GeMoMa-Docs: Difference between revisions

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''GeMoMa pipeline'' may be called with
''GeMoMa pipeline'' may be called with


  java -jar GeMoMa-1.7.jar CLI GeMoMaPipeline
  java -jar GeMoMa-1.7.1.jar CLI GeMoMaPipeline


and has the following parameters
and has the following parameters
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'''Example:'''
'''Example:'''


  java -jar GeMoMa-1.7.jar CLI GeMoMaPipeline t=<target_genome> AnnotationFinalizer.p=<prefix>
  java -jar GeMoMa-1.7.1.jar CLI GeMoMaPipeline t=&lt;target_genome&gt; g=&lt;genome&gt; a=&lt;annotation&gt; AnnotationFinalizer.p=&lt;prefix&gt;




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''Extract RNA-seq Evidence'' may be called with
''Extract RNA-seq Evidence'' may be called with


  java -jar GeMoMa-1.7.jar CLI ERE
  java -jar GeMoMa-1.7.1.jar CLI ERE


and has the following parameters
and has the following parameters
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'''Example:'''
'''Example:'''


  java -jar GeMoMa-1.7.jar CLI ERE m=<mapped_reads_file>
  java -jar GeMoMa-1.7.1.jar CLI ERE m=&lt;mapped_reads_file&gt;




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''CheckIntrons'' may be called with
''CheckIntrons'' may be called with


  java -jar GeMoMa-1.7.jar CLI CheckIntrons
  java -jar GeMoMa-1.7.1.jar CLI CheckIntrons


and has the following parameters
and has the following parameters
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'''Example:'''
'''Example:'''


  java -jar GeMoMa-1.7.jar CLI CheckIntrons t=<target_genome>
  java -jar GeMoMa-1.7.1.jar CLI CheckIntrons t=&lt;target_genome&gt; i=&lt;introns&gt;




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''DenoiseIntrons'' may be called with
''DenoiseIntrons'' may be called with


  java -jar GeMoMa-1.7.jar CLI DenoiseIntrons
  java -jar GeMoMa-1.7.1.jar CLI DenoiseIntrons


and has the following parameters
and has the following parameters
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'''Example:'''
'''Example:'''


  java -jar GeMoMa-1.7.jar CLI DenoiseIntrons i=<introns> coverage_unstranded=<coverage_unstranded>
  java -jar GeMoMa-1.7.1.jar CLI DenoiseIntrons i=&lt;introns&gt; coverage_unstranded=&lt;coverage_unstranded&gt;




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''NCBI Reference Retriever'' may be called with
''NCBI Reference Retriever'' may be called with


  java -jar GeMoMa-1.7.jar CLI NRR
  java -jar GeMoMa-1.7.1.jar CLI NRR


and has the following parameters
and has the following parameters
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'''Example:'''
'''Example:'''


  java -jar GeMoMa-1.7.jar CLI NRR rl=<reference_list>
  java -jar GeMoMa-1.7.1.jar CLI NRR rl=&lt;reference_list&gt;




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''Extractor'' may be called with
''Extractor'' may be called with


  java -jar GeMoMa-1.7.jar CLI Extractor
  java -jar GeMoMa-1.7.1.jar CLI Extractor


and has the following parameters
and has the following parameters
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'''Example:'''
'''Example:'''


  java -jar GeMoMa-1.7.jar CLI Extractor a=<annotation> g=<genome>
  java -jar GeMoMa-1.7.1.jar CLI Extractor a=&lt;annotation&gt; g=&lt;genome&gt;




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''GeneModelMapper'' may be called with
''GeneModelMapper'' may be called with


  java -jar GeMoMa-1.7.jar CLI GeMoMa
  java -jar GeMoMa-1.7.1.jar CLI GeMoMa


and has the following parameters
and has the following parameters
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'''Example:'''
'''Example:'''


  java -jar GeMoMa-1.7.jar CLI GeMoMa s=<search_results> t=<target_genome> c=<cds_parts> a=<assignment>
  java -jar GeMoMa-1.7.1.jar CLI GeMoMa s=&lt;search_results&gt; t=&lt;target_genome&gt; c=&lt;cds_parts&gt;




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''GeMoMa Annotation Filter'' may be called with
''GeMoMa Annotation Filter'' may be called with


  java -jar GeMoMa-1.7.jar CLI GAF
  java -jar GeMoMa-1.7.1.jar CLI GAF


and has the following parameters
and has the following parameters
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'''Example:'''
'''Example:'''


  java -jar GeMoMa-1.7.jar CLI GAF g=<gene_annotation_file>
  java -jar GeMoMa-1.7.1.jar CLI GAF g=&lt;gene_annotation_file&gt;




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''AnnotationFinalizer'' may be called with
''AnnotationFinalizer'' may be called with


  java -jar GeMoMa-1.7.jar CLI AnnotationFinalizer
  java -jar GeMoMa-1.7.1.jar CLI AnnotationFinalizer


and has the following parameters
and has the following parameters
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'''Example:'''
'''Example:'''


  java -jar GeMoMa-1.7.jar CLI AnnotationFinalizer g=<genome> a=<annotation> p=<prefix>
  java -jar GeMoMa-1.7.1.jar CLI AnnotationFinalizer g=&lt;genome&gt; a=&lt;annotation&gt; p=&lt;prefix&gt;




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''Annotation evidence'' may be called with
''Annotation evidence'' may be called with


  java -jar GeMoMa-1.7.jar CLI AnnotationEvidence
  java -jar GeMoMa-1.7.1.jar CLI AnnotationEvidence


and has the following parameters
and has the following parameters
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'''Example:'''
'''Example:'''


  java -jar GeMoMa-1.7.jar CLI AnnotationEvidence a=<annotation> g=<genome>
  java -jar GeMoMa-1.7.1.jar CLI AnnotationEvidence a=&lt;annotation&gt; g=&lt;genome&gt;




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''Compare transcripts'' may be called with
''Compare transcripts'' may be called with


  java -jar GeMoMa-1.7.jar CLI CompareTranscripts
  java -jar GeMoMa-1.7.1.jar CLI CompareTranscripts


and has the following parameters
and has the following parameters
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'''Example:'''
'''Example:'''


  java -jar GeMoMa-1.7.jar CLI CompareTranscripts p=<prediction> a=<annotation>
  java -jar GeMoMa-1.7.1.jar CLI CompareTranscripts p=&lt;prediction&gt; a=&lt;annotation&gt;




