than another.\n"However, existing methods to discover them suffer from either low discovery rates or high rates of\nfalse positives.\n"We introduce Dawnn, a deep neural network able to find differential abundance with higher accuracy\nthan current tools, both on simulated and biological datasets...
Single-cell RNA-seq (scRNA-seq) enables the quantification of RNA abundance at the resolution of individual cells4. The maturation of single-cell technologies now enables large-scale comparisons of cell states within complex tissues, thus providing the appropriate resolution to dissect cell-type-speci...
DA分析同样是基于注释celltype,比较不同conditions的相同的celltype的cells数有无显著差异。 test for significant changes in per-label cell abundance across conditions; reveal which cell types are depleted or enriched upon treatment. 1、preparation "count matrics" quantify the number of cells assigned to ...
As a proof of concept, we designed a ladder comprising eight different hash oligos, theoretical abundance ranging from 0.1–12.8 picomoles per one million nuclei, and introduced into a sci-RNA-seq library preparation of HEK293T cells during the cell lysis step (Fig. 1a). As expected, we re...
Background The analysis of single-cell RNA sequencing (scRNAseq) data plays an important role in understanding the intrinsic and extrinsic cellular processes in biological and biomedical research. One significant effort in this area is the detection of differentially expressed (DE) genes. scRNAseq dat...
Many methods have been used to determine differential gene expression from single-cell RNA (scRNA)-seq data. We evaluated 36 approaches using experimental and synthetic data and found considerable differences in the number and characteristics of the genes that are called differentially expressed. Prefil...
As a first step in addressing the low relative abundance of phosphorylated proteins, it is advisable to use some form of fractionation to reduce sample complexity during subsequent analytical steps (Gruhler et al., 2005). Differential centrifugation is a popular technique for fractionation of biologic...
Second, the assignment of a single numerical value to a gene can mask dynamic effects among its multiple constituent transcripts (Fig. 2). In the case of “cancellation” (Fig. 2a), the abundance of transcripts changing in opposite directions cancels out upon conversion to gene abundance. In ...
Single-cell transcriptome sequencing (scRNA-seq) has revolutionized modern biology by allowing researchers to profile transcript abundance at the resolution of an individual cell. This has opened new avenues of research to study cellular pathways during the cell cycle, cell-type differentiation, or cell...
Several statistical methods have been proposed for differential abundance analysis based on zero-inflated MS data. Gleiss et al.3 classified these methods into three types. The first type of methods is one-part tests, which consider the data as left-censored and use a single model to ...