REAT - Robust and Extendable eukaryotic Annotation Toolkit¶
REAT is a robust easy-to-use genome annotation toolkit for turning high-quality genome assemblies into usable and informative resources. REAT makes use of state-of-the-art annotation tools and is robust to varying quality and sources of molecular evidence.
REAT provides an integrated environment that comprises both a set of workflows geared towards integrating multiple sources of evidence into a genome annotation, and an execution environment for these workflows.
Installation¶
To install REAT you can:
git clone https://github.com/ei-corebioinformatics/reat
wget https://github.com/broadinstitute/cromwell/releases/download/62/cromwell-62.jar
conda env create -f reat/reat.yml
These commands will download the cromwell binary required to execute the workflows and make REAT available in the ‘reat’ conda environment which can be activated using:
conda activate reat
Each task in the workflow is configured with default resource requirements appropriate for most tasks, but these can be overriden by user provided ones. For an example of this file see:
{
"ei_annotation.wf_align.long_read_alignment_resources":
{
"cpu_cores": 6,
"max_retries": 1,
"mem_gb": 16
},
"ei_annotation.wf_align.long_read_assembly_resources":
{
"cpu_cores": 6,
"max_retries": 1,
"mem_gb": 16
},
"ei_annotation.wf_align.long_read_indexing_resources":
{
"cpu_cores": 6,
"max_retries": 1,
"mem_gb": 16
},
"ei_annotation.wf_align.short_read_alignment_resources":
{
"cpu_cores": 6,
"max_retries": 1,
"mem_gb": 16
},
"ei_annotation.wf_align.short_read_alignment_sort_resources":
{
"cpu_cores": 6,
"max_retries": 1,
"mem_gb": 16
},
"ei_annotation.wf_align.short_read_merge_resources": {
"cpu_cores": 4,
"max_retries": 1,
"mem_gb": 16
},
"ei_annotation.wf_align.short_read_scallop_assembly_resources":
{
"cpu_cores": 6,
"max_retries": 1,
"mem_gb": 16
},
"ei_annotation.wf_align.short_read_stringtie_assembly_resources":
{
"cpu_cores": 6,
"max_retries": 1,
"mem_gb": 16
},
"ei_annotation.wf_align.short_read_stats_resources":
{
"cpu_cores": 6,
"max_retries": 1,
"mem_gb": 8
},
"ei_annotation.wf_main_mikado.homology_alignment_resources":
{
"cpu_cores": 6,
"max_retries": 1,
"mem_gb": 16
},
"ei_annotation.wf_main_mikado.homology_index_resources":
{
"cpu_cores": 6,
"max_retries": 1,
"mem_gb": 8
},
"ei_annotation.wf_main_mikado.orf_calling_resources":
{
"cpu_cores": 6,
"max_retries": 1,
"mem_gb": 8
},
"ei_annotation.wf_main_mikado.protein_alignment_resources":
{
"cpu_cores": 6,
"max_retries": 1,
"mem_gb": 16
},
"ei_annotation.wf_main_mikado.protein_index_resources":
{
"cpu_cores": 6,
"max_retries": 1,
"mem_gb": 16
}
}
To configure the cromwell engine, there are two relevant files, the cromwell runtime options and the workflow options files.
The cromwell engine can be configured to run in your environment using a file such as:
include required(classpath("application"))
system.io {
# For our shared cluster, you want to hit it with lots of requests and let SLURM figure out priority, rather than waiting.
