rnaQUAST 1.4 manual

1. About rnaQUAST
2. Installation & requirements
    2.1. General requirements
    2.2. Software for de novo quality assessments
    2.3. Read alignment software
3. Options
    3.1. Input data options
    3.2. Basic options
    3.3. Advanced options
4. Understanding rnaQUAST output
    4.1. Reports
    4.2. Detailed output
    4.3. Plots
5. Citation
6. Feedback and bug reports

1 About rnaQUAST

rnaQUAST is a tool for evaluating RNA-Seq assemblies using reference genome and gene database. In addition, rnaQUAST is also capable of estimating gene database coverage by raw reads and de novo quality assessment using third-party software.

rnaQUAST version 1.4.0 was released under GPLv2 on July 5th, 2016 and can be downloaded from http://cab.spbu.ru/software/rnaquast/.

For impatient people:

2 Installation & requirements

2.1 General requirements

To run rnaQUAST you need:

Note, that due to the limitations of BLAT, in order to work with reference genomes of size more than 4 Gb a pslSort is also required.

Paths to blastn and GMAP (or BLAT) should be added to the $PATH environmental variable. To check that everything is installed correctly we recommend to run:

python rnaQUAST.py --test

Note that gffutils is used to complete gene coordinates in case of missing transcripts / genes records. For more information, see advanced options.

2.2 Software for de novo quality assessment

When reference genome and gene database are unavailable, we recommend to run BUSCO and GeneMarkS-T in rnaQUAST pipeline.

BUSCO requirements

BUSCO allows to detect core genes in the assembled transcripts. To use it you should install BUSCO v1.1b1, tblastn, HMMER and transeq and add these tools to the $PATH variable.

Since BUSCO requires python3, you may also need to add

#!/usr/bin/env python3
to the top of BUSCO_v1.1b1.py executable file. Depending on the species you wish to assess, you should download the appropriate lineage-specific profile libraries: Metazoa, Eukaryota, Arthropoda, Vertebrata, Fungi, or Bacteria from http://busco.ezlab.org and provide it to rnaQUAST with --clade option.

GeneMarkS-T requirements

GeneMarkS-T allows to predict genes in the assembled transcripts without reference genome. If you wish to use it in rnaQUAST pipeline, GeneMarkS-T should be properly installed and added to the $PATH variable.

2.3 Read alignment software

rnaQUAST is also capable of calculating various statistics using raw reads (e.g. database coverage by reads). To obtain them you need to install STAR aligner (or alternatively TopHat aligner + SAM tools) and add it to the $PATH variable. To learn more see input options.

3 Options

3.1 Input data options

To run rnaQUAST you need to provide either FASTA files with transcripts (recommended), or align transcripts to the reference genome manually and provide the resulting PSL files.

-r <REFERENCE>, --reference <REFERENCE>
    Single file with reference genome containing all chromosomes/scaffolds in FASTA format (preferably with *.fasta, *.fa, *.fna, *.ffn or *.frn extension) OR
    *.txt file containing the one-per-line list of FASTA files with reference sequences.

    File with gene coordinates in GTF/GFF format (needs information about parent relations). We recommend to use files downloaded from GENCODE or Ensembl.

--gene_db <GENE_DB>
    Path to the gene database generated by gffutils. The database is created during the first run. This option is not compatible with --gtf option. We recommend to use this option once the database is created in order to speed up the run.

--gmap_index <INDEX FOLDER>,
    Folder containing pre-built GMAP index for the reference genome. Using previously constructed index decreases running time. Note, that you still need to provide the reference genome that was used for index construction when this option is used.

-c <TRANSCRIPTS ...>, --transcripts <TRANSCRIPTS, ...>
     File(s) with transcripts in FASTA format separated by space.

     File(s) with transcript alignments to the reference genome in PSL format separated by space.

-sam <READS_ALIGNMENT>, --reads_alignment <READS_ALIGNMENT>
     File with read alignments to the reference genome in SAM format.

-1 <LEFT_READS>, --left_reads <LEFT_READS>
     File with forward paired-end reads in FASTQ format.

-2 <RIGHT_READS>, --right_reads <RIGHT_READS>
     File with reverse paired-end reads in FASTQ format.

-s <SINGLE_READS>, --single_reads <SINGLE_READS>
     File with single reads in FASTQ format.

3.2 Basic options

-o <OUTPUT_DIR>, --output_dir <OUTPUT_DIR>
     Directory to store all results. Default is rnaQUAST_results/results_<datetime>.

     Run rnaQUAST on the test data from the test_data folder, output directory is rnaOUAST_test_output.

