Chi Yen Tseng1, Christine M. Custer2, Thomas W. Custer2, Paul M. Dummer2, Natalie Karouna‐Renier3 and Cole W. Matson1
1Department of Environmental Science, The Institute of Ecological, Earth, and Environmental Sciences (TIE3S), and the Center for Reservoir and Aquatic Systems Research (CRASR), Baylor University, Waco, Texas 76798, United States
2Upper Midwest Environmental Sciences Center, U.S. Geological Survey, La Crosse, Wisconsin 54603, United States
3U.S. Geological Survey, Eastern Ecological Science Center (EESC) at Patuxent, Beltsville, Maryland 20705, United States
Corresponding author: Cole W. Matson cole_matson@baylor.edu
Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
trimmomatic-0.36.jar PE -phred33 {}_R1_001.fastq.gz {}_R2_001.fastq.gz {}_R1_qc.fq.gz {}_S1_fq.gz {}_R2_qc.fq.gz *_S2_fq.gz ILLUMINACLIP:TruSeqPE.fa:2:15:8:2 LEADING:5 TRAILING:5 SLIDINGWINDOW:4:15 MINLEN:36Star v2.6.1a
First generate contig index
STAR --runThreadN 8 \
--runMode genomeGenerate \
--genomeDir Renamed_tswallow_contig_index \
--genomeFastaFiles Renamed_tswallow_contig.fasta
Then run Star alignment
STAR --genomeDir Renamed_tswallow_contig_index \
--runThreadN 8 \
--readFilesCommand zcat \
--readFilesIn {}_R1_qc.fq.gz {}_R2_qc.fq.gz \
--outFileNamePrefix {}_ \
--outTmpDir {}_temp \
--alignIntronMin 10 \
--alignIntronMax 250000 \
--alignMatesGapMax 250000 \
--outSAMtype BAM SortedByCoordinate \
--outSAMunmapped Within \
--outSAMattributes Standard
Counts per gene were estimated using subread_-1.6.5-/featureCounts with parameter designed for paired-end and stranded estimation
featureCounts -T 8 -p -s 2 -t gene -a Tbic_Run3_2.renamed.putative_function.gff -o ts_16.featureCounts -g ID ts_16/*.bam
PROCESS BARCODE MATCH: 383244671 (93.90%) PROCESS BARCODE MISMATCH1: 2524728 (0.62%) PROCESS BARCODE AMBIGUOUS: 5288877 (1.30%) PROCESS BARCODE UNKNOWN: 17102415 (4.19%)
Run ARK+LINKS pipeline
Input files
draft assembly from supernova corrected by misassembly corrector Tigmint and generate supernova_hap1.tigmint.fa. The command tigmint-molecule groups linked reads with the same barcode into molecules. The command tigmint-cut identifies regions of the assembly that are not well supported by the linked reads, and cuts the contigs of the draft assembly at these positions. Tigmint may optionally scaffold the genome using ARCS.