number-of-requests = 1000000
per = 1 seconds
number-of-attempts = 5
}
system {
file-hash-cache = true
# Sometimes the defaults for input read limits were too small. These increase the max file sizes.
input-read-limits {
tsv = 1073741823
object = 1073741823
string = 1073741823
lines = 1073741823
json = 1073741823
}
}
database {
profile = "slick.jdbc.HsqldbProfile$"
db {
driver = "org.hsqldb.jdbcDriver"
url = """
jdbc:hsqldb:file:cromwell-executions/cromwell-db/cromwell-db;
shutdown=false;
hsqldb.default_table_type=cached;hsqldb.tx=mvcc;
hsqldb.result_max_memory_rows=10000;
hsqldb.large_data=true;
hsqldb.applog=1;
hsqldb.lob_compressed=true;
hsqldb.script_format=3
"""
connectionTimeout = 120000
numThreads = 1
}
}
concurrent-job-limit = 2
max-concurrent-workflows = 1
akka.http.server.request-timeout = 30s
call-caching {
# Allows re-use of existing results for jobs you've already run
# (default: false)
enabled = true
# Whether to invalidate a cache result forever if we cannot reuse them. Disable this if you expect some cache copies
# to fail for external reasons which should not invalidate the cache (e.g. auth differences between users):
# (default: true)
invalidate-bad-cache-results = true
}
backend {
default = slurm
providers {
slurm {
actor-factory = "cromwell.backend.impl.sfs.config.ConfigBackendLifecycleActorFactory"
config {
concurrent-job-limit = 50
filesystems {
local {
localization: [
# for local SLURM, hardlink doesn't work. Options for this and caching: , "soft-link" , "hard-link", "copy"
"soft-link", "copy"
]
## call caching config relating to the filesystem side
caching {
# When copying a cached result, what type of file duplication should occur. Attempted in the order listed below:
duplication-strategy: [
"soft-link"
]
hashing-strategy: "path"
# Possible values: file, path, path+modtime
# "file" will compute an md5 hash of the file content.
# "path" will compute an md5 hash of the file path. This strategy will only be effective if the duplication-strategy (above) is set to "soft-link",
# in order to allow for the original file path to be hashed.
check-sibling-md5: false
# When true, will check if a sibling file with the same name and the .md5 extension exists, and if it does, use the content of this file as a hash.
# If false or the md5 does not exist, will proceed with the above-defined hashing strategy.
}
}
}
runtime-attributes = """
Int runtime_minutes = 1440
Int cpu = 4
Int memory_mb = 8000
String? constraints
String? queue = "ei-medium"
"""
submit = """
if [ "" == "${queue}" ]
then
sbatch -J ${job_name} --constraint="${constraints}" -D ${cwd} -o ${out} -e ${err} -t ${runtime_minutes} \
-p ei-medium \
${"-c " + cpu} \
--mem ${memory_mb} \
--wrap "/bin/bash
${script}"
else
sbatch -J ${job_name} --constraint="${constraints}" -D ${cwd} -o ${out} -e ${err} -t ${runtime_minutes} \
-p ${queue} \
${"-c " + cpu} \
--mem ${memory_mb} \
--wrap "/bin/bash
${script}"
fi
"""
kill = "scancel ${job_id}"
check-alive = "squeue -j ${job_id}"
job-id-regex = "Submitted batch job (\\d+).*"
exit-code-timeout-seconds = 45
}
}
}
}
The workflow options can be used to activate the caching behaviour in cromwell, i.e:
{
"write_to_cache": true,
"read_from_cache": true,
"memory_retry_multiplier" : 1.5
}
Running REAT¶
There are several workflows that make REAT, here we will describe ‘transcriptome’ and ‘homology’.
Transcriptome Workflow¶
The intention of the transcriptome workflow is to use a variety of data types, from short reads to long reads of varied quality and length.
The data input for the workflow can be defined through the use of comma separated files one for short read samples and another for long read samples. These samples are then processed in several steps, first they are aligned to the genome, then assembled into transcripts, junctions are determined from the data and finally they are combined into a consolidated set of gene models.
The aligner and assembly programs used for short and long read samples can be selected through command line arguments. There are also command line arguments to select extra options to be applied at each step.
In case an annotation is available, this can be provided for junctions and reference models to be extracted and these can then be augmented using the evidence present in the data.
Welcome to REAT
version - 0.4.6
Command-line call:
/home/docs/checkouts/readthedocs.org/user_builds/reat/envs/v0.4.6/bin/reat transcriptome --help
usage: reat transcriptome [-h] --reference REFERENCE
[--samples SAMPLES [SAMPLES ...]]
