A Pipeline for small RNA Characterization (sRNACharP) written in the Nextflow DSL.
The pipeline obtains for each sRNA provided:
- the free energy of its secondary structure using centroidFold,
- the distance to the closest promoter predicted by Promotech,
- the distance to the closest terminator predicted by transterm,
- the distance to the closest ORFs listed in the genome annotation, and
- a vector with the reverse tetranucleotide (tetranucleotide + its reverse complement) frequencies.
Install [nextflow] with the following command:
curl -fsSL get.nextflow.io | bash
Nextflow can be installed on any POSIX system (UNIX-like system such as Linux, OS X) with Java 7 or 8.
sRNACharP requires several pieces of software. There are two ways to get sRNACharP to run: 1) install all of the software packages required natively, or 2) use sRNACharP Docker container (recommended).
This is certainly the easier (and more reproducible) method. In order to run the pipeline with Docker, you need to install Docker 18.03 (or higher). See the included Dockerfile for the configuration details of the Docker image we have built. Note that this Dockerfile is included for information only as we have already generated the Docker image. To pull the docker image:
docker pull penacastillolab/srnacharpv2
The pipeline can also be used without Docker by installing the following software components on your system:
- Bedtools version 2.27 (or higher)
- ViennaRNA version 2.4.18 (or higher)
- CentroidFold (requires Boost libraries)
- TransTermHP version 2.09
- R version 3.4 (or higher)
After downloading the file sRNACharP.nf, one can launch the pipeline with the --help parameter (make sure you run this command on the directory where sRNACharP.nf is located). This should show the help message:
nextflow run sRNACharP.nf --help
N E X T F L O W ~ version 20.10.0
Launching `sRNACharP.nf` [adoring_volta] - revision: c85fc3d135
sRNACharP: sRNA Characterization Pipeline
----------------------------------------------------
Usage:
sRNACharP [options]
Options:
--org ORGANISM the organism name [required]
--dir DIRECTORY the directory containing the input files [required]
--genome GENOME_FILE the genome file in FASTA format [required]
--annot ANNOTATION_FILE the annotation file in BED format (including only protein coding genes)[required]
--sRNAs SEQUENCE_FILE the sRNAs file in BED format [required]
--transtermFile TRANSTERM_FILE the TransTerm predictions file [optional].
--promoterFile PREDICTED_PROMOTER_FILE the Promoter predictions file [required]
The organism name is any alphanumeric string without whitespaces.
The annotation file is a BED file with seven columns: Sequence, Start, End, Name, Score, Strand, and Type. For instance,
NC_008060.1 277 1393 Bcen_0001 · - gene
NC_008060.1 1407 2622 Bcen_0002 · - gene
NC_008060.1 2665 2992 Bcen_0003 · - gene
The sRNAs BED file requires six columns: Sequence, Start, End, Name, Score, Strand. A seventh column with the Type may also be provided. The name in the fourth column must uniquely identify each sRNA. For instance,
NC_008060.1 208288 208699 s208288 412 +
NC_008060.1 604653 605021 s604653 369 -
NC_008060.1 2044980 2045161 s2044980 182 +
NC_008062.1 409323 409390 s409323 68 +
The promoter file provides the location of promoter sequences in the genome. You can use our programs Promotech or Promotech-CNN to obtain promoter predictions. However, prior knowledge or othe software can be used to obtain promoter locations. The promoter file contains six columns: Sequence, start of promoter, end of promoter, probability of being a promoter, strand and promoter sequence. For instance,
NC_008060.1 3647120 3647159 0.63685 - CGTTTTCCGTCCGCAGGCTCCGGTTGGCACGATGGATGCG
NC_008060.1 3651194 3651233 0.65932 + CCGCTGGAATTCAACATCGCCTGACCCTAGATTCAAGGCG
NC_008060.1 3652212 3652251 0.68253 + CCCTGTTCCCCGCCCCCGTGCCGGAGATAACCTTTCCGCA
NC_008060.1 3656315 3656354 0.67378 + CCGCCGCCGCATCGCGCAGGTTGGTGCCATAATCGTCCCG
NOTE: Make sure that the sequence identifier is the same in all BED files and in the genome FASTA file (in the example above the sequence identifier is NC_008060.1). The sequence identifier should not contain any whitespace.
sRNACharP is configured to run using the Docker container engine by default (see Nextflow config file). If you are using Docker, download the Nextflow config file and save it on the same directory as the sRNACharP.nf file. If you have installed the required software natively, you will need to modify the Nextflow config file.
