Adding UTRs and refining predictions¶
If you have RNA-seq data and would like to use the PASA-mediated “annotation comparison” to add UTRs and refine gene model predictions, this can be accomplished using the
funannotate update command. This script can also be run as a stand-alone to re-align RNA-seq data and/or update an existing GenBank genome.
If you have run
funannotate train and then
funannotate predict, this script will re-use those data and you can simply pass
funannotate update -i folder --cpus 12. This will add the gene predictions to the SQL database and then walk through each gene comparing to existing PASA alignments, PASA will make some adjustments to the gene models. As recommended by PASA developers, this is run twice in
funannotate update so slow??¶
The default SQL database for PASA is set to use SQLite – this is for compatibility. However, the limitation is that SQLite database in PASA is single threaded due to SQLite database lock issue. Thus even if you pass multiple cpus to the script, it will run all of the PASA steps single threaded, which can take a long time depending on PASA alignments and genome size. If you setup PASA to use MySQL, then the scripts can run PASA multi-threaded and
funannotate update will run much faster.
Usage: funannotate update <arguments> version: 1.7.2 Description: Script will run PASA mediated update of gene models. It can directly update the annotation from an NCBI downloaded GenBank file using RNA-seq data or can be used after funannotate predict to refine UTRs and gene model predictions. Kallisto is used to evidence filter most likely PASA gene models. Dependencies are hisat2, Trinity, samtools, fasta, minimap2, PASA, kallisto, bedtools. Required: -i, --input Funannotate folder or Genome in GenBank format (.gbk,.gbff). or -f, --fasta Genome in FASTA format -g, --gff Annotation in GFF3 format --species Species name, use quotes for binomial, e.g. "Aspergillus fumigatus" Optional: -o, --out Output folder name -l, --left Left/Forward FASTQ Illumina reads (R1) -r, --right Right/Reverse FASTQ Illumina reads (R2) -s, --single Single ended FASTQ reads --stranded If RNA-seq library stranded. [RF,FR,F,R,no] --left_norm Normalized left FASTQ reads (R1) --right_norm Normalized right FASTQ reads (R2) --single_norm Normalized single-ended FASTQ reads --pacbio_isoseq PacBio long-reads --nanopore_cdna Nanopore cDNA long-reads --nanopore_mrna Nanopore mRNA direct long-reads --trinity Pre-computed Trinity transcripts (FASTA) --jaccard_clip Turn on jaccard clip for dense genomes [Recommended for fungi] --no_normalize_reads Skip read Normalization --no_trimmomatic Skip Quality Trimming of reads --memory RAM to use for Jellyfish. Default: 50G -c, --coverage Depth to normalize reads. Default: 50 -m, --min_coverage Min depth for normalizing reads. Default: 5 --pasa_config PASA assembly config file, i.e. from previous PASA run --pasa_db Database to use. Default: sqlite [mysql,sqlite] --pasa_alignment_overlap PASA --stringent_alignment_overlap. Default: 30.0 --max_intronlen Maximum intron length. Default: 3000 --min_protlen Minimum protein length. Default: 50 --alt_transcripts Expression threshold (percent) to keep alt transcripts. Default: 0.1 [0-1] --p2g NCBI p2g file (if updating NCBI annotation) -t, --tbl2asn Assembly parameters for tbl2asn. Example: "-l paired-ends" --name Locus tag name (assigned by NCBI?). Default: use existing --sbt NCBI Submission file --species Species name, use quotes for binomial, e.g. "Aspergillus fumigatus" --strain Strain name --isolate Isolate name --SeqCenter Sequencing facilty for NCBI tbl file. Default: CFMR --SeqAccession Sequence accession number for NCBI tbl file. Default: 12345 --cpus Number of CPUs to use. Default: 2 ENV Vars: If not passed, will try to load from your $PATH. --PASAHOME --TRINITYHOME