[--csv_paired_samples CSV_PAIRED_SAMPLES]
[--csv_long_samples CSV_LONG_SAMPLES]
[--annotation ANNOTATION]
[--annotation_score ANNOTATION_SCORE]
[--check_reference]
[--mode {basic,update,only_update}]
[--extra_junctions EXTRA_JUNCTIONS]
[--skip_mikado_long] [--filter_HQ_assemblies]
[--filter_LQ_assemblies]
[--parameters_file PARAMETERS_FILE]
[--genetic_code GENETIC_CODE]
[--all_extra_config ALL_EXTRA_CONFIG]
[--long_extra_config LONG_EXTRA_CONFIG]
[--lq_extra_config LQ_EXTRA_CONFIG]
--all_scoring_file ALL_SCORING_FILE
[--long_scoring_file LONG_SCORING_FILE]
[--long_lq_scoring_file LONG_LQ_SCORING_FILE]
[--homology_proteins HOMOLOGY_PROTEINS]
[--separate_mikado_LQ SEPARATE_MIKADO_LQ]
[--exclude_LQ_junctions]
[--short_reads_aligner {hisat,star}]
[--skip_2pass_alignment]
[--HQ_aligner {minimap2,gmap,2pass,2pass_merged}]
[--LQ_aligner {minimap2,gmap,2pass,2pass_merged}]
[--min_identity MIN_IDENTITY]
[--min_intron_len MIN_INTRON_LEN]
[--max_intron_len MAX_INTRON_LEN]
[--max_intron_len_ends MAX_INTRON_LEN_ENDS]
[--PR_hisat_extra_parameters PR_HISAT_EXTRA_PARAMETERS]
[--PR_star_extra_parameters PR_STAR_EXTRA_PARAMETERS]
[--HQ_aligner_extra_parameters HQ_ALIGNER_EXTRA_PARAMETERS]
[--LQ_aligner_extra_parameters LQ_ALIGNER_EXTRA_PARAMETERS]
[--skip_scallop]
[--HQ_assembler {filter,merge,stringtie,stringtie_collapse}]
[--LQ_assembler {filter,merge,stringtie,stringtie_collapse}]
[--HQ_min_identity HQ_MIN_IDENTITY]
[--HQ_min_coverage HQ_MIN_COVERAGE]
[--HQ_assembler_extra_parameters HQ_ASSEMBLER_EXTRA_PARAMETERS]
[--LQ_min_identity LQ_MIN_IDENTITY]
[--LQ_min_coverage LQ_MIN_COVERAGE]
[--LQ_assembler_extra_parameters LQ_ASSEMBLER_EXTRA_PARAMETERS]
[--PR_stringtie_extra_parameters PR_STRINGTIE_EXTRA_PARAMETERS]
[--PR_scallop_extra_parameters PR_SCALLOP_EXTRA_PARAMETERS]
[--extra_parameters EXTRA_PARAMETERS]
[--orf_caller {prodigal,transdecoder,none}]
[--orf_calling_proteins ORF_CALLING_PROTEINS]
optional arguments:
-h, --help show this help message and exit
--reference REFERENCE
Reference FASTA to annotate (default: None)
--samples SAMPLES [SAMPLES ...]
Reads organised in the input specification for REAT,
for more information please look at
https://github.com/ei-corebioinformatics/reat for an
example (default: None)
--csv_paired_samples CSV_PAIRED_SAMPLES
CSV formatted input paired read samples. Without
headers. The CSV fields are as follows name, strand,
files (because this is an array that can contain one
or more pairs, this fields' values are separated by
semi-colon and space. Files in a pair are separated by
semi-colonpairs are separated by a single space),
merge, score, is_ref, exclude_redundant sample_strand
takes values 'fr-firststrand', 'fr-unstranded', 'fr-
secondstrand' merge, is_ref and exclude_redundant are
boolean and take values 'true', 'false' Example:
PR1,fr-secondstrand,A_R1.fq;A_R2.fq
/samples/paired/B1.fq;/samples/paired/B2.fq,false,2
(default: None)
--csv_long_samples CSV_LONG_SAMPLES
CSV formatted input long read samples. Without
headers. The CSV fields are as follows name, strand,
files (space separated if there is more than one),
quality, score, is_ref, exclude_redundant
sample_strand takes values 'fr-firststrand', 'fr-
unstranded', 'fr-secondstrand' quality takes values
'low', 'high' is_ref and exclude_redundant are
booleans and take values 'true', 'false' Example:
Sample1,fr-firststrand,A.fq /samples/long/B.fq
./inputs/C.fq,low,2 (default: None)
--annotation ANNOTATION
Annotation of the reference, this file will be used as
the base for the new annotation which will incorporate
from the available evidence new gene models or update
existing ones (default: None)
--annotation_score ANNOTATION_SCORE
Score for models in the reference annotation file
(default: 1)
--check_reference At mikado stage, annotation models will be evaluated
in the same manner as RNA-seq based models, removing
any models deemed incorrect (default: False)
--mode {basic,update,only_update}
basic: Annotation models are treated the same as the
RNA-Seq models at the pick stage.update: Annotation
models are prioritised but also novel loci are
reported.only_update: Annotation models are
prioritised and non-reference loci are excluded.