A sample data set is provided. To run sRNACharP with the test data, replace ADD_PATH below with the correct path in your system and run the following command on your terminal (make sure you are executing nextflow on the directory where the sRNACharP.nf file and the Nextflow config file are located):
nextflow run sRNACharP.nf --org="R_capsulatus" --dir="/ADD_PATH/sRNACharP/test_data" --genome="R_capsulatus_genome.fasta" --sRNAs="R_capsulatus_sRNAs.bed" --genomeAnnotation="R_capsulatus_genomeAnnotation_proteincoding.bed" --promoterFile="R_capsulatus_genome_promoter_predictions.csv"
On your terminal you should see something like this:
N E X T F L O W ~ version 20.10.0
Launching `sRNACharP.nf` [astonishing_yalow] - revision: d038e223d1
executor > local (9)
[99/a861f0] process > getFASTAsRNAs [100%] 1 of 1 ✔
[c2/e039ce] process > reorderAndSortPromoterPredictions [100%] 1 of 1 ✔
[b4/eafc8f] process > getFreeEnergySS [100%] 1 of 1 ✔
[d6/2d2435] process > createCRDFile [100%] 1 of 1 ✔
[56/51aa8c] process > runTransterm [100%] 1 of 1 ✔
[cb/72eb37] process > parseTranstermResults [100%] 1 of 1 ✔
[2b/c2bdf0] process > getDistances (1) [100%] 1 of 1 ✔
[7d/9244ec] process > createAttributeTable (1) [100%] 1 of 1 ✔
[ec/9eec60] process > createTetranucleotideRC_features (1) [100%] 1 of 1 ✔
Pipeline execution summary
executor > local (9)
[99/a861f0] process > getFASTAsRNAs [100%] 1 of 1 ✔
[c2/e039ce] process > reorderAndSortPromoterPredictions [100%] 1 of 1 ✔
[b4/eafc8f] process > getFreeEnergySS [100%] 1 of 1 ✔
[d6/2d2435] process > createCRDFile [100%] 1 of 1 ✔
[56/51aa8c] process > runTransterm [100%] 1 of 1 ✔
[cb/72eb37] process > parseTranstermResults [100%] 1 of 1 ✔
[2b/c2bdf0] process > getDistances (1) [100%] 1 of 1 ✔
[7d/9244ec] process > createAttributeTable (1) [100%] 1 of 1 ✔
[ec/9eec60] process > createTetranucleotideRC_features (1) [100%] 1 of 1 ✔
Analyses results are saved into the working directory.
Output files are the following (replace ORGANISM with the value of the --org parameter):
ORGANISM_FeatureTableNew.tsv- table containing the characteristics per sRNA. Columns are: sequence identifier (sRNA ID), free energy of predicted secondary structure, distance to the closest predicted promoter, distance to the closest predicted terminator, distance to the closest upstream ORF, a flag indicating whether the sRNA is on the same strand as the closest upstream ORF, distance to the closest downstream ORF, a flag indicating whether the sRNA is on the same strand as the closest downstream ORF, and Tetranucleotide_RC frequencies. Here are some lines of a feature table generated:
