the knowledge derived from UMI-count modeling, we proposed a NB-based al- gorithm ... See full document

... stem cell renewal and differ- entiation are essential for normal tissue development, homeostasis, and repair, yet our understanding of these fundamental processes remains ...Bulk RNA-seq studies have ... See full document

... a cell-identifying sequencing barcode and a 3′-poly(dT) ...optical identification of the sequen- cing barcode on each bead, we attach a unique combin- ation of oligonucleotides selected from a set of ... See full document

... by cell sorting, it was important to demonstrate the ability to differen- tiate cell types on transcriptomic data ...expected cell types, a limitation of the study was the inability to ... See full document

... further screened by limma package based on Bayes method (http://www.bioconductor.org/). After processing using the top table method of limma package, the differentially expressed genes were analyzed. Then, they were ... See full document

... 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 ... See full document

... bulk RNA-seq analyses are also applicable to single-cell RNA- seq data; further tools have been designed specifically for analyses of single-cell RNA-seq ...stem ... See full document

... rare cell populations, uncovering regulatory re- lationships between genes, and tracking the trajectories of distinct cell lineages in development [10, ...transcriptome data with quantified gene ... See full document

... direct comparison and examination of reproducibility of data between single cell and bulk RNA-seq ...of single cell analysis. While bulk RNA-seq identified RAMs and ... See full document

... expression, sequencing reads from high quality cells are aligned to a reference genome and gene counts are ...non-UMI data, expression may be obtained as counts using tools such as HTSeq [49], RSEM [50], ... See full document

... of RNA sequencing (RNA-seq) technology has allowed for the rapid quantification of individual gene ...high-throughput data with computational and statistical methods provides a toolbox ... See full document

... using siRNA showed that there is a significant reduction but not complete loss of Oct4 mRNA and protein level (Fig. S9D). The expression of key stem cell markers (i.e. Gfra1 and Id4) remained unchanged, while 590 ... See full document

... An essential step in understanding HCMV latency is deciphering the importance of viral transcripts and proteins to latency maintenance and to the ability of the virus to reactivate. Based on the view that only a limited ... See full document

... of single-agent therapy a rational approach that targets multiple subpopulations of tumor cells with a combin- ation of non-cross-resistant drugs characterized by differ- ent mechanisms of action and ... See full document