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''Synteny checker'' may be called with
''Synteny checker'' may be called with


  java -jar GeMoMa-1.7.jar CLI SyntenyChecker
  java -jar GeMoMa-1.7.1.jar CLI SyntenyChecker


and has the following parameters
and has the following parameters
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'''Example:'''
'''Example:'''


  java -jar GeMoMa-1.7.jar CLI SyntenyChecker a=<assignment> g=<gene_annotation_file>
  java -jar GeMoMa-1.7.1.jar CLI SyntenyChecker a=&lt;assignment&gt; g=&lt;gene_annotation_file&gt;




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''AddAttribute'' may be called with
''AddAttribute'' may be called with


  java -jar GeMoMa-1.7.jar CLI AddAttribute
  java -jar GeMoMa-1.7.1.jar CLI AddAttribute


and has the following parameters
and has the following parameters
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'''Example:'''
'''Example:'''


  java -jar GeMoMa-1.7.jar CLI AddAttribute a=<annotation> attribute=<attribute> t=&lt;table&gt; i=<ID_column> ac=<attribute_column>
  java -jar GeMoMa-1.7.1.jar CLI AddAttribute a=&lt;annotation&gt; attribute=&lt;attribute&gt; t=&lt;table&gt; i=&lt;ID_column&gt; ac=&lt;attribute_column&gt;

Revision as of 12:16, 9 September 2020

This page describes the parameters of all GeMoMa modules.
If you have any questions, comments or bugs, please check the FAQs, our github page or contact Jens Keilwagen.

GeMoMa pipeline

This tool can be used to run the complete GeMoMa pipeline. The tool is multi-threaded and can utilize all compute cores on one machine, but not distributed as for instance in a compute cluster. It basically runs: Extract RNA-seq evidence (ERE), DenoiseIntrons, Extractor, external search (tblastn or mmseqs), Gene Model Mapper (GeMoMa), GeMoMa Annotation Filter (GAF), and AnnnotationFinalizer.