SS PromoterDistance DistTerm Distance sameStrand DownDistance sameDownStrand AAAA/TTTT AAAC/GTTT AAAG/CTTT AAAT/ATTT AACA/TGTT AACC/GGTT AACG/CGTT AACT/AGTT AAGA/TCTT AAGC/GCTT AAGG/CCTT AAGT/ACTT AATA/TATT AATC/GATT AATG/CATT AATT/AATT ACAA/TTGT ACAC/GTGT ACAG/CTGT ACAT/ATGT ACCA/TGGT ACCC/GGGT ACCG/CGGT ACCT/AGGT ACGA/TCGT ACGC/GCGT ACGG/CCGT ACGT/ACGT ACTA/TAGT ACTC/GAGT ACTG/CAGT AGAA/TTCT AGAC/GTCT AGAG/CTCT AGAT/ATCT AGCA/TGCT AGCC/GGCT AGCG/CGCT AGCT/AGCT AGGA/TCCT AGGC/GCCT AGGG/CCCT AGTA/TACT AGTC/GACT AGTG/CACT ATAA/TTAT ATAC/GTAT ATAG/CTAT ATAT/ATAT ATCA/TGAT ATCC/GGAT ATCG/CGAT ATGA/TCAT ATGC/GCAT ATGG/CCAT ATTA/TAAT ATTC/GAAT ATTG/CAAT CAAA/TTTG CAAC/GTTG CAAG/CTTG CACA/TGTG CACC/GGTG CACG/CGTG CAGA/TCTG CAGC/GCTG CAGG/CCTG CATA/TATG CATC/GATG CATG/CATG CCAA/TTGG CCAC/GTGG CCAG/CTGG CCCA/TGGG CCCC/GGGG CCCG/CGGG CCGA/TCGG CCGC/GCGG CCGG/CCGG CCTA/TAGG CCTC/GAGG CGAA/TTCG CGAC/GTCG CGAG/CTCG CGCA/TGCG CGCC/GGCG CGCG/CGCG CGGA/TCCG CGGC/GCCG CGTA/TACG CGTC/GACG CTAA/TTAG CTAC/GTAG CTAG/CTAG CTCA/TGAG CTCC/GGAG CTGA/TCAG CTGC/GCAG CTTA/TAAG CTTC/GAAG GAAA/TTTC GAAC/GTTC GACA/TGTC GACC/GGTC GAGA/TCTC GAGC/GCTC GATA/TATC GATC/GATC GCAA/TTGC GCAC/GTGC GCCA/TGGC GCCC/GGGC GCGA/TCGC GCGC/GCGC GCTA/TAGC GGAA/TTCC GGAC/GTCC GGCA/TGCC GGCC/GGCC GGGA/TCCC GGTA/TACC GTAA/TTAC GTAC/GTAC GTCA/TGAC GTGA/TCAC GTTA/TAAC TAAA/TTTA TACA/TGTA TAGA/TCTA TATA/TATA TCAA/TTGA TCCA/TGGA TCGA/TCGA TGAA/TTCA TGCA/TGCA TTAA/TTAA
sRNA00508 -33.2 -1000 1000 -119 1 315 1 0.011494253 0 0.011494253 0.011494253 0 0.011494253 0 0.011494253 0 0.011494253 0.011494253 0 0.011494253 0.011494253 0 0 0 0.022988506 0 0 0.022988506 0.011494253 0.011494253 0 0 0.011494253 0.022988506 0 0 0 0.011494253 0 0 0 0 0 0.022988506 0 0 0 0.011494253 0.011494253 0 0 0 0 0.011494253 0 0 0.011494253 0.011494253 0 0 0.011494253 0.011494253 0 0.011494253 0 0.011494253 0 0.011494253 0.011494253 0.034482759 0.011494253 0 0.011494253 0 0 0.011494253 0 0.022988506 0.022988506 0 0 0.022988506 0.034482759 0 0.034482759 0.022988506 0.011494253 0 0 0 0 0.011494253 0.011494253 0.022988506 0.011494253 0.045977011 0.022988506 0 0 0.011494253 0 0 0 0.011494253 0.011494253 0 0 0.011494253 0.011494253 0 0 0 0 0 0 0 0 0.034482759 0.011494253 0 0.011494253 0 0.022988506 0 0.022988506 0.022988506 0.022988506 0 0.011494253 0 0 0.011494253 0.011494253 0 0.011494253 0 0 0 0 0 0.011494253 0 0
sRNA00526 -36.2 -1000 1000 -64 1 475 1 0 0 0.012345679 0 0.012345679 0 0.012345679 0.024691358 0 0 0.012345679 0.012345679 0 0.012345679 0 0 0 0.012345679 0.012345679 0 0 0.012345679 0.012345679 0 0 0 0.037037037 0 0 0 0.012345679 0 0.012345679 0 0 0 0.012345679 0 0 0 0.024691358 0.012345679 0 0 0 0 0 0 0 0 0.012345679 0 0 0 0 0 0 0.012345679 0 0.012345679 0.012345679 0.012345679 0 0.024691358 0.012345679 0.012345679 0.012345679 0 0 0 0 0.012345679 0.012345679 0.012345679 0.024691358 0.037037037 0.012345679 0.024691358 0.024691358 0 0.012345679 0 0.012345679 0 0.024691358 0 0 0.049382716 0.024691358 0 0 0 0 0 0 0.012345679 0 0.024691358 0 0 0.012345679 0.049382716 0 0.024691358 0 0 0 0 0.012345679 0 0.012345679 0.037037037 0 0 0 0.037037037 0 0.012345679 0.037037037 0.012345679 0 0 0 0 0 0 0 0 0 0 0.024691358 0 0 0.024691358 0 0
