Report on Annotation Recommended Tools

Version 1.0—December 2024

To accompany the Recommendations, the EBP provides A Report on Annotation Standards.

The annotation subcommittee has assembled a list of tools that have proven useful for given steps of the annotation process to one or more of its members. This list was created in the Fall of 2024 and is not meant to be exhaustive. Comments provided for each tool on scope, parameters or performance are based on the experience of this committee only. It is recommended to always use the latest version of a tool.

Repeat masking

RepeatModeler2

• URL: https://www.repeatmasker.org/RepeatModeler/

• DOI: https://doi.org/10.1073/pnas.1921046117

• For building a de novo library of repeats that can be used for repeat masking. Options for additional LTR identification

  TE-Trimmer

• URL: https://github.com/ptoth/TE-TRIM

• DOI: https://doi.org/10.1101/2024.06.27.600963

• For trimming transposable element sequences from reads prior to assembly. Automates manual curation of TE libraries: TE boundary definition and classification to improve library construction.

  RepeatMasker

• URL: https://www.repeatmasker.org/

• For annotating and masking repetitive elements in genomic sequences.

  Tandem Repeat Finder

• URL: https://github.com/Benson-Genomics-Lab/TRF

• DOI: https://doi.org/10.1093/nar/27.2.573

• Integrated in RepeatMasker but can additionally be run with different parameters to mask more repeats in large genomes.

  Ultra

• URL: https://github.com/TravisWheelerLab/ULTRA

• DOI: https://doi.org/10.1101/2024.06.03.597269

• For the identification and classification of tandem repeats (including satellites)

  RepeatDetector

• URL: https://github.com/BioinformaticsToolsmith/Red

• DOI: https://doi.org/10.1093/nargab/lqac089

• K-mer based. Works well for vertebrates, insects and plants. May not work well for some species, fungi in particular

  Windowmasker

• URL: https://www.ncbi.nlm.nih.gov/tools/windowmasker/

• DOI: https://doi.org/10.1093/bioinformatics/bti774

• For masking low-complexity regions in genomic sequences. K-mer based. Has a tendency to mask less than other tools

Short read alignment

STAR

• URL: https://github.com/alexdobin/STAR

• DOI: https://doi.org/10.1093/bioinformatics/bts635

• RNA-Seq aligner that handles spliced alignments, with an option for diploid genomes. Two-pass mapping increases intron discovery.

  Hisat2

• URL: https://github.com/DaehwanKimLab/hisat2

• DOI: https://doi.org/10.1038/s41587-019-0201-4

• Fast, RAM-efficient and sensitive RNA-Seq aligner

Long read/cDNA alignment

Minimap2

• URL: https://github.com/lh3/minimap2

• DOI: https://doi.org/10.1093/bioinformatics/btab705

• IsoSeq consensus or ONT reads aligner. Options for ONT cDNA and direct RNA

Transcript reconstruction

Stringtie2

• URL: https://github.com/gpertea/stringtie

• DOI: https://doi.org/10.1186/s13059-019-1910-1

• Can handle RNA-Seq and IsoSeq or ONT long reads simultaneously.

Psiclass

• URL: https://github.com/aloysj/psiclass

• DOI: https://doi.org/10.1038/s41467-019-12990-0

• For RNA-Seq reads. Can operate with a variable number of libraries, optimised for rare isoform construction.

  Scallop

• URL: https://github.com/Kingsford-Group/scallop

• DOI: https://doi.org/10.1186/s13059-019-1883-0

• For RNA-Seq reads. Sensitive.

Mikado

• URL: https://github.com/EI-CoreBioinformatics/mikado

• DOI: https://doi.org/10.1093/gigascience/giy093

• Combines and filters transcript assemblies from alternative tools, samples or sequencing technologies

Protein-to-genome alignment

miniprot

• URL: https://github.com/lh3/miniprot

• DOI: https://doi.org/10.1093/bioinformatics/btad014

• Extremely fast. Reasonably accurate if distance is not very large (e.g. within mammals)

  Spaln

• URL: https://github.com/ogotoh/spaln

• DOI: https://doi.org/10.1093/nar/gks708 https://doi.org/10.1093/bioinformatics/btae517

• Useful in case of larger evolutionary distances.