GeMoMa pipeline may be called with 

java -jar GeMoMa-1.7.1.jar CLI GeMoMaPipeline

and has the following parameters

name comment type
t target genome (Target genome file (FASTA), mime = fasta,fa,fas,fna,fasta.gz,fa.gz,fas.gz,fna.gz) FILE
The following parameter(s) can be used zero or multiple times:
s species (data for reference species, range={own, pre-extracted}, default = own) STRING
Parameters for selection "own":
i ID (ID to distinguish the different reference species, default = , OPTIONAL) STRING
a annotation (Reference annotation file (GFF or GTF), which contains gene models annotated in the reference genome, mime = gff,gff3,gtf) FILE
g genome (Reference genome file (FASTA), mime = fasta,fa,fas,fna,fasta.gz,fa.gz,fas.gz,fna.gz) FILE
w weight (the weight can be used to prioritize predictions from different input files; each prediction will get an additional attribute sumWeight that can be used in the filter, valid range = [0.0, 1000.0], default = 1.0, OPTIONAL) DOUBLE
ai annotation info (annotation information of the reference, tab-delimted file containing at least the columns transcriptName, GO and .*defline, mime = tabular, OPTIONAL) FILE
Parameters for selection "pre-extracted":
i ID (ID to distinguish the different reference species, default = , OPTIONAL) STRING
c cds parts (The query cds parts file (FASTA), i.e., the cds parts that have been blasted, mime = fasta,fas,fa,fna) FILE
a assignment (The assignment file, which combines parts of the CDS to transcripts, mime = tabular, OPTIONAL) FILE
w weight (the weight can be used to prioritize predictions from different input files; each prediction will get an additional attribute sumWeight that can be used in the filter, valid range = [0.0, 1000.0], default = 1.0, OPTIONAL) DOUBLE
ai annotation info (annotation information of the reference, tab-delimted file containing at least the columns transcriptName, GO and .*defline, mime = tabular, OPTIONAL) FILE
The following parameter(s) can be used zero or multiple times:
ID ID (ID to distinguish the different external annotations of the target organism, default = , OPTIONAL) STRING
e external annotation (External annotation file (GFF,GTF) of the target organism, which contains gene models from an external source (e.g., ab initio gene prediction) and will be integrated in the module GAF, mime = gff,gff3,gtf) FILE
weight weight (the weight can be used to prioritize predictions from different input files in the module GAF; each prediction will get an additional attribute sumWeight that can be used in the filter, valid range = [0.0, 1000.0], default = 1.0, OPTIONAL) DOUBLE
ae annotation evidence (run AnnotationEvidence on this external annotation, default = true) BOOLEAN
selected selected (The path to list file, which allows to make only a predictions for the contained transcript ids. The first column should contain transcript IDs as given in the annotation. Remaining columns can be used to determine a target region that should be overlapped by the prediction, if columns 2 to 5 contain chromosome, strand, start and end of region, mime = tabular,txt, OPTIONAL) FILE
gc genetic code (optional user-specified genetic code, mime = tabular, OPTIONAL) FILE
tblastn tblastn (if *true* tblastn is used as search algorithm, otherwise mmseqs is used. Tblastn and mmseqs need to be installed to use the corresponding option, default = false) BOOLEAN
tag tag (A user-specified tag for transcript predictions in the third column of the returned gff. It might be beneficial to set this to a specific value for some genome browsers., default = mRNA) STRING
r RNA-seq evidence (data for RNA-seq evidence, range={NO, MAPPED, EXTRACTED}, default = NO) STRING
No parameters for selection "NO"
Parameters for selection "MAPPED":
ERE.s Stranded (Defines whether the reads are stranded. In case of FR_FIRST_STRAND, the first read of a read pair or the only read in case of single-end data is assumed to be located on forward strand of the cDNA, i.e., reverse to the mRNA orientation. If you are using Illumina TruSeq you should use FR_FIRST_STRAND., range={FR_UNSTRANDED, FR_FIRST_STRAND, FR_SECOND_STRAND}, default = FR_UNSTRANDED) STRING
The following parameter(s) can be used multiple times:
ERE.m mapped reads file (BAM/SAM files containing the mapped reads, mime = bam,sam) FILE
ERE.v ValidationStringency (Defines how strict to be when reading a SAM or BAM, beyond bare minimum validation., range={STRICT, LENIENT, SILENT}, default = LENIENT) STRING
ERE.u use secondary alignments (allows to filter flags in the SAM or BAM, default = true) BOOLEAN
ERE.c coverage (allows to output the coverage, default = true) BOOLEAN
ERE.mmq minimum mapping quality (reads with a mapping quality that is lower than this value will be ignored, valid range = [0, 255], default = 40) INT
ERE.mc minimum context (only introns that have evidence of at least one split read with a minimal M (=(mis)match) stretch in the cigar string larger than or equal to this value will be used, valid range = [1, 1000000], default = 1) INT
Parameters for selection "EXTRACTED":
The following parameter(s) can be used multiple times:
introns introns (Introns (GFF), which might be obtained from RNA-seq, mime = gff,gff3) FILE
The following parameter(s) can be used zero or multiple times:
coverage coverage (experimental coverage (RNA-seq), range={UNSTRANDED, STRANDED}, default = UNSTRANDED) STRING
Parameters for selection "UNSTRANDED":
coverage_unstranded coverage_unstranded (The coverage file contains the unstranded coverage of the genome per interval. Intervals with coverage 0 (zero) can be left out., mime = bedgraph) FILE
Parameters for selection "STRANDED":
coverage_forward coverage_forward (The coverage file contains the forward coverage of the genome per interval. Intervals with coverage 0 (zero) can be left out., mime = bedgraph) FILE
coverage_reverse coverage_reverse (The coverage file contains the reverse coverage of the genome per interval. Intervals with coverage 0 (zero) can be left out., mime = bedgraph) FILE
d denoise (removing questionable introns that have been extracted by ERE, range={DENOISE, RAW}, default = DENOISE) STRING
Parameters for selection "DENOISE":
DenoiseIntrons.m maximum intron length (The maximum length of an intron, default = 15000) INT
DenoiseIntrons.me minimum expression (The threshold for removing introns, valid range = [0.0, 1.0], default = 0.01) DOUBLE
DenoiseIntrons.c context (The context upstream a donor and donwstream an acceptor site that is used to determine the expression of the region, valid range = [0, 100], default = 10) INT
No parameters for selection "RAW"
Extractor.u upcase IDs (whether the IDs in the GFF should be upcased, default = false) BOOLEAN
Extractor.r repair (if a transcript annotation can not be parsed, the program will try to infer the phase of the CDS parts to repair the annotation, default = false) BOOLEAN
Extractor.a Ambiguity (This parameter defines how to deal with ambiguities in the DNA. There are 3 options: EXCEPTION, which will remove the corresponding transcript, AMBIGUOUS, which will use an X for the corresponding amino acid, and RANDOM, which will randomly select an amnio acid from the list of possibilities., range={EXCEPTION, AMBIGUOUS, RANDOM}, default = AMBIGUOUS) STRING
Extractor.d discard pre-mature stop (if *true* transcripts with pre-mature stop codon are discarded as they often indicate misannotation, default = true) BOOLEAN
Extractor.s stop-codon excluded from CDS (A flag that states whether the reference annotation contains the stop codon in the CDS annotation or not, default = false) BOOLEAN
Extractor.f full-length (A flag which allows for choosing between only full-length and all (i.e., full-length and partial) transcripts, default = true) BOOLEAN
GeMoMa.r reads (if introns are given by a GFF, only use those which have at least this number of supporting split reads, valid range = [1, 2147483647], default = 1) INT
GeMoMa.s splice (if no intron is given by RNA-seq, compute candidate splice sites or not, default = true) BOOLEAN
GeMoMa.sm substitution matrix (optional user-specified substitution matrix, mime = tabular, OPTIONAL) FILE
GeMoMa.g gap opening (The gap opening cost in the alignment, default = 11) INT
GeMoMa.ge gap extension (The gap extension cost in the alignment, default = 1) INT
GeMoMa.m maximum intron length (The maximum length of an intron, default = 15000) INT
GeMoMa.sil static intron length (A flag which allows to switch between static intron length, which can be specified by the user and is identical for all genes, and dynamic intron length, which is based on the gene-specific maximum intron length in the reference organism plus the user given maximum intron length, default = true) BOOLEAN
GeMoMa.i intron-loss-gain-penalty (The penalty used for intron loss and gain, default = 25) INT
GeMoMa.e e-value (The e-value for filtering blast results, default = 100.0) DOUBLE
GeMoMa.c contig threshold (The threshold for evaluating contigs, valid range = [0.0, 1.0], default = 0.4) DOUBLE
GeMoMa.rt region threshold (The threshold for evaluating regions, valid range = [0.0, 1.0], default = 0.9) DOUBLE
GeMoMa.h hit threshold (The threshold for adding additional hits, valid range = [0.0, 1.0], default = 0.9) DOUBLE
GeMoMa.p predictions (The (maximal) number of predictions per transcript, default = 10) INT
GeMoMa.a avoid stop (A flag which allows to avoid (additional) pre-mature stop codons in a transcript, default = true) BOOLEAN
GeMoMa.approx approx (whether an approximation is used to compute the score for intron gain, default = true) BOOLEAN
GeMoMa.pa protein alignment (whether a protein alignment between the prediction and the reference transcript should be computed. If so two additional attributes (iAA, pAA) will be added to predictions in the gff output. These might be used in GAF. However, since some transcripts are very long this can increase the needed runtime and memory (RAM)., default = true) BOOLEAN
GeMoMa.prefix prefix (A prefix to be used for naming the predictions, default = ) STRING
GeMoMa.t timeout (The (maximal) number of seconds to be used for the predictions of one transcript, if exceeded GeMoMa does not output a prediction for this transcript., valid range = [0, 604800], default = 3600) LONG
GeMoMa.Score Score (A flag which allows to do nothing, re-score or re-align the search results, range={Trust, ReScore, ReAlign}, default = ReAlign) STRING
GAF.c common border filter (the filter on the common borders of transcripts, the lower the more transcripts will be checked as alternative splice isoforms, valid range = [0.0, 1.0], default = 0.75) DOUBLE
GAF.m maximal number of transcripts per gene (the maximal number of allowed transcript predictions per gene, valid range = [1, 2147483647], default = 2147483647) INT
GAF.d default attributes (Comma-separated list of attributes that is set to NaN if they are not given in the annotation file. This allows to use these attributes for sorting or filter criteria. It is especially meaningful if the gene annotation files were received fom different software packages (e.g., GeMoMa, Braker, ...) having different attributes., default = tie,tde,tae,iAA,pAA,score) STRING
GAF.f filter (A filter can be applied to transcript predictions to receive only reasonable predictions. The filter is applied to the GFF attributes. The default filter decides based on the completeness of the prediction (start=='M' and stop=='*') and the relative score (score/aa>=0.75) whether a prediction is used or not. In addition, predictions without score (isNaN(score)) will be used as external annotations do not have the attribute score. Different criteria can be combined using 'and' and 'or'. A more sophisticated filter could be applied for instance using the completeness, the relative score, the evidence as well as statistics based on RNA-seq: start=='M' and stop=='*' and score/aa>=0.75 and (evidence>1 or tpc==1.0), default = start=='M' and stop=='*' and (isNaN(score) or score/aa>=0.75), OPTIONAL) STRING
GAF.s sorting (comma-separated list that defines the way predictions are sorted within a cluster, default = evidence,score) STRING
GAF.a alternative transcript filter (If a prediction is suggested as an alternative transcript, this additional filter will be applied. The filter works syntactically like the 'filter' parameter and allows you to keep the number of alternative transcripts small based on meaningful criteria. Reasonable filter could be based on RNA-seq data (tie==1) or on evidence (evidence>1). A more sophisticated filter could be applied combining several criteria: tie==1 or evidence>1, default = tie==1 or evidence>1, OPTIONAL) STRING
AnnotationFinalizer.u UTR (allows to predict UTRs using RNA-seq data, range={NO, YES}, default = NO) STRING
No parameters for selection "NO"
No parameters for selection "YES"
AnnotationFinalizer.r rename (allows to generate generic gene and transcripts names (cf. parameter "name attribute"), range={COMPOSED, SIMPLE, NO}, default = COMPOSED) STRING
Parameters for selection "COMPOSED":
AnnotationFinalizer.p prefix (the prefix of the generic name) STRING
AnnotationFinalizer.i infix (the infix of the generic name, default = G) STRING
AnnotationFinalizer.s suffix (the suffix of the generic name, default = 0) STRING
AnnotationFinalizer.d digits (the number of informative digits, valid range = [4, 10], default = 5) INT
AnnotationFinalizer.di delete infix (a comma-separated list of infixes that is deleted from the sequence names before building the gene/transcript name, default = ) STRING
Parameters for selection "SIMPLE":
AnnotationFinalizer.p prefix (the prefix of the generic name) STRING
AnnotationFinalizer.d digits (the number of informative digits, valid range = [4, 10], default = 5) INT
No parameters for selection "NO"
AnnotationFinalizer.n name attribute (if true the new name is added as new attribute "Name", otherwise "Parent" and "ID" values are modified accordingly, default = true) BOOLEAN
p predicted proteins (If *true*, returns the predicted proteins of the target organism as fastA file, default = true) BOOLEAN
pc predicted CDSs (If *true*, returns the predicted CDSs of the target organism as fastA file, default = false) BOOLEAN
pgr predicted genomic regions (If *true*, returns the genomic regions of predicted gene models of the target organism as fastA file, default = false) BOOLEAN
o output individual predictions (If *true*, returns the predictions for each reference species, default = false) BOOLEAN
debug debug (If *false* removes all temporary files even if the jobs exits unexpected, default = true) BOOLEAN
restart restart (can be used to restart the latest GeMoMaPipeline run, which was finished without results, with very similar parameters, e.g., after an exception was thrown (cf. parameter debug), default = false) BOOLEAN
b BLAST_PATH (allows to set a path to the blast binaries if not set in the environment, default = , OPTIONAL) STRING
m MMSEQS_PATH (allows to set a path to the blast binaries if not set in the environment, default = , OPTIONAL) STRING
outdir The output directory, defaults to the current working directory (.) STRING
threads The number of threads used for the tool, defaults to 1 INT