(default: basic)
--extra_junctions EXTRA_JUNCTIONS
Extra junctions provided by the user, this file will
be used as a set of valid junctions for alignment of
short and long read samples, in the case of long
reads, these junctions are combined with the results
of portcullis whenever short read samples have been
provided as part of the input datasets (default: None)
--skip_mikado_long Disables generation of the long read only mikado run
(default: False)
--filter_HQ_assemblies
Use all the junctions available to filter the
HQ_assemblies before mikado (default: False)
--filter_LQ_assemblies
Use all the junctions available to filter the
LQ_assemblies before mikado (default: False)
--parameters_file PARAMETERS_FILE
Base parameters file, this file can be the output of a
previous REAT run which will be used as the base for a
new parameters file written to the
output_parameters_file argument (default: None)
--genetic_code GENETIC_CODE
Parameter for the translation table used in Mikado for
translating CDS sequences, and for ORF calling, can
take values in the genetic code range of NCBI as an
integer. E.g 1, 6, 10 or when using TransDecoder as
ORF caller, one of: Universal, Tetrahymena,
Acetabularia, Ciliate, Dasycladacean, Hexamita,
Candida, Euplotid, SR1_Gracilibacteria,
Pachysolen_tannophilus, Peritrich. 0 is equivalent to
Standard, NCBI #1, but only ATG is considered a valid
start codon. (default: 0)
Mikado:
Parameters for Mikado runs
--all_extra_config ALL_EXTRA_CONFIG
External configuration file for Paired and Long reads
mikado (default: None)
--long_extra_config LONG_EXTRA_CONFIG
External configuration file for Long reads mikado run
(default: None)
--lq_extra_config LQ_EXTRA_CONFIG
External configuration file for Low-quality long reads
only mikado run (this is only applied when
'separate_mikado_LQ' is enabled) (default: None)
--all_scoring_file ALL_SCORING_FILE
Mikado long and short scoring file (default: None)
--long_scoring_file LONG_SCORING_FILE
Mikado long scoring file (default: None)
--long_lq_scoring_file LONG_LQ_SCORING_FILE
Mikado low-quality long scoring file (default: None)
--homology_proteins HOMOLOGY_PROTEINS
Homology proteins database, used to score transcripts
by Mikado (default: None)
--separate_mikado_LQ SEPARATE_MIKADO_LQ
Specify whether or not to analyse low-quality long
reads separately from high-quality, this option
generates an extra set of mikado analyses including
low-quality data (default: None)
--exclude_LQ_junctions
When this parameter is defined, junctions derived from
low-quality long reads will not be included in the set
of valid junctions for the mikado analyses (default:
False)
Alignment:
Parameters for alignment of short and long reads
--short_reads_aligner {hisat,star}
Choice of short read aligner (default: hisat)
--skip_2pass_alignment
If not required, the second round of alignments for
2passtools can be skipped when this parameter is
active (default: False)
--HQ_aligner {minimap2,gmap,2pass,2pass_merged}
Choice of aligner for high-quality long reads
(default: minimap2)
--LQ_aligner {minimap2,gmap,2pass,2pass_merged}
Choice of aligner for low-quality long reads (default:
minimap2)
--min_identity MIN_IDENTITY
Minimum alignment identity to retain transcript
(default: 0.9)
--min_intron_len MIN_INTRON_LEN
Where available, the minimum intron length allowed
will be specified for the aligners (default: 20)
--max_intron_len MAX_INTRON_LEN
Where available, the maximum intron length allowed
will be specified for the aligners (default: 200000)
--max_intron_len_ends MAX_INTRON_LEN_ENDS
Where available, the maximum *boundary* intron length
allowed will be specified for the aligner, when
specified this implies max_intron_len only applies to
the *internal* introns and this parameter to the
*boundary* introns (default: 100000)
--PR_hisat_extra_parameters PR_HISAT_EXTRA_PARAMETERS
Extra command-line parameters for the selected short
read aligner, please note that extra parameters are
not validated and will have to match the parameters
available for the selected read aligner (default:
None)
--PR_star_extra_parameters PR_STAR_EXTRA_PARAMETERS
Extra command-line parameters for the selected short
read aligner, please note that extra parameters are
not validated and will have to match the parameters
available for the selected read aligner (default:
None)