barcoded_reads.fq.gz : barcode multiplicities generated from fastqbasic.sh longranger basic
Running the arks makefile with default parameters (except specify 16 threads, -j 0.5 for ARKS)
scripts are adapted from Introduction to Maker and MAKER Tutorial for WGS Assembly and Annotation Winter School 2018
Step 0, prepare all the input files including
Trinity --max_memory 200G --seqType fq --left $left --right $right --CPU 16 --full_cleanup --output trinity_out_dirless $WORKDIR/trinity.fasta |sed 's/;/\t/1'|awk '{print $1}' >Renamednematode_sp._22Aug2017_DZkUC.fastaRepeatModelermodule load repeatmodeler/1.0.10
BuildDatabase -name tswallow0db -engine ncbi tswallow.contig.fa
nohup RepeatModeler -database tswallow0db >& tswallow.out
UP000001645_9103,UP000016665_59894,UP000007754_59729,UP000000539_9031,UP000016666_8839,UP000053258_328815,UP000053875_118200,UP000053641_94827,UP000051836_12930,UP000054308_9244,UP000053858_50402,UP000053760_55661,UP000053584_441894,UP000053283_128390,UP000053872_8932,UP000198419_9014,UP000198323_9009,UP000190648_372326,UP000053286_9233,UP000053605_30419,UP000197619_299123,UP000053119_188379,UP000052976_85066,UP000054081_9238,UP000269221_333673.Step 1. start and edit maker ctrl files maker -CTL
make sure all the paths in maker_as_exe.ctl are correct. Check blastn, blastx, tblastx, repeatmasker, exonerate, snap, augustus (for gene modeling, I only run snap and augustus). And left default for maker_bopts.ctl
Run Maker step 1 to determine repeat region and predict genes from aligned EST (assembled transcriptome) and get repeats.gff, est2genome.gff , protein2genome.gff
#!/bin/bash
#PBS -k oe
#PBS -m abe
#PBS -M chi-yen_tseng@baylor.edu
#PBS -N Run_Maker
#PBS -l nodes=8:ppn=12,vmem=100gb,walltime=2:00:00:00
module load maker/2.31.9
module load openmpi/intel/2.1.0
MAKERDIR="TswallowMaker2"
cd /N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir
mpiexec -n 96 maker -base ${MAKERDIR} -fix_nucleotides
#rm ${MAKERDIR}.maker.output/${MAKERDIR}_master_datastore_index.log
maker -base ${MAKERDIR} -fix_nucleotides -dsindex
gff3_merge -d ${MAKERDIR}.maker.output/${MAKERDIR}_master_datastore_index.log
fasta_merge -d ${MAKERDIR}.maker.output/${MAKERDIR}_master_datastore_index.log
Using the following maker_opts.ctl (only list changed portion)
#-----Genome (these are always required)
genome=/N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/Renamed_tswallow_contig.fasta #genome sequence (fasta file or fasta embeded in GFF3 file)
organism_type=eukaryotic #eukaryotic or prokaryotic. Default is eukaryotic
#-----EST Evidence (for best results provide a file for at least one)
est=/N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/Renamed_transcriptome_combined.fa #set of ESTs or assembled mRNA-seq in fasta format
altest= #EST/cDNA sequence file in fasta format from an alternate organism
est_gff= #aligned ESTs or mRNA-seq from an external GFF3 file
altest_gff= #aligned ESTs from a closly relate species in GFF3 format
#-----Protein Homology Evidence (for best results provide a file for at least one)
protein=/N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/ave_proteome.fasta #protein sequence file in fasta format (i.e. from mutiple oransisms)
protein_gff= #aligned protein homology evidence from an external GFF3 file
#-----Repeat Masking (leave values blank to skip repeat masking)
model_org=all #select a model organism for RepBase masking in RepeatMasker
rmlib= /N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/consensi.fa.classified #provide an organism specific repeat library in fasta format for RepeatMasker