-d, --debug
     Report detailed information, typically used only for detecting problems.

-h, --help
     Show help message and exit.

3.3 Advanced options

-t <INT>, --threads <INT>
     Maximum number of threads. Default is min(number of CPUs / 2, 16).

-l <LABELS ...>, --labels <LABELS ...>
     Name(s) of assemblies that will be used in the reports separated by space and given in the same order as files with transcripts / alignments.

-ss, --strand_specific
     Set if transcripts were assembled using strand-specific RNA-Seq data in order to benefit from knowing whether the transcript originated from the + or - strand.

--min_alignment <MIN_ALIGNMENT>
     Minimal alignment length to be used, default value is 50.

     Do not draw plots (makes rnaQUAST run a bit faster).

     Run with BLAT alignment tool instead of GMAP.

     Run BUSCO tool, which detects core genes in the assembly (see Installation & requirements). Use --clade <PATH> option to provide path to the BUSCO lineage data (Eukaryota, Metazoa, Arthropoda, Vertebrata or Fungi).

     Run with TopHat tool instead of STAR for analyzing database coverage by reads.

     Run with GeneMarkS-T gene prediction tool. Use --prokaryote option if the genome is prokaryotic.

     Use this option if your GTF file already contains genes records, otherwise gffutils will fix it. Note that gffutils may work for quite a long time.

     Is option if your GTF file already contains transcripts records, otherwise gffutils will fix it. Note that gffutils may work for quite a long time.

     Lower threshold for x-assembled/covered/matched metrics, default: 50%.

     Upper threshold for x-assembled/covered/matched metrics, default: 95%.

4 Understanding rnaQUAST output

In this section we describe metrics, statistics and plots generated by rnaQUAST. Metrics highlighted with bold italic are considered as the most important and are included in the short summary report (short_report.txt).

For the simplicity of explanation, transcript is further referred to as a sequence generated by the assembler and isoform denotes a sequence from the gene database. Figure below demonstrates how rnaQUAST classifies transcript and isoform sequences using alignment information.

4.1 Reports

The following text files with reports are contained in comparison_output directory and include results for all input assemblies. In addition, these reports are contained in <assembly_label>_output directories for each assembly separately.

Gene database metrics.

Coverage by reads. The following metrics are calculated only when --left_reads, --right_reads, --single_reads or --sam options are used (see options for details).

Basic transcripts metrics are calculated without reference genome and gene database.

Alignment metrics are calculated with reference genome but without using gene database. To calculate the following metrics rnaQUAST filters all short partial alignments (see --min_alignment option) and attempts to select the best hits for each transcript.

Number of assembled transcripts = Unaligned + Aligned = Unaligned + (Uniquely aligned + Multiply aligned + Misassembly candidates reported by GMAP (or BLAT)).

Alignment metrics for non-misassembled transcripts


Assembly completeness (sensitivity). For the following metrics (calculated with reference genome and gene database) rnaQUAST attempts to select best-matching database isoforms for every transcript. Note that a single transcript can contribute to multiple isoforms in the case of, for example, paralogous genes or genomic repeats. At the same time, an isoform can be covered by multiple transcripts in the case of fragmented assembly or duplicated transcripts in the assembly.

BUSCO metrics. The following metrics are calculated only when --busco and --clade options are used (see options for details).

GeneMarkS-T metrics. The following metrics are calculated when reference and gene database are not provided or --gene_mark option is used (see options for details).

Assembly specificity. To compute the following metrics we use only transcripts that have at least one significant alignment and are not misassembled.

Relative database coverage metrics are calculated only when raw reads (or read alignments) are provided. rnaQUAST uses read alignments to estimate the upper bound of the database coverage and the number of x-covered genes / isoforms / exons (see read coverage) and computes the following metrics:

4.3 Detailed output

These files are contained in <assembly_label>_output directories for each assembly separately.

4.3 Plots

The following plots are similarly contained in both comparison_output directory and <assembly_label>_output directories. Please note, that most of the plots represent cumulative distributions and some plots are given in logarithmic scale.




5 Citation

Bushmanova, E., Antipov, D., Lapidus, A., Suvorov, V. and Prjibelski, A.D., 2016. rnaQUAST: a quality assessment tool for de novo transcriptome assemblies. Bioinformatics, btw218.

6 Feedback and bug reports

Your comments, bug reports, and suggestions are very welcomed. They will help us to further improve rnaQUAST. If you have any troubles running rnaQUAST, please send us logs/rnaQUAST.log from the output directory. Address for communications: rnaquast_support@ablab.spbau.ru.