Pseudotime estimation: deconfounding single cell time series
نویسندگان
چکیده
منابع مشابه
Pseudotime estimation: deconfounding single cell time series
MOTIVATION Repeated cross-sectional time series single cell data confound several sources of variation, with contributions from measurement noise, stochastic cell-to-cell variation and cell progression at different rates. Time series from single cell assays are particularly susceptible to confounding as the measurements are not averaged over populations of cells. When several genes are assayed ...
متن کاملSlingshot: Cell lineage and pseudotime inference for single-cell transcriptomics
Single-cell transcriptomics allows researchers to investigate complex communities of heterogeneous cells. These methods can be applied to stem cells and their descendants in order to chart the progression from multipotent progenitors to fully differentiated cells. While a number of statistical and computational methods have been proposed for analyzing cell lineages, the problem of accurately ch...
متن کاملSpectral Estimation of Stationary Time Series: Recent Developments
Spectral analysis considers the problem of determining (the art of recovering) the spectral content (i.e., the distribution of power over frequency) of a stationary time series from a finite set of measurements, by means of either nonparametric or parametric techniques. This paper introduces the spectral analysis problem, motivates the definition of power spectral density functions, and reviews...
متن کاملTASIC: determining branching models from time series single cell data
Motivation Single cell RNA-Seq analysis holds great promise for elucidating the networks and pathways controlling cellular differentiation and disease. However, the analysis of time series single cell RNA-Seq data raises several new computational challenges. Cells at each time point are often sampled from a mixture of cell types, each of which may be a progenitor of one, or several, specific fa...
متن کاملLEAP: constructing gene co-expression networks for single-cell RNA-sequencing data using pseudotime ordering
Summary To construct gene co-expression networks based on single-cell RNA-Sequencing data, we present an algorithm called LEAP, which utilizes the estimated pseudotime of the cells to find gene co-expression that involves time delay. Availability and Implementation R package LEAP available on CRAN. Contact [email protected]. Supplementary information Supplementary data are available at Bioinf...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Bioinformatics
سال: 2016
ISSN: 1367-4803,1460-2059
DOI: 10.1093/bioinformatics/btw372