repeat_protein=/gpfs/hps/soft/rhel7/maker/2.31.9/data/te_proteins.fasta #provide a fasta file of transposable element proteins for RepeatRunner
rm_gff= #pre-identified repeat elements from an external GFF3 file
prok_rm=0 #forces MAKER to repeatmask prokaryotes (no reason to change this), 1 = yes, 0 = no
softmask=1 #use soft-masking rather than hard-masking in BLAST (i.e. seg and dust filtering)
#-----Gene Prediction
snaphmm= #SNAP HMM file
gmhmm= #GeneMark HMM file
augustus_species= #Augustus gene prediction species model
fgenesh_par_file= #FGENESH parameter file
pred_gff= #ab-initio predictions from an external GFF3 file
model_gff= #annotated gene models from an external GFF3 file (annotation pass-through)
est2genome=1 #infer gene predictions directly from ESTs, 1 = yes, 0 = no
protein2genome=1 #infer predictions from protein homology, 1 = yes, 0 = no
trna=0 #find tRNAs with tRNAscan, 1 = yes, 0 = no
snoscan_rrna= #rRNA file to have Snoscan find snoRNAs
unmask=0 #also run ab-initio prediction programs on unmasked sequence, 1 = yes, 0 = no
~~~
#-----MAKER Behavior Options
alt_splice=1 #Take extra steps to try and find alternative splicing, 1 = yes, 0 = no
Step 2 Round2 maker using previous aligned GFF files and run through SNAP predict model
Build SNAP training moedl
#!/bin/bash
#PBS -q debug
#PBS -k oe
#PBS -m abe
#PBS -M chi-yen_tseng@baylor.edu
#PBS -N Retrain_SNAP
#PBS -l nodes=1:ppn=16,vmem=64gb,walltime=00:59:00
module load maker
cd /N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/SNAP_training_workdir2
maker2zff TswallowMaker2.all.gff ## gff from aligned EST and close species proteins
fathom -categorize 1000 genome.ann2 genome.dna
fathom -export 1000 -plus uni.ann uni.dna
forge export.ann export.dna
hmm-assembler.pl TswallowMaker2 . > TswallowMaker2_2.hmm
Run maker gene prediction using SNAP training model
#!/bin/bash
#PBS -k oe
#PBS -m abe
#PBS -o /N/dc2/projects/Tswallow_GLRP/CT/scripts/error_output
#PBS -e /N/dc2/projects/Tswallow_GLRP/CT/scripts/error_output
#PBS -M chi-yen_tseng@baylor.edu
#PBS -N Run_Maker_Run2_SET3
#PBS -l nodes=8:ppn=12,vmem=96gb,walltime=1:00:00:00
##Run_Maker_Run2_SET3
##SNAP predictor: SNAP (1st training) predictor database N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/SNAP_training_workdir2/TswallowMaker2_2.hm
module load maker/2.31.9
module load openmpi/intel/2.1.0
##export AUGUSTUS_CONFIG_PATH=/N/u/tsengch/Carbonate/.augustus_config_CT
MAKERDIR="TswallowmakerRun_SET3_Run2"
cd /N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/maker_work_dir_SET3_Run2
maker -CTL
mv maker_opts.SET3_Run2 maker_opts.ctl
mpiexec -n 96 maker -base ${MAKERDIR} -fix_nucleotides
#rm ${MAKERDIR}.maker.output/${MAKERDIR}_master_datastore_index.log
maker -base ${MAKERDIR} -fix_nucleotides -dsindex
gff3_merge -d ${MAKERDIR}.maker.output/${MAKERDIR}_master_datastore_index.log
fasta_merge -d ${MAKERDIR}.maker.output/${MAKERDIR}_master_datastore_index.log
Using the following maker_opts.ctl
#-----Genome (these are always required)
genome=/N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/Renamed_tswallow_contig.fasta #genome sequence (fasta file or fasta embeded in GFF3 file)
organism_type=eukaryotic #eukaryotic or prokaryotic. Default is eukaryotic
#-----Re-annotation Using MAKER Derived GFF3
maker_gff= #MAKER derived GFF3 file
est_pass=0 #use ESTs in maker_gff: 1 = yes, 0 = no
altest_pass=0 #use alternate organism ESTs in maker_gff: 1 = yes, 0 = no
protein_pass=0 #use protein alignments in maker_gff: 1 = yes, 0 = no