Example: 

java -jar GeMoMa-1.7.1.jar CLI GeMoMaPipeline t=<target_genome> g=<genome> a=<annotation> AnnotationFinalizer.p=<prefix>


Extract RNA-seq Evidence

This tools extracts introns and coverage from mapped RNA-seq reads. Introns might be denoised by the tool DenoiseIntrons. Introns and coverage results can be used in GeMoMa to improve the predictions and might help to select better gene models in GAF. In addition, introns and coverage can be used to predict UTRs by AnnotationFinalizer.

Extract RNA-seq Evidence may be called with 

java -jar GeMoMa-1.7.1.jar CLI ERE

and has the following parameters

name comment type
s Stranded (Defines whether the reads are stranded. In case of FR_FIRST_STRAND, the first read of a read pair or the only read in case of single-end data is assumed to be located on forward strand of the cDNA, i.e., reverse to the mRNA orientation. If you are using Illumina TruSeq you should use FR_FIRST_STRAND., range={FR_UNSTRANDED, FR_FIRST_STRAND, FR_SECOND_STRAND}, default = FR_UNSTRANDED) STRING
The following parameter(s) can be used multiple times:
m mapped reads file (BAM/SAM files containing the mapped reads, mime = bam,sam) FILE
v ValidationStringency (Defines how strict to be when reading a SAM or BAM, beyond bare minimum validation., range={STRICT, LENIENT, SILENT}, default = LENIENT) STRING
u use secondary alignments (allows to filter flags in the SAM or BAM, default = true) BOOLEAN
c coverage (allows to output the coverage, default = true) BOOLEAN
mmq minimum mapping quality (reads with a mapping quality that is lower than this value will be ignored, valid range = [0, 255], default = 40) INT
mc minimum context (only introns that have evidence of at least one split read with a minimal M (=(mis)match) stretch in the cigar string larger than or equal to this value will be used, valid range = [1, 1000000], default = 1) INT
outdir The output directory, defaults to the current working directory (.) STRING

Example: 

java -jar GeMoMa-1.7.1.jar CLI ERE m=<mapped_reads_file>


CheckIntrons

The tool checks the distribution of introns on the strands and the dinucleotide distribution at splice sites.

