txtools: A package facilitating analysis of RNA modifications, structures, and interactions

txtools enables the processing, analysis, and visualization of RNA-seq data at the nucleotide-level resolution, seamlessly integrating alignments to the genome with transcriptomic representation. txtools’ main inputs are BAM files and a transcriptome annotation, and the main output is a table, capturing mismatches, deletions, and the number of reads beginning and ending at each nucleotide in the transcriptomic space. txtools further facilitates downstream visualization and analyses.

Details

Most of txtools' functions start with the prefix tx_ and are grouped by families:

tx_load_*()

Load initial data as genomes (FASTA), gene annotations (BED), and mapped reads (BAM).

tx_add_*()

Add a new variable to the txDT, generally by computing a ratio or frequency. Their output is the new txDT. e.g. tx_add_startRatio(), which adds the start to coverage ratio; tx_add_motifPresence(), which adds the location of RNA sequence motifs across the transcriptome

tx_get_*()

Extract information from a txDT and generate an object that is NOT a txDT. e.g. tx_get_metageneRegions() which outputs a metagene matrix with each row representing a gene and each column a bin in one of the codifying gene regions

tx_plot_*()

Plotting functions. e.g. tx_plot_nucFreq() and tx_plot_staEndCov(), which plot the counts of data of nucleotide frequency, and read-starts/ends and coverage respectively.

tx_test_*()

Use of the txDT objects from experimental data to do statistical tests of metrics between groups of samples. e.g. tx_test_ttest() which performs t-tests using a list of txDTs and a vector of the groups.

Author

Maintainer: Miguel Angel Garcia-Campos garciacampos.bioinfo@gmail.com (ORCID) (https://angelcampos.github.io/)