InstaPrism:一个R包,用于快速实现BayesPrism
Mengying Hu1,2, Maria Chikina1,2
1Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, 15260, United States.
Bioinformatics (Oxford, England)
|July 6, 2024
概括
InstaPrism加速了基因表达数据的计算细胞类型解卷. 这一新包为BayesPrism提供了一个更快,更有效的记忆替代方案,通过精选的癌症参考来简化分析.
科学领域:
- 计算生物学是一种计算生物学.
- 生物信息学是一种生物信息学.
- 基因组学就是基因组学.
背景情况:
- 计算型细胞类型解卷对于分析大量基因表达数据异质性至关重要.
- 贝叶斯镜,贝叶斯方法,提供卓越的准确性和稳定性,但由于吉布斯采样,计算密集.
研究的目的:
- 介绍InstaPrism,一个用于高效的细胞类型解的新包.
- 与BayesPrism等现有方法相比,提高计算速度和内存效率.
主要方法:
- 用一个随机化的框架重新实现了BayesPrism.
- 用固定点算法取代了计算上昂贵的吉布斯采样.
- 针对各种癌症类型的综合预编译,精选的参考数据集.
主要成果:
- 在InstaPrism的性能方面,它与BayesPrism相美.
- 在计算速度和内存使用方面取得了显著的改进.
- 通过精心策划的参考集,简化了解卷过程.
结论:
- InstaPrism为细胞类型解卷提供了一个计算效率高,准确的解决方案.
- 该包可更快,更容易地分析基因表达数据异质性的基因表达数据.
- 为癌症研究和其他需要解卷分析的应用提供了有价值的工具.
相关概念视频
Binomial Probability Distribution
10.4K
A binomial distribution is a probability distribution for a procedure with a fixed number of trials, where each trial can have only two outcomes.
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter n denotes the number of trials.
There are only two possible outcomes,...
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter n denotes the number of trials.
There are only two possible outcomes,...
10.4K
Information Processing Approach
33
The information-processing theory of cognitive development centers on fundamental mental processes, including attention, memory, and problem-solving skills. Researchers in this field examine how cognitive abilities, such as working memory, evolve and influence children's overall development. Studies indicate that children with stronger working memory tend to excel in reading comprehension, math, and problem-solving compared to peers with less efficient memory skills. Low working memory is...
33
Biostatistics: Overview
233
Biostatistics plays a crucial role in understanding and analyzing data in healthcare and biology. Biostatisticians conduct experiments, gather evidence, and draw meaningful conclusions using statistical methods and techniques. Different variables form the foundation of biostatistical analysis, allowing researchers to understand and interpret data effectively. These variables are classified into different types, each serving a specific purpose in statistical analysis.
Discrete variables are...
Discrete variables are...
233
Poisson Probability Distribution
7.8K
A Poisson probability distribution is a discrete probability distribution. It gives the probability of a number of events occurring in a fixed interval of time or space if these events happen at a known average rate and independently of the time since the last event. For example, a book editor might be interested in the number of words spelled incorrectly in a particular book. It might be that, on average, there are five words spelled incorrectly in 100 pages. The interval is 100 pages.
The...
The...
7.8K
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
454
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
On...
454
Statistical Software for Data Analysis and Clinical Trials
532
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
532