CheckIntrons may be called with 

java -jar GeMoMa-1.7.1.jar CLI CheckIntrons

and has the following parameters

name comment type
t target genome (The target genome file (FASTA), i.e., the target sequences in the blast run. Should be in IUPAC code, mime = fasta) FILE
The following parameter(s) can be used multiple times:
i introns (Introns (GFF), which might be obtained from RNA-seq, mime = gff, OPTIONAL) FILE
v verbose (A flag which allows to output a wealth of additional information per transcript, default = false) BOOLEAN
outdir The output directory, defaults to the current working directory (.) STRING

Example: 

java -jar GeMoMa-1.7.1.jar CLI CheckIntrons t=<target_genome> i=<introns>


DenoiseIntrons

This module allows to analyze introns extracted by ERE. Introns with a large intron size or a low relative expression are possibly artefacts and will be removed. The result of this module can be used in the module GeMoMa, AnnotationEvidence, and AnnotationFinalizer.

DenoiseIntrons may be called with 

java -jar GeMoMa-1.7.1.jar CLI DenoiseIntrons

and has the following parameters

name comment type
The following parameter(s) can be used multiple times:
i introns (Introns (GFF), which might be obtained from RNA-seq, mime = gff,gff3) FILE
The following parameter(s) can be used multiple times:
c coverage (experimental coverage (RNA-seq), range={UNSTRANDED, STRANDED}, default = UNSTRANDED) STRING
Parameters for selection "UNSTRANDED":
coverage_unstranded coverage_unstranded (The coverage file contains the unstranded coverage of the genome per interval. Intervals with coverage 0 (zero) can be left out., mime = bedgraph) FILE
Parameters for selection "STRANDED":
coverage_forward coverage_forward (The coverage file contains the forward coverage of the genome per interval. Intervals with coverage 0 (zero) can be left out., mime = bedgraph) FILE
coverage_reverse coverage_reverse (The coverage file contains the reverse coverage of the genome per interval. Intervals with coverage 0 (zero) can be left out., mime = bedgraph) FILE
m maximum intron length (The maximum length of an intron, default = 15000) INT
me minimum expression (The threshold for removing introns, valid range = [0.0, 1.0], default = 0.01) DOUBLE
context context (The context upstream a donor and donwstream an acceptor site that is used to determine the expression of the region, valid range = [0, 100], default = 10) INT
outdir The output directory, defaults to the current working directory (.) STRING

Example: 

java -jar GeMoMa-1.7.1.jar CLI DenoiseIntrons i=<introns> coverage_unstranded=<coverage_unstranded>


NCBI Reference Retriever

This tool can be used to download or update assembly and annotation files of reference organsims from NCBI. This way it allows to easily collect all data necessary to start GeMoMaPipeline or Extractor.

NCBI Reference Retriever may be called with 

java -jar GeMoMa-1.7.1.jar CLI NRR

and has the following parameters

name comment type
r reference directory (the directory where the genome and annotation files of the reference organisms should be stored, default = references/) STRING
n number of tries (the number of tries for downloading a reference file, valid range = [1, 100], default = 10) INT
rl reference list (a list of reference organisms, mime = txt) FILE
outdir The output directory, defaults to the current working directory (.) STRING

Example: 

java -jar GeMoMa-1.7.1.jar CLI NRR rl=<reference_list>


Extractor

This tool can be used to create input files for GeMoMa, i.e., it creates at least a fasta file containing the translated parts of the CDS and a tabular file containing the assignment of transcripts to genes and parts of CDS to transcripts. In addition, Extractor can be used to create several additional files from the final prediction, e.g. proteins, CDSs, ... . Two inputs are mandatory: The genome as fasta or fasta.gz and the corresponding annotation as gff or gff.gz. The gff file should be sorted. If you like to set a user-specific genetic code, please use a tab-delimited file with two columns. The first column contains the amino acid in one letter code, the second a list of tripletts.

Extractor may be called with 

java -jar GeMoMa-1.7.1.jar CLI Extractor

and has the following parameters

name comment type
a annotation (Reference annotation file (GFF or GTF), which contains gene models annotated in the reference genome, mime = gff,gff3,gtf) FILE
g genome (Reference genome file (FASTA), mime = fasta,fa,fas,fna,fasta.gz,fa.gz,fas.gz,fna.gz) FILE
gc genetic code (optional user-specified genetic code, mime = tabular, OPTIONAL) FILE
p proteins (whether the complete proteins sequences should returned as output, default = false) BOOLEAN
c cds (whether the complete CDSs should returned as output, default = false) BOOLEAN
genomic genomic (whether the genomic regions should be returned (upper case = coding, lower case = non coding), default = false) BOOLEAN
i introns (whether introns should be extracted from annotation, that might be used for test cases, default = false) BOOLEAN
u upcase IDs (whether the IDs in the GFF should be upcased, default = false) BOOLEAN
r repair (if a transcript annotation can not be parsed, the program will try to infer the phase of the CDS parts to repair the annotation, default = false) BOOLEAN
s selected (The path to list file, which allows to make only a predictions for the contained transcript ids. The first column should contain transcript IDs as given in the annotation. Remaining columns will be ignored., mime = tabular,txt, OPTIONAL) FILE
Ambiguity Ambiguity (This parameter defines how to deal with ambiguities in the DNA. There are 3 options: EXCEPTION, which will remove the corresponding transcript, AMBIGUOUS, which will use an X for the corresponding amino acid, and RANDOM, which will randomly select an amnio acid from the list of possibilities., range={EXCEPTION, AMBIGUOUS, RANDOM}, default = EXCEPTION) STRING
d discard pre-mature stop (if *true* transcripts with pre-mature stop codon are discarded as they often indicate misannotation, default = true) BOOLEAN
sefc stop-codon excluded from CDS (A flag that states whether the reference annotation contains the stop codon in the CDS annotation or not, default = false) BOOLEAN
f full-length (A flag which allows for choosing between only full-length and all (i.e., full-length and partial) transcripts, default = true) BOOLEAN
v verbose (A flag which allows to output a wealth of additional information, default = false) BOOLEAN
outdir The output directory, defaults to the current working directory (.) STRING

Example: 

java -jar GeMoMa-1.7.1.jar CLI Extractor a=<annotation> g=<genome>


GeneModelMapper

This tool is the main part of, a homology-based gene prediction tool. GeMoMa builds gene models from search results (e.g. tblastn or mmseqs).

As first step, you should run Extractor obtaining cds parts and assignment. Second, you should run a search algorithm, e.g. tblastn or mmseqs, with cds parts as query. Finally, these search results are then used in GeMoMa. Search results should be clustered according to the reference genes. The most easiest way is to sort the search results accoring to the first column. If the search results are not sorted by default (e.g. mmseqs), you should the parameter sort. If you like to run GeMoMa ignoring intron position conservation, you should blast protein sequences and feed the results in query cds parts and leave assignment unselected.

