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Abstract：
limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
摘要：
limma是一个R/Bioconductor软件包，为分析基因表达实验的数据提供了一个集成的解决方案。它包含丰富的功能，可用于处理复杂的实验设计和信息借用，以克服样本量小的问题。在过去的十年里，通过微阵列和高通量PCR数据的差异表达分析，limma已成为基因发现的热门选择。该软件包包含特别强大的阅读设施，规范和探索这些数据。最近,limma的能力在两个重要方向上得到了显着扩展。首先,该软件包现在可以对RNA测序（RNA-seq）数据进行差异表达和差异剪接分析。以前限于微阵列数据的所有下游分析工具现在也可用于RNA-seq。这些功能允许用户使用非常相似的管道分析RNA-seq和微阵列数据。第二,该软件包现在能够以多种方式超越传统的基因表达分析，根据共调节的基因集或高阶表达特征分析表达谱。这为基因表达差异的生物学解释提供了增强的可能性。本文回顾了limma包装的理念和设计，总结新的和历史的特点，强调最近的增强功能和以前没有描述的功能。
