txtools | R Documentation |
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.
Most of txtools' functions start with the prefix tx_ and are grouped by families:
Load initial data as genomes (FASTA), gene annotations (BED), and mapped reads (BAM).
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
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
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.
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.
Maintainer: Miguel Angel Garcia-Campos garciacampos.bioinfo@gmail.com (ORCID) (https://angelcampos.github.io/)
Useful links:
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