If you like to run GeMoMa using RNA-seq evidence, you should map your RNA-seq reads to the genome and run ERE on the mapped reads. For several reasons, spurious introns can be extracted from RNA-seq data. Hence, we recommend to run DenoiseIntrons to remove such spurious introns. Finally, you can use the obtained introns (and coverage) in GeMoMa.

If you like to obtain multiple predictions per gene model of the reference organism, you should set predictions accordingly. In addition, we suggest to decrease the value of contig threshold allowing GeMoMa to evaluate more candidate contigs/chromosomes.

If you change the values of contig threshold, region threshold and hit threshold, this will influence the predictions as well as the runtime of the algorithm. The lower the values are, the slower the algorithm is.

You can filter your predictions using GAF, which also allows for combining predictions from different reference organismns.

Finally, you can predict UTRs and rename predictions using AnnotationFinalizer.

If you like to run the complete GeMoMa pipeline and not only specific module, you can run the multi-threaded module GeMoMaPipeline.

GeneModelMapper may be called with 

java -jar GeMoMa-1.7.1.jar CLI GeMoMa

and has the following parameters

name comment type
s search results (The search results, e.g., from tblastn or mmseqs, mime = tabular) FILE
t target genome (The target genome file (FASTA), i.e., the target sequences in the blast run. Should be in IUPAC code, mime = fasta,fas,fa,fna,fasta.gz,fas.gz,fa.gz,fna.gz) FILE
c cds parts (The query cds parts file (FASTA), i.e., the cds parts that have been blasted, mime = fasta,fa,fas,fna) FILE
a assignment (The assignment file, which combines parts of the CDS to transcripts, mime = tabular, OPTIONAL) FILE
The following parameter(s) can be used zero or multiple times:
i introns (Introns (GFF), which might be obtained from RNA-seq, mime = gff,gff3) FILE
r reads (if introns are given by a GFF, only use those which have at least this number of supporting split reads, valid range = [1, 2147483647], default = 1) INT
splice splice (if no intron is given by RNA-seq, compute candidate splice sites or not, default = true) BOOLEAN
The following parameter(s) can be used zero or multiple times:
coverage coverage (experimental coverage (RNA-seq), range={UNSTRANDED, STRANDED}, default = UNSTRANDED) STRING
Parameters for selection "UNSTRANDED":
coverage_unstranded coverage_unstranded (The coverage file contains the unstranded coverage of the genome per interval. Intervals with coverage 0 (zero) can be left out., mime = bedgraph) FILE
Parameters for selection "STRANDED":
coverage_forward coverage_forward (The coverage file contains the forward coverage of the genome per interval. Intervals with coverage 0 (zero) can be left out., mime = bedgraph) FILE
coverage_reverse coverage_reverse (The coverage file contains the reverse coverage of the genome per interval. Intervals with coverage 0 (zero) can be left out., mime = bedgraph) FILE
g genetic code (optional user-specified genetic code, mime = tabular, OPTIONAL) FILE
sm substitution matrix (optional user-specified substitution matrix, mime = tabular, OPTIONAL) FILE
go gap opening (The gap opening cost in the alignment, default = 11) INT
ge gap extension (The gap extension cost in the alignment, default = 1) INT
m maximum intron length (The maximum length of an intron, default = 15000) INT
sil static intron length (A flag which allows to switch between static intron length, which can be specified by the user and is identical for all genes, and dynamic intron length, which is based on the gene-specific maximum intron length in the reference organism plus the user given maximum intron length, default = true) BOOLEAN
intron-loss-gain-penalty intron-loss-gain-penalty (The penalty used for intron loss and gain, default = 25) INT
e e-value (The e-value for filtering blast results, default = 100.0) DOUBLE
ct contig threshold (The threshold for evaluating contigs, valid range = [0.0, 1.0], default = 0.4) DOUBLE
rt region threshold (The threshold for evaluating regions, valid range = [0.0, 1.0], default = 0.9) DOUBLE
h hit threshold (The threshold for adding additional hits, valid range = [0.0, 1.0], default = 0.9) DOUBLE
p predictions (The (maximal) number of predictions per transcript, default = 10) INT
selected selected (The path to list file, which allows to make only a predictions for the contained transcript ids. The first column should contain transcript IDs as given in the annotation. Remaining columns can be used to determine a target region that should be overlapped by the prediction, if columns 2 to 5 contain chromosome, strand, start and end of region, mime = tabular,txt, OPTIONAL) FILE
as avoid stop (A flag which allows to avoid (additional) pre-mature stop codons in a transcript, default = true) BOOLEAN
approx approx (whether an approximation is used to compute the score for intron gain, default = true) BOOLEAN
pa protein alignment (whether a protein alignment between the prediction and the reference transcript should be computed. If so two additional attributes (iAA, pAA) will be added to predictions in the gff output. These might be used in GAF. However, since some transcripts are very long this can increase the needed runtime and memory (RAM)., default = true) BOOLEAN
prefix prefix (A prefix to be used for naming the predictions, default = ) STRING
tag tag (A user-specified tag for transcript predictions in the third column of the returned gff. It might be beneficial to set this to a specific value for some genome browsers., default = mRNA) STRING
v verbose (A flag which allows to output a wealth of additional information per transcript, default = false) BOOLEAN
timeout timeout (The (maximal) number of seconds to be used for the predictions of one transcript, if exceeded GeMoMa does not output a prediction for this transcript., valid range = [0, 604800], default = 3600) LONG
sort sort (A flag which allows to sort the search results, default = false) BOOLEAN
Score Score (A flag which allows to do nothing, re-score or re-align the search results, range={Trust, ReScore, ReAlign}, default = Trust) STRING
outdir The output directory, defaults to the current working directory (.) STRING

Example: 

java -jar GeMoMa-1.7.1.jar CLI GeMoMa s=<search_results> t=<target_genome> c=<cds_parts>


GeMoMa Annotation Filter

This tool combines and filters gene predictions from different sources yielding a common gene prediction. The tool does not modify the predictions, but filters redundant and low-quality predictions and selects relevant predictions. In addition, it adds attributes to the annotation of transcript predictions.

The algorithm does the following: First, redundant predictions are identified (and additional attributes (evidence, sumWeight) are introduced). Second, the predictions are filtered using the user-specified criterium based on the attributes from the annotation. Third, clusters of overlapping predictions are determined, the predictions are sorted within the cluster and relevant predictions are extracted.