--HQ_aligner_extra_parameters HQ_ALIGNER_EXTRA_PARAMETERS
Extra command-line parameters for the selected long
read aligner, please note that extra parameters are
not validated and will have to match the parameters
available for the selected read aligner (default:
None)
--LQ_aligner_extra_parameters LQ_ALIGNER_EXTRA_PARAMETERS
Extra command-line parameters for the selected long
read aligner, please note that extra parameters are
not validated and will have to match the parameters
available for the selected read aligner (default:
None)
Assembly:
Parameters for assembly of short and long reads
--skip_scallop
--HQ_assembler {filter,merge,stringtie,stringtie_collapse}
Choice of long read assembler. - filter: Simply
filters the reads based on identity and coverage-
merge: cluster the input transcripts into loci,
discarding "duplicated" transcripts (those with the
same exact introns and fully contained or equal
boundaries). This option also discards contained
transcripts- stringtie: Assembles the long reads
alignments into transcripts- stringtie_collapse:
Cleans and collapses long reads but does not assemble
them (default: filter)
--LQ_assembler {filter,merge,stringtie,stringtie_collapse}
Choice of long read assembler. - filter: Simply
filters the reads based on identity and coverage-
merge: cluster the input transcripts into loci,
discarding "duplicated" transcripts (those with the
same exact introns and fully contained or equal
boundaries). This option also discards contained
transcripts- stringtie: Assembles the long reads
alignments into transcripts- stringtie_collapse:
Cleans and collapses long reads but does not assembles
them (default: stringtie_collapse)
--HQ_min_identity HQ_MIN_IDENTITY
When the 'filter' option is selected, this parameter
defines the minimum identity used to filtering
(default: None)
--HQ_min_coverage HQ_MIN_COVERAGE
When the 'filter' option is selected, this parameter
defines the minimum coverage used for filtering
(default: None)
--HQ_assembler_extra_parameters HQ_ASSEMBLER_EXTRA_PARAMETERS
Extra parameters for the long reads assembler, please
note that extra parameters are not validated and will
have to match the parameters available for the
selected assembler (default: None)
--LQ_min_identity LQ_MIN_IDENTITY
When the 'filter' option is selected, this parameter
defines the minimum identity used to filtering
(default: None)
--LQ_min_coverage LQ_MIN_COVERAGE
When the 'filter' option is selected, this parameter
defines the minimum coverage used for filtering
(default: None)
--LQ_assembler_extra_parameters LQ_ASSEMBLER_EXTRA_PARAMETERS
Extra parameters for the long reads assembler, please
note that extra parameters are not validated and will
have to match the parameters available for the
selected assembler (default: None)
--PR_stringtie_extra_parameters PR_STRINGTIE_EXTRA_PARAMETERS
Extra parameters for stringtie, please note that extra
parameters are not validated and will have to match
the parameters available for stringtie (default: None)
--PR_scallop_extra_parameters PR_SCALLOP_EXTRA_PARAMETERS
Extra parameters for scallop, please note that extra
parameters are not validated and will have to match
the parameters available for scallop (default: None)
Portcullis:
Parameters specific to portcullis
--extra_parameters EXTRA_PARAMETERS
Extra parameters for portcullis execution (default:
None)
ORF Caller:
Parameters for ORF calling programs
--orf_caller {prodigal,transdecoder,none}
Choice of available orf calling softwares (default:
prodigal)
--orf_calling_proteins ORF_CALLING_PROTEINS
Set of proteins to be aligned to the genome for orf
prediction by Transdecoder (default: None)
Sample files¶
The way samples are organised in the input files reflects how the files that correspond to the sample will be processed. Data can be combined or kept separate at different stages of the workflow in accordance with the configuration provided and the characteristics of the data.
Short read data¶
Each line corresponds to a sample. There are four required fields: Sample name, strandness, RNA-seq paired data, merge. Followed by three optional fields: score, is_reference, exclude_redundant. Previous fields to an optional field must be present in the line. Files within a pair are separated by semi-colon and where there are multiple pairs in a sample, these are separated by spaces.