sRNA00627 -25.8 -1000 1000 -263 0 59 1 0 0 0.013157895 0 0 0.026315789 0 0 0 0.013157895 0.013157895 0 0 0 0 0 0 0 0.013157895 0 0.013157895 0.013157895 0 0.013157895 0 0.026315789 0 0 0 0.013157895 0 0.013157895 0 0 0.013157895 0.026315789 0.013157895 0 0 0 0 0.039473684 0 0.013157895 0 0 0 0 0 0.013157895 0.013157895 0 0.013157895 0.026315789 0 0 0 0 0.013157895 0 0 0 0.013157895 0 0.013157895 0.026315789 0.026315789 0 0.013157895 0.013157895 0 0 0.026315789 0 0.013157895 0.026315789 0 0.013157895 0.026315789 0.013157895 0 0 0.013157895 0 0 0.026315789 0 0.039473684 0 0.013157895 0.013157895 0 0.013157895 0 0.013157895 0.013157895 0.026315789 0 0 0.013157895 0 0.026315789 0.013157895 0 0.013157895 0 0 0.013157895 0 0.013157895 0.013157895 0.039473684 0.013157895 0 0 0 0.026315789 0.013157895 0 0.013157895 0 0 0 0 0 0 0 0 0 0 0.013157895 0 0 0.026315789 0 0
ORGANISMRNA_PromoterDistances.txt- sRNA distances to predicted promoters. Columns are: sRNA Sequence, Start, End, sRNA Name, Score, Strand, PromoterSequence, Start, End, Promoter Name, Score, Strand, distance Here are some lines of promoter distances table generated:
Chromosome 40220 40387 sRNA00747 15.2512228906 - Chromosome 40202 40241 CCTCTGGTGATCGGGGAGGCATGTGCTATCCTCCCCGACA 0.61461 - 0
Chromosome 260228 260433 sRNA00798 149.01043287 - Chromosome 264063 264102 GCGGCGGGGGCGGCGCTGCTTTCCTGGTATGATGCCCAGG 0.75134 - -3631
Chromosome 354469 354612 sRNA00123 12.6197304188 + Chromosome 351554 351593 CCTGACGCGACCTAGATCGTCGATTGCTATGATTGTTTCT 0.60641 + -2877
Chromosome 397555 397640 sRNA00822 9.92096705552 - Chromosome 401074 401113 CAGGGCGAAACCGGCCCGTTCTGGGGGCACAATGCCATCG 0.61885 - -3435
ORGANISMRNAsTranstermRes.gtf- compilation of TransTermHP results. Columns are: Replicon, Program, Terminator ID, Start, End, Score, Strand, and an empty field. Here are some lines of a predicted terminators table generated:
NC_016810.1 TransTermHP TERM2 13530 13572 83 + .
NC_016810.1 TransTermHP TERM3 13538 13564 100 + .
NC_016810.1 TransTermHP TERM4 14760 14779 100 + .
- Three more files are generated in the working directory:
ORGANISMRNAsSS.txt,ORGANISMGenomelength.txt, andORGANISMRNA_sortedPromoterPredictions.bedcontaining the free energy of the predicted secondary structure, the number of nucleotides in the genome, and sorted promoter predictions respectively.
If you use the pipeline, please cite:
Eppenhof EJ, Peña-Castillo L. (2019) Prioritizing bona fide bacterial small RNAs with machine learning classifiers. PeerJ 7:e6304