Optionally, annotation info can be added for each reference organism enabling a functional prediction for predicted transcripts based on the function of the reference transcript. Phytozome provides annotation info tables for plants, but annotation info can be used from any source as long as they are tab-delimited files with at least the following columns: transcriptName, GO and .*defline.

Initially, GAF was build to combine gene predictions obtained from GeMoMa. It allows to combine the predictions from multiple reference organisms, but works also using only one reference organism. However, GAF also allows to integrate predictions from ab-initio or purely RNA-seq-based gene predictors as well as manually curated annotation. If you like to do so, we recommend to run AnnotationEvidence for each of these input files to add additional attributes that can be used for sorting and filtering within GAF. The sort and filter criteria need to be carefully revised in this case. Default values can be set for missing attributes.

GeMoMa Annotation Filter may be called with 

java -jar GeMoMa-1.7.1.jar CLI GAF

and has the following parameters

name comment type
t tag (the tag used to read the GeMoMa annotations, default = mRNA) STRING
c common border filter (the filter on the common borders of transcripts, the lower the more transcripts will be checked as alternative splice isoforms, valid range = [0.0, 1.0], default = 0.75) DOUBLE
m maximal number of transcripts per gene (the maximal number of allowed transcript predictions per gene, valid range = [1, 2147483647], default = 2147483647) INT
The following parameter(s) can be used multiple times:
p prefix (the prefix can be used to distinguish predictions from different input files, OPTIONAL) STRING
w weight (the weight can be used to prioritize predictions from different input files; each prediction will get an additional attribute sumWeight that can be used in the filter, valid range = [0.0, 1000.0], default = 1.0, OPTIONAL) DOUBLE
g gene annotation file (GFF file containing the gene annotations (predicted by GeMoMa), mime = gff,gff3) FILE
a annotation info (annotation information of the reference, tab-delimted file containing at least the columns transcriptName, GO and .*defline, mime = tabular, OPTIONAL) FILE
d default attributes (Comma-separated list of attributes that is set to NaN if they are not given in the annotation file. This allows to use these attributes for sorting or filter criteria. It is especially meaningful if the gene annotation files were received fom different software packages (e.g., GeMoMa, Braker, ...) having different attributes., default = tie,tde,tae,iAA,pAA,score) STRING
f filter (A filter can be applied to transcript predictions to receive only reasonable predictions. The filter is applied to the GFF attributes. The default filter decides based on the completeness of the prediction (start=='M' and stop=='*') and the relative score (score/aa>=0.75) whether a prediction is used or not. In addition, predictions without score (isNaN(score)) will be used as external annotations do not have the attribute score. Different criteria can be combined using 'and' and 'or'. A more sophisticated filter could be applied for instance using the completeness, the relative score, the evidence as well as statistics based on RNA-seq: start=='M' and stop=='*' and score/aa>=0.75 and (evidence>1 or tpc==1.0), default = start=='M' and stop=='*' and (isNaN(score) or score/aa>=0.75), OPTIONAL) STRING
s sorting (comma-separated list that defines the way predictions are sorted within a cluster, default = evidence,score) STRING
atf alternative transcript filter (If a prediction is suggested as an alternative transcript, this additional filter will be applied. The filter works syntactically like the 'filter' parameter and allows you to keep the number of alternative transcripts small based on meaningful criteria. Reasonable filter could be based on RNA-seq data (tie==1) or on evidence (evidence>1). A more sophisticated filter could be applied combining several criteria: tie==1 or evidence>1, default = tie==1 or evidence>1, OPTIONAL) STRING
outdir The output directory, defaults to the current working directory (.) STRING

Example: 

java -jar GeMoMa-1.7.1.jar CLI GAF g=<gene_annotation_file>


AnnotationFinalizer

This tool finalizes an annotation. It allows to predict for UTRs for annotated coding sequences and to generate generic gene and transcript names. UTR prediction might be negatively influenced (i.e. too long predictions) by genomic contamination of RNA-seq libraries, overlapping genes or genes in close proximity as well as unstranded RNA-seq libraries. Please use ERE to preprocess the mapped reads.

AnnotationFinalizer may be called with 

java -jar GeMoMa-1.7.1.jar CLI AnnotationFinalizer

and has the following parameters

name comment type
g genome (The genome file (FASTA), i.e., the target sequences in the blast run. Should be in IUPAC code, mime = fasta,fa,fas,fna,fasta.gz,fa.gz,fas.gz,fna.gz) FILE
a annotation (The predicted genome annotation file (GFF), mime = gff,gff3) FILE
t tag (A user-specified tag for transcript predictions in the third column of the returned gff. It might be beneficial to set this to a specific value for some genome browsers., default = mRNA) STRING
u UTR (allows to predict UTRs using RNA-seq data, range={NO, YES}, default = NO) STRING
No parameters for selection "NO"
Parameters for selection "YES":
The following parameter(s) can be used multiple times:
i introns file (Introns (GFF), which might be obtained from RNA-seq, mime = gff,gff3) FILE
r reads (if introns are given by a GFF, only use those which have at least this number of supporting split reads, valid range = [1, 2147483647], default = 1) INT
The following parameter(s) can be used multiple times:
c coverage file (experimental coverage (RNA-seq), range={NO, UNSTRANDED, STRANDED}, default = NO) STRING
No parameters for selection "NO"
Parameters for selection "UNSTRANDED":
coverage_unstranded coverage_unstranded (The coverage file contains the unstranded coverage of the genome per interval. Intervals with coverage 0 (zero) can be left out., mime = bedgraph) FILE
Parameters for selection "STRANDED":
coverage_forward coverage_forward (The coverage file contains the forward coverage of the genome per interval. Intervals with coverage 0 (zero) can be left out., mime = bedgraph) FILE
coverage_reverse coverage_reverse (The coverage file contains the reverse coverage of the genome per interval. Intervals with coverage 0 (zero) can be left out., mime = bedgraph) FILE
rename rename (allows to generate generic gene and transcripts names (cf. parameter "name attribute"), range={COMPOSED, SIMPLE, NO}, default = COMPOSED) STRING
Parameters for selection "COMPOSED":
p prefix (the prefix of the generic name) STRING
infix infix (the infix of the generic name, default = G) STRING
s suffix (the suffix of the generic name, default = 0) STRING
d digits (the number of informative digits, valid range = [4, 10], default = 5) INT
di delete infix (a comma-separated list of infixes that is deleted from the sequence names before building the gene/transcript name, default = ) STRING
Parameters for selection "SIMPLE":
p prefix (the prefix of the generic name) STRING
d digits (the number of informative digits, valid range = [4, 10], default = 5) INT
No parameters for selection "NO"
n name attribute (if true the new name is added as new attribute "Name", otherwise "Parent" and "ID" values are modified accordingly, default = true) BOOLEAN
outdir The output directory, defaults to the current working directory (.) STRING