rm_pass=0 #use repeats in maker_gff: 1 = yes, 0 = no
model_pass=0 #use gene models in maker_gff: 1 = yes, 0 = no
pred_pass=0 #use ab-initio predictions in maker_gff: 1 = yes, 0 = no
other_pass=0 #passthrough anyything else in maker_gff: 1 = yes, 0 = no
#-----EST Evidence (for best results provide a file for at least one)
est=##/N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/Renamed_transcriptome_combined.fa #set of ESTs or assembled mRNA-seq in fasta format
altest= #EST/cDNA sequence file in fasta format from an alternate organism
est_gff=/N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/TswallowMaker2.maker.output.Run1/TswallowMaker2.all.est2genome.gff #aligned ESTs or mRNA-seq from an external GFF3 file
altest_gff= #aligned ESTs from a closly relate species in GFF3 format
#-----Protein Homology Evidence (for best results provide a file for at least one)
protein=#/N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/ave_proteome.fasta #protein sequence file in fasta format (i.e. from mutiple oransisms)
protein_gff=/N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/TswallowMaker2.maker.output.Run1/TswallowMaker2.all.protein2genome.gff #aligned protein homology evidence from an external GFF3 file
#-----Repeat Masking (leave values blank to skip repeat masking)
model_org=all #select a model organism for RepBase masking in RepeatMasker
rmlib= #/N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/consensi.fa.classified #provide an organism specific repeat library in fasta format for RepeatMasker
repeat_protein=/gpfs/hps/soft/rhel7/maker/2.31.9/data/te_proteins.fasta #provide a fasta file of transposable element proteins for RepeatRunner
rm_gff=/N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/TswallowMaker2.maker.output.Run1/TswallowMaker2.all.repeats.gff #pre-identified repeat elements from an external GFF3 file
prok_rm=0 #forces MAKER to repeatmask prokaryotes (no reason to change this), 1 = yes, 0 = no
softmask=1 #use soft-masking rather than hard-masking in BLAST (i.e. seg and dust filtering)
#-----Gene Prediction
snaphmm=/N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/SNAP_training_workdir2/TswallowMaker2_2.hmm #SNAP HMM file
gmhmm= #GeneMark HMM file
augustus_species= #Augustus gene prediction species model
fgenesh_par_file= #FGENESH parameter file
pred_gff= #ab-initio predictions from an external GFF3 file
model_gff= #annotated gene models from an external GFF3 file (annotation pass-through)
est2genome=0 #infer gene predictions directly from ESTs, 1 = yes, 0 = no
protein2genome=0 #infer predictions from protein homology, 1 = yes, 0 = no
trna=0 #find tRNAs with tRNAscan, 1 = yes, 0 = no
snoscan_rrna= #rRNA file to have Snoscan find snoRNAs
unmask=0 #also run ab-initio prediction programs on unmasked sequence, 1 = yes, 0 = no
Train SNAP model again
## SNAPTraining_nd.sh-second SNAP training
module load maker
cd /N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/maker_work_dir_SET3_Run2
mkdir SNAP2ndTraining
cd SNAP2ndTraining
ln -s /N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/maker_work_dir_SET3_Run2/TswallowmakerRun_SET3_Run2.all.gff .
maker2zff TswallowmakerRun_SET3_Run2.all.gff
fathom -categorize 1000 genome.ann genome.dna
fathom -export 1000 -plus uni.ann uni.dna
forge export.ann export.dna
hmm-assembler.pl TswallowmakerRun_SET3_Run2 . > TswallowmakerRun_SET3_Run2.hmm
And using TswallowmakerRun_SET3_Run2.hmm for the following analysis
