Simple and integrated tool that automatically extracts and folds all hairpin sequences from raw genome-wide data. It predicts the secondary structure of several overlapped segments, with longer length than the mean length of sequences of interest for the species under processing, ensuring that no one is lost nor inappropriately cut.
Publication: https://www.biorxiv.org/content/10.1101/2020.10.09.333898v1
Contact
- Cristian Yones cyones@sinc.unl.edu.ar
- sinc(i): http://sinc.unl.edu.ar
HextractoR was tested in R > 3.4, but it can probably work in older versions as well. For folding and aligning sequences, the toolbox uses some external well-known packages. The following software must be installed:
-
Vienna RNA: this package is used to fold sequences and alignments. Download: https://www.tbi.univie.ac.at/RNA/
-
NCBI blast+: this package is used to identify the known miRNAs and the sequences to discard. Download: ftp://ftp.ncbi.nlm.nih.gov/blast/executables/blast+/LATEST/
To install the R package simply execute from R:
install.packages("HextractoR", dependencies=T)
For processing a genome, you need a file containing the raw genome in FASTA format. To run HExtractor, simply call the main function. This function creates 2 files in the "out" folder and automatically names them. The input parameters are:
- input_file filename of the fasta file to process
- window_size Number of bases in the windows.
- window_step Window step. This number defines the overlap window: window_overlap=window_size-window_step
- min_length Minimum sequence length. Shorter sequences are discarded.
- min_bp Minimum number of base-pairs that must form a sequence.
- margin_bp When the sequence is trimmed, at least min_bp+margin_bp base-pairs are left.
- min_valid_nucleotides Each input sequence must have this quantity of valid nucleotides (not 'N') to be processed.
- only_sloop Only extract single loop sequence.
- trim_sequences Use some heuristics to trim the hairpins.
- blast_evalue e-value used in blast to match the extracted sequences with the sequences from the filter files.
- identity_threshold Identity threshold used to match sequences with the sequences from the filter files.
- nthreads Allows using more than one thread in the execution.
- nworks Split each sequence in nworks to use less RAM memory.
- filter_files Fasta files with known sequences to separate the output stems.
HextractoR function returns a list with the path of the output files and the result of the processing of each sequence (if it was succesful or failed)
Small example without filter files
First we get the path of the example FASTA file
library(HextractoR)
fpath <- system.file("Example_tiny.fasta", package="HextractoR")
To run HextractoR, simply call the main function
HextractoR(input_file = fpath)
Other example with filter files and a larger input file
fpath1 <- system.file("Example_human.fasta", package="HextractoR")
fpath2 <- system.file("Example_pre-miRNA.fasta", package="HextractoR")
HextractoR(input_file = fpath1, filter_files = {fpath2})
This function creates 2 files in the working directory and automatically names them.