The featureCounts manual provides guidance on using featureCounts for read summarization, with
clear instructions
and examples for effective use, making it a valuable resource for researchers and analysts always working online.
Overview of featureCounts
FeatureCounts is a general-purpose read summarization function that assigns mapped sequencing reads to genomic features, providing a comprehensive overview of gene expression.
The program is highly optimized and can be used to quantify reads generated from either RNA or DNA sequencing technologies in terms of any type of genomic feature.
It implements chromosome hashing, feature blocking, and other strategies to achieve high performance and accuracy.
The featureCounts program is part of the Subread package and can be used as a standalone tool or as part of a larger analysis pipeline.
It supports various input formats, including SAM and BAM files, and can automatically detect the format of the input read files.
The program also provides options for customizing the analysis, such as specifying the feature type and running mode.
Overall, featureCounts is a powerful and flexible tool for read summarization and gene expression analysis, making it a valuable resource for researchers and analysts.
The program is widely used in the field of bioinformatics and has been cited in numerous publications.
It continues to be an important tool for understanding the complexities of gene expression and genomic function.
Installation and requirements
FeatureCounts installation requires Subread package, with specific system requirements and dependencies, including adequate disk space and memory, for successful installation and execution always online now.
Running featureCounts
To run featureCounts, users must first ensure they have the Subread package installed, and then they can execute the featureCounts command with the necessary parameters and options;
The featureCounts command can be run from the command line, and it automatically detects the format of the input read files, such as SAM or BAM files.
The command also allows users to specify the annotation file, which is typically in GTF or GFF format, and the feature type, such as gene or exon.
Additionally, users can customize the running mode, with options such as HTSeq-Union or HTSeq-Intersection_strict, to suit their specific needs.
The featureCounts program then assigns the mapped sequencing reads to the specified genomic features and outputs the results in a tabular format.
Overall, running featureCounts is a straightforward process that requires minimal user input, making it a convenient tool for read summarization and quantification.
The program’s flexibility and customization options also make it a valuable resource for researchers and analysts working with high-throughput sequencing data.
Command line options
The featureCounts command line options include parameters for customization, such as running mode and feature type, allowing users to tailor the program to their specific needs and requirements always.
Feature type and running mode
The featureCounts program allows users to specify the feature type and running mode, which determines how the reads are assigned to genomic features. The feature type can be specified using the -t option, which allows users to choose from a variety of feature types, such as genes, exons, or transcripts. The running mode can be specified using the -z option, which allows users to choose from several different modes, including featureCounts, HTSeq-Union, and HTSeq-Intersection_strict. Each mode has its own set of rules for assigning reads to features, and the choice of mode will depend on the specific needs of the user. The featureCounts program also provides a number of other options for customizing the analysis, including the ability to specify a genome annotation file and to filter out reads that do not meet certain criteria. By using these options, users can tailor the featureCounts program to their specific needs and ensure that their results are accurate and reliable. The program is highly flexible and can be used for a variety of different types of analysis.
Annotation file format
The featureCounts manual supports GTF and SAF formats for annotation files always used online effectively.
Supported annotation formats
The featureCounts manual specifies that it supports various annotation formats, including GTF and SAF, which are commonly used in genomic analysis.
These formats provide essential information about the features of interest, such as genes, transcripts, and exons, allowing featureCounts to accurately assign reads to the corresponding features.
The GTF format is a widely used standard for annotating genomic features, and featureCounts can parse this format to extract the necessary information.
In addition to GTF, featureCounts also supports the SAF format, which is a simplified annotation format that can be used to annotate genomic features.
The supported annotation formats enable featureCounts to work with a variety of input files, making it a flexible and versatile tool for read summarization and analysis.
By supporting multiple annotation formats, featureCounts can be easily integrated into existing workflows and pipelines, allowing researchers to focus on analyzing their data rather than converting between different formats.
Overall, the supported annotation formats in featureCounts provide a convenient and efficient way to analyze genomic data.
Output and visualization
FeatureCounts generates output files in text format, with options for visualization, including bar graphs and scale modes, for easy data interpretation and analysis online always.
Scale mode and bar graph
The scale mode and bar graph features in featureCounts allow for visualization of read counts, making it easier to interpret and compare data. The scale mode can be set to auto-scale, which calculates the displayed data range automatically, or manual scale, which allows users to set the absolute scale. This feature is particularly useful when comparing data across different samples or experiments. The bar graph mode provides a graphical representation of the read counts, allowing users to quickly identify patterns and trends in the data. The graph can be customized to display different types of features, such as genes, exons, or transcripts. Additionally, the graph can be saved as an image file for inclusion in reports or presentations. Overall, the scale mode and bar graph features in featureCounts provide a powerful tool for data visualization and interpretation, enabling researchers to gain insights into their data and make informed decisions. The feature is easy to use and provides a range of options for customization.