Step 3 Predict gene model using augustus trainning model followed by another round of SNAP training
Using busco as training environment for Augustus, adapted from
darencard/maker_genome_annotation.md
#!/bin/bash
#PBS -k oe
#PBS -m abe
#PBS -M chi-yen_tseng@baylor.edu
#PBS -N train_RunBUSCO
#PBS -l nodes=1:ppn=16,vmem=64gb,walltime=2:00:00:00
module load busco
cd /N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir
run_BUSCO.py -i TswallowMaker2.all.maker.transcripts1000.fasta -o TswallowMaker2_BUSCO_maker -l aves_odb9/ \
-m genome -c 8 --long -sp human -z --augustus_parameters='--progress=true
Run maker using AUGUSTUS
##makerRun3.1.sh - Run maker again with 2nd SNAP and BUSCO_Augustus_BUSCO_Tswallow_prediction_413945187 - Augustus (BUSCO chicken version)
##SNAP predictor: SNAP-/N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/maker_work_dir_SET3_Run2/SNAP2ndTraining/TswallowmakerRun_SET3_Run2.hmm (2nd training)
module load maker/2.31.9
module load openmpi/intel/2.1.0
export AUGUSTUS_CONFIG_PATH=/N/u/tsengch/Carbonate/.augustus_config_CT
MAKERDIR="TswallowmakerRun_SET3_Run3"
mkdir /N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/maker_work_dir_SET3_Run3
cd /N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/maker_work_dir_SET3_Run3
maker -CTL
mv ../maker_opts.ctl.SET3_Run3 maker_opts.ctl
mpiexec -n 96 maker -base ${MAKERDIR} -fix_nucleotides
#rm ${MAKERDIR}.maker.output/${MAKERDIR}_master_datastore_index.log
maker -base ${MAKERDIR} -fix_nucleotides -dsindex
gff3_merge -d ${MAKERDIR}.maker.output/${MAKERDIR}_master_datastore_index.log
fasta_merge -d ${MAKERDIR}.maker.output/${MAKERDIR}_master_datastore_index.log\
using maker_opts.ctl like this
#-----Gene Prediction
snaphmm=/N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/maker_work_dir_SET3_Run2/SNAP2ndTraining/TswallowmakerRun_SET3_Run2.hmm #SNAP HMM file
gmhmm= #GeneMark HMM file
augustus_species=BUSCO_Augustus_BUSCO_Tswallow_prediction_413945187 #Augustus gene prediction species model
fgenesh_par_file= #FGENESH parameter file
pred_gff= #ab-initio predictions from an external GFF3 file
model_gff= #annotated gene models from an external GFF3 file (annotation pass-through)
est2genome=0 #infer gene predictions directly from ESTs, 1 = yes, 0 = no
protein2genome=0 #infer predictions from protein homology, 1 = yes, 0 = no
trna=0 #find tRNAs with tRNAscan, 1 = yes, 0 = no
snoscan_rrna= #rRNA file to have Snoscan find snoRNAs
unmask=0 #also run ab-initio prediction programs on unmasked sequence, 1 = yes, 0 = no
Finally run again SNAP training
`#makerRun3.2.sh
## Run maker with 3rd SNAP and BUSCO_Augustus_BUSCO_Tswallow_prediction_413945187
##makerRun3.2.sh - Run maker again with 3rd SNAP and BUSCO_Augustus_BUSCO_Tswallow_prediction_413945187 - Augustus (BUSCO chicken version)
##SNAP predictor: SNAP-/N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/maker_work_dir_SET3_Run3/SNAP3rdTraining/TswallowmakerRun_SET3_Run3.hmm (3rd training)
module load maker/2.31.9
module load openmpi/intel/2.1.0
export AUGUSTUS_CONFIG_PATH=/N/u/tsengch/Carbonate/.augustus_config_CT
MAKERDIR="TswallowmakerRun_SET3_Run3_2"
mkdir /N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/maker_work_dir_SET3_Run3_2
cd /N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/maker_work_dir_SET3_Run3_2
maker -CTL
mv ../maker_opts.ctl.SET3_Run3_2 maker_opts.ctl
mpiexec -n 96 maker -base ${MAKERDIR} -fix_nucleotides
#rm ${MAKERDIR}.maker.output/${MAKERDIR}_master_datastore_index.log
maker -base ${MAKERDIR} -fix_nucleotides -dsindex
gff3_merge -d ${MAKERDIR}.maker.output/${MAKERDIR}_master_datastore_index.log