Ara0,fr-firststrand,data/Ara1.1.fastq.gz;data/Ara1.2.fastq.gz,true,20
Ara1,fr-firststrand,data/Ara1.1.fastq.gz;data/Ara1.2.fastq.gz data/Ara2.1.fastq.gz;data/Ara2.2.fastq.gz,true,20
Ara2,fr-firststrand,data/Ara3.1.fastq.gz;data/Ara3.2.fastq.gz data/Ara5.1.fastq.gz;data/Ara5.2.fastq.gz data/Ara6.1.fastq.gz;data/Ara6.2.fastq.gz,false
Sample RNA-seq data can be merged in different places, the options for controlling when the merging happens are as follows: All transcripts assembled from paired reads within a sample are combined after assembling, paired read alignments can be merged before assembly using the ‘merge’ parameter in the CSV file.
Junctions¶
Junctions from RNA-seq data can be determined in several ways. By default junctions are collected for all the RNA-seq fastq pair as defined in the ‘RNA-seq paired data’ section of the CSV file for each sample. Alternatively, samples can be combined where appropriate using the ‘ei_annotation.wf_align.group_to_samples’ parameter in the input.json file. This parameter will define arbitrary groupings of the samples present in the short read CSV, with the following format:
"ei_annotation.wf_align.group_to_samples": {
"group1": ["Sample1", "Sample2"],
"group2": ["Sample3", "Sample4"]
}
These groups will be validated against the samples in the CSV files, group names should be unique, samples can only belong to a single group and all samples should be part of a group.
Long read data¶
Each line corresponds to a sample. There are four required fields: Sample name, strandness, RNA-seq long read data, merge. Followed by three optional fields: score, is_reference and exclude_redundant. Previous fields to an optional field must be present in the line. Where multiple read files correspond to a single sample (this implies they result in a single set of transcripts), the third column will contain all the files separated by spaces.
A01_1,fr-firststrand,data/A1_1.fastq.gz,low
A01_2,fr-firststrand,data/A1_2.fastq.gz,low
B01,fr-firststrand,data/B1.fastq.gz,low,10,true,true
C01,fr-firststrand,data/C1.fastq.gz,low
ALL,fr-firststrand,data/D1_1.fastq.gz data/D1_2.fastq.gz data/D1_3.fastq.gz data/D1_4.fastq.gz,low
CCS,fr-firststrand,data/CCS.fastq.gz,high
polished,fr-firststrand,data/polished.fastq.gz,high
Warning
The ‘reference’ sample name is reserved for internal use. If this name is being used in any of the sample input CSV files, you will be notified with an error message.
Homology workflow¶
When there is protein evidence available from related species, the homology workflow can be used to generate gene models based on this evidence. This is achieved by aligning the proteins provided through a set of related species annotations and evaluating these alignments to generate a score. Protein alignments are evaluated in two ways: Coherence of the alignment structure with respect to the original model’s structure and consensus structure from the multiple species. These scores are then used by Mikado to group and filter models, generating a set of predicted models.
Welcome to REAT
version - 0.4.6
Command-line call:
/home/docs/checkouts/readthedocs.org/user_builds/reat/envs/v0.4.6/bin/reat homology --help
usage: reat homology [-h] --genome GENOME [-p OUTPUT_PREFIX]
--alignment_species ALIGNMENT_SPECIES
[--annotations_csv ANNOTATIONS_CSV]
[--protein_sequences [PROTEIN_SEQUENCES [PROTEIN_SEQUENCES ...]]]
[--annotation_filters {all,none,exon_len,intron_len,internal_stop,aa_len,splicing} [{all,none,exon_len,intron_len,internal_stop,aa_len,splicing} ...]]
--mikado_config MIKADO_CONFIG --mikado_scoring
MIKADO_SCORING [--junctions JUNCTIONS] [--utrs UTRS]
[--pick_extra_config PICK_EXTRA_CONFIG]
[--min_cdna_length MIN_CDNA_LENGTH]
[--max_intron_length MAX_INTRON_LENGTH]
[--filter_min_cds FILTER_MIN_CDS]
[--filter_max_intron FILTER_MAX_INTRON]
[--filter_min_exon FILTER_MIN_EXON]
[--alignment_min_exon_len ALIGNMENT_MIN_EXON_LEN]
[--alignment_filters {all,none,exon_len,intron_len,internal_stop,aa_len,splicing} [{all,none,exon_len,intron_len,internal_stop,aa_len,splicing} ...]]