Example: 

java -jar GeMoMa-1.7.1.jar CLI AnnotationFinalizer g=<genome> a=<annotation> p=<prefix>


Annotation evidence

This tool adds attributes to the annotation, e.g., tie, tpc, aa, start, stop. These attributes can be used, for instance, if the annotation is used in GAF. All predictions of the annotation are used. The predictions are not filtered for internal stop codons, missing start or stop codons, frame-shifts, ... . Please use ERE to preprocess the mapped reads.

Annotation evidence may be called with 

java -jar GeMoMa-1.7.1.jar CLI AnnotationEvidence

and has the following parameters

name comment type
a annotation (The genome annotation file (GFF,GTF), mime = gff,gff3,gtf) FILE
t tag (A user-specified tag for transcript predictions in the third column of the returned gff. It might be beneficial to set this to a specific value for some genome browsers., default = mRNA) STRING
g genome (The genome file (FASTA), i.e., the target sequences in the blast run. Should be in IUPAC code, mime = fasta,fas,fa,fna,fasta.gz,fas.gz,fa.gz,fna.gz) FILE
The following parameter(s) can be used multiple times:
i introns file (Introns (GFF), which might be obtained from RNA-seq, mime = gff,gff3, OPTIONAL) FILE
r reads (if introns are given by a GFF, only use those which have at least this number of supporting split reads, valid range = [1, 2147483647], default = 1) INT
The following parameter(s) can be used multiple times:
c coverage file (experimental coverage (RNA-seq), range={NO, UNSTRANDED, STRANDED}, default = NO) STRING
No parameters for selection "NO"
Parameters for selection "UNSTRANDED":
coverage_unstranded coverage_unstranded (The coverage file contains the unstranded coverage of the genome per interval. Intervals with coverage 0 (zero) can be left out., mime = bedgraph) FILE
Parameters for selection "STRANDED":
coverage_forward coverage_forward (The coverage file contains the forward coverage of the genome per interval. Intervals with coverage 0 (zero) can be left out., mime = bedgraph) FILE
coverage_reverse coverage_reverse (The coverage file contains the reverse coverage of the genome per interval. Intervals with coverage 0 (zero) can be left out., mime = bedgraph) FILE
ao annotation output (if the annotation should be returned with attributes tie, tpc, and aa, default = true) BOOLEAN
gc genetic code (optional user-specified genetic code, mime = tabular, OPTIONAL) FILE
outdir The output directory, defaults to the current working directory (.) STRING

Example: 

java -jar GeMoMa-1.7.1.jar CLI AnnotationEvidence a=<annotation> g=<genome>


Compare transcripts

This tool compares a predicted annotation with a given annotation in terms of F1 measure. If the F1 measure is 1 both annotations are in perfect agreement for this transcript. The smaller the value is the low is the agreement. If it is NA then there is no overlapping annotation.

Compare transcripts may be called with 

java -jar GeMoMa-1.7.1.jar CLI CompareTranscripts

and has the following parameters

name comment type
p prediction (The predicted annotation, mime = gff,gff3) FILE
a annotation (The true annotation, mime = gff,gff3) FILE
The following parameter(s) can be used zero or multiple times:
prefix prefix (the prefix can be used to distinguish predictions from different input files, default = , OPTIONAL) STRING
assignment assignment (the transcript info for the reference of the prediction, mime = tabular) FILE
outdir The output directory, defaults to the current working directory (.) STRING

Example: 

java -jar GeMoMa-1.7.1.jar CLI CompareTranscripts p=<prediction> a=<annotation>


Synteny checker

This tool can be used to determine syntenic regions between target organism and reference organism based on similiarity of genes.!The tool returns a table of reference genes per predicted gene. This table can be easily visualized with an R script that is included in the GeMoMa package.

Synteny checker may be called with 

java -jar GeMoMa-1.7.1.jar CLI SyntenyChecker

and has the following parameters

name comment type
t tag (the tag used to read the GeMoMa annotations, default = mRNA) STRING
The following parameter(s) can be used multiple times:
p prefix (the prefix can be used to distinguish predictions from different input files, OPTIONAL) STRING
a assignment (The assignment file, which combines parts of the CDS to transcripts, mime = tabular) FILE
g gene annotation file (GFF file containing the gene annotations predicted by GAF, mime = gff,gff3) FILE
outdir The output directory, defaults to the current working directory (.) STRING

Example: 

java -jar GeMoMa-1.7.1.jar CLI SyntenyChecker a=<assignment> g=<gene_annotation_file>


AddAttribute

This tool allows to add an additional attribute to specific features of an annotation.

Those additional attributes might be used in GAF for filtering or sorting or might be displayed in genome browsers like IGV or WebApollo. The user can choose binary attributes (true or false) or attributes with values according to given tab-delimited table.

AddAttribute may be called with 

java -jar GeMoMa-1.7.1.jar CLI AddAttribute

and has the following parameters

name comment type
a annotation (annotation file, mime = gff,gff3) FILE
f feature (a feature of the annotation, e.g., gene, transcript or mRNA, default = mRNA) STRING
attribute attribute (the name of the attribute that is added to the annotation) STRING
t table (a tab-delimited file containing IDs and additional attribute, mime = tabular) FILE
i ID column (the ID column in the tab-delimited file, valid range = [0, 2147483647]) INT
type type (type of addition attribute, range={VALUES, BINARY}, default = VALUES) STRING
Parameters for selection "VALUES":
ac attribute column (the attribute column in the tab-delimited file, valid range = [0, 2147483647]) INT
No parameters for selection "BINARY"
outdir The output directory, defaults to the current working directory (.) STRING

Example: 

java -jar GeMoMa-1.7.1.jar CLI AddAttribute a=<annotation> attribute=<attribute> t=<table> i=<ID_column> ac=<attribute_column>
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