Protein-coding gene prediction

BRAKER3

• URL: https://github.com/Gaius-Augustus/BRAKER

• DOI: https://doi.org/10.1101/gr.278090.123

• Use when RNA-Seq data is available

  BRAKER2

• URL:https://github.com/Gaius-Augustus/BRAKER

• DOI: 10.1093/nargab/lqaa108

• Use when no RNA-Seq data is available, for genomes <1 Gbp

  GALBA

• URL: https://github.com/Gaius-Augustus/GALBA

• DOI: https://doi.org/10.1186/s12859-023-05449-z

• For larger genomes. Quick, useful when annotating closely related species where no RNA-Seq is available

  GeMoMa

• URL: https://github.com/Jstacs/Jstacs/tree/master/projects/gemoma

• DOI: https://doi.org/10.1007/978-1-4939-9173-0_9

• Requires proteins and reference annotations from closely related genome/species, optionally uses short read RNA-Seq alignments

  EviAnn

• URL: https://github.com/alekseyzimin/EviAnn_release/

• DOI: https://doi.org/10.1073/pnas.1921046117

• Requires proteins and reference annotations from closely related genome/species, optionally uses short read RNA-Seq data

Protein-coding gene set combiners

TSEBRA

• URL: https://github.com/Gaius-Augustus/TSEBRA

• DOI: https://doi.org/10.1186/s12859-021-04482-0

• Combines gene sets from BRAKER and Galba

Protein-coding gene predictors (ab initio)

Helixer

• URL: https://github.com/weberlab-hhu/Helixer

• DOI: https://doi.org/10.1093/bioinformatics/btaa1044

  Tiberius

• URL: https://github.com/Gaius-Augustus/Tiberius

• DOI: https://doi.org/10.1093/bioinformatics/btae685

• Currently supports only vertebrates

Annotation by projection

LiftOff

• URL: https://github.com/agshumate/Liftoff

• DOI: https://doi.org/10.1093/bioinformatics/btaa1016

• Projection from “closely” related species

  LiftOn

• URL: https://github.com/Kuanhao-Chao/LiftOn

• DOI: https://doi.org/10.1101/2024.05.16.593026

• Projection from same or different species

  CESAR2

• URL: https://github.com/hillerlab/CESAR2.0

• DOI: https://doi.org/10.1093/bioinformatics/btx527

• Requires the regions to be pre-aligned. Can work at large distances

  CAT

• URL: https://github.com/ComparativeGenomicsToolkit/Comparative-Annotation-Toolkit

• DOI: https://doi.org/10.1101%2Fgr.233460.117

• Good for smaller distances (e.g. primates)

Functional annotation

InterproScan

• URL: https://github.com/ebi-pf-team/interproscan

• DOI: https://doi.org/10.1093/bioinformatics/btu031

• Prediction of domain architectures

  EnTap

• URL: https://gitlab.com/PlantGenomicsLab/EnTAP

• DOI: https://doi.org/10.1111/1755-0998.13106

• Sequence similarity, gene family, ontology, protein domain, contaminant and HGT detection

FANTASIA

• URL: https://github.com/MetazoaPhylogenomicsLab/FANTASIA

• DOI: https://doi.org/10.1093/nargab/lqae078, https://doi.org/10.1101/2024.02.28.582465

• GO prediction when used in combination with top GO. Very fast on GPU (e.g. 2 minutes on proteome of one species)

Non-coding gene prediction

RFAM + Infernal cmsearch

• URL: https://rfam.org/ http://eddylab.org/infernal/

• RFAM: https://doi.org/10.1093/nar/gkaa1047

• cmsearch: https://doi.org/10.1093/bioinformatics/btt509

• For predicting short non-coding RNAs

  tRNAscan-SE

• URL: https://github.com/UCSC-LoweLab/tRNAscan-SE

• DOI: https://doi.org/10.1007/978-1-4939-9173-0_1

• For predicting tRNAs, has a eukaryotic high confidence filter that can be applied to significantly reduce false positives