[--alignment_min_identity ALIGNMENT_MIN_IDENTITY]
[--alignment_min_coverage ALIGNMENT_MIN_COVERAGE]
[--alignment_max_per_query ALIGNMENT_MAX_PER_QUERY]
[--alignment_recursion_level ALIGNMENT_RECURSION_LEVEL]
[--alignment_show_intron_length]
[--exon_f1_filter EXON_F1_FILTER]
[--junction_f1_filter JUNCTION_F1_FILTER]
optional arguments:
-h, --help show this help message and exit
--genome GENOME Fasta file of the genome to annotate (default: None)
-p OUTPUT_PREFIX, --output_prefix OUTPUT_PREFIX
Prefix for the final output files (default: xspecies)
--alignment_species ALIGNMENT_SPECIES
Species specific parameters, select a value from the
first or second column of https://raw.githubuserconten
t.com/ogotoh/spaln/master/table/gnm2tab (default:
None)
--annotations_csv ANNOTATIONS_CSV
CSV file with reference annotations to extract
proteins/cdnas for spliced alignments in csv format.
The CSV fields are as follows
genome_fasta,annotation_gff e.g
Athaliana.fa,Athaliana.gff (default: None)
--protein_sequences [PROTEIN_SEQUENCES [PROTEIN_SEQUENCES ...]]
List of files containing protein sequences to use as
evidence (default: None)
--annotation_filters {all,none,exon_len,intron_len,internal_stop,aa_len,splicing} [{all,none,exon_len,intron_len,internal_stop,aa_len,splicing} ...]
Filter annotation coding genes by the filter types
specified (default: ['none'])
--mikado_config MIKADO_CONFIG
Base configuration for Mikado consolidation stage.
(default: None)
--mikado_scoring MIKADO_SCORING
Scoring file for Mikado pick at consolidation stage.
(default: None)
--junctions JUNCTIONS
Validated junctions BED file for use in Mikado
consolidation stage. (default: None)
--utrs UTRS Gene models that may provide UTR extensions to the
homology based models at the mikado stage (default:
None)
--pick_extra_config PICK_EXTRA_CONFIG
Extra configuration for Mikado pick stage (default:
None)
--min_cdna_length MIN_CDNA_LENGTH
Minimum cdna length for models to consider in Mikado
consolidation stage (default: 100)
--max_intron_length MAX_INTRON_LENGTH
Maximum intron length for models to consider in Mikado
consolidation stage (default: 1000000)
--filter_min_cds FILTER_MIN_CDS
If 'aa_len' filter is enabled for annotation coding
features, any CDS smaller thanthis parameter will be
filtered out (default: 20)
--filter_max_intron FILTER_MAX_INTRON
If 'intron_len' filter is enabled, any features with
introns longer than this parameter will be filtered
out (default: 200000)
--filter_min_exon FILTER_MIN_EXON
If 'exon_len' filter is enabled, any features with
exons shorter than this parameter will be filtered out
(default: 20)
--alignment_min_exon_len ALIGNMENT_MIN_EXON_LEN
Minimum exon length, alignment parameter (default: 20)
--alignment_filters {all,none,exon_len,intron_len,internal_stop,aa_len,splicing} [{all,none,exon_len,intron_len,internal_stop,aa_len,splicing} ...]
Filter alignment results by the filter types specified
(default: ['none'])
--alignment_min_identity ALIGNMENT_MIN_IDENTITY
Minimum identity filter for alignments (default: 50)
--alignment_min_coverage ALIGNMENT_MIN_COVERAGE
Minimum coverage filter for alignments (default: 80)
--alignment_max_per_query ALIGNMENT_MAX_PER_QUERY
Maximum number of alignments per input query protein
(default: 4)
--alignment_recursion_level ALIGNMENT_RECURSION_LEVEL
SPALN's Q value, indicating the level of recursion for
the Hirschberg algorithm (default: 6)
--alignment_show_intron_length
Add an attribute to the alignment gff with the maximum
intron len for each mRNA (default: False)
--exon_f1_filter EXON_F1_FILTER
Filter alignments scored against its original
structure with a CDS exon f1 lower than this value
(default: None)
--junction_f1_filter JUNCTION_F1_FILTER
Filter alignments scored against its original
structure with a CDS junction f1 lower than this value
(default: None)