fasta_merge -d ${MAKERDIR}.maker.output/${MAKERDIR}_master_datastore_index.log
using maker_opts.ctl like this
#-----Gene Prediction
snaphmm=/N/dc2/projects/Tswallow_GLRP/CT/Tswallow_annotation/maker_work_dir/maker_work_dir_SET3_Run3/SNAP3rdTraining/TswallowmakerRun_SET3_Run3.hmm #SNAP HMM file
gmhmm= #GeneMark HMM file
augustus_species=BUSCO_Augustus_BUSCO_Tswallow_prediction_413945187 #Augustus gene prediction species model
fgenesh_par_file= #FGENESH parameter file
pred_gff= #ab-initio predictions from an external GFF3 file
model_gff= #annotated gene models from an external GFF3 file (annotation pass-through)
est2genome=0 #infer gene predictions directly from ESTs, 1 = yes, 0 = no
protein2genome=0 #infer predictions from protein homology, 1 = yes, 0 = no
trna=0 #find tRNAs with tRNAscan, 1 = yes, 0 = no
snoscan_rrna= #rRNA file to have Snoscan find snoRNAs
unmask=0 #also run ab-initio prediction programs on unmasked sequence, 1 = yes, 0 = no
Get TswallowmakerRun_SET3_Run3_2.all.gff as annotation end result
blastp to determine gene id. I ran against chicken, barn swallow, and zebra finch and use primary chicken as ortholog id
#PBS -k oe
#PBS -m abe
#PBS -o chicken_blastp.o
#PBS -e chicken_blastp.e
#PBS -M chi-yen_tseng@baylor.edu
#PBS -N chicken_blastp
#PBS -l nodes=1:ppn=8,vmem=24gb,walltime=6:00:00
module load blast/2.6.0+
cd $PBS_O_WORKDIR
## blastp against chicken proteome
blastp -query TswallowmakerRun_SET3_Run3_2.all.maker.proteins.fasta -db blastdb/Gallus_gallus_prot -evalue 1e-6 -max_hsps 1 -max_target_seqs 1 -outfmt 6 -out output.G_gallus.blastp
cp output.G_gallus.blastp /N/dc2/projects/Tswallow_GLRP/data/Tswallow_genome/Tswallow_annotation/output.G_gallus.renamed.blastp
module load maker
cd /N/dc2/projects/Tswallow_GLRP/data/Tswallow_genome/Tswallow_annotation
map_data_ids Tbic_Run3_2.all.maker.name.map output.G_gallus.renamed.blastp
rename the annotation
module load maker
## For cleanning and processing names
# create naming table (there are additional options for naming beyond defaults) with eight digit identifier
maker_map_ids --prefix TacBic --justify 8 TswallowmakerRun_SET3_Run3_2.all.gff > Tbic_Run3_2.all.maker.name.map
# replace names in GFF files
cp TswallowmakerRun_SET3_Run3_2.all.gff Tbic_Run3_2.all.gff
map_gff_ids Tbic_Run3_2.all.maker.name.map Tbic_Run3_2.all.gff
# replace names in FASTA headers
cp TswallowmakerRun_SET3_Run3_2.all.maker.transcripts.fasta Tbic_Run3_2.all.maker.transcripts.fasta
cp TswallowmakerRun_SET3_Run3_2.all.maker.proteins.fasta Tbic_Run3_2.all.maker.proteins.fasta
map_fasta_ids Tbic_Run3_2.all.maker.name.map Tbic_Run3_2.all.maker.transcripts.fasta
map_fasta_ids Tbic_Run3_2.all.maker.name.map Tbic_Run3_2.all.maker.proteins.fasta
# replace names in output of interproscan and blastp
cp /N/dc2/projects/Tswallow_GLRP/data/Tswallow_genome/Tswallow_annotation/uniprot_interpro_dir/blastp_result/finaloutput /N/dc2/projects/Tswallow_GLRP/data/Tswallow_genome/Tswallow_annotation/output.renamed.blastp
cp /N/dc2/projects/Tswallow_GLRP/data/Tswallow_genome/Tswallow_annotation/uniprot_interpro_dir/interproscan_result/output.iprscan /N/dc2/projects/Tswallow_GLRP/data/Tswallow_genome/Tswallow_annotation/output.renamed.iprscan
map_data_ids Tbic_Run3_2.all.maker.name.map output.renamed.iprscan
map_data_ids Tbic_Run3_2.all.maker.name.map output.renamed.blastp
# BUSCO version is: 3.0.2
# The lineage dataset is: aves_odb9 (Creation date: 2016-02-13, number of species: 40, number of BUSCOs: 4915)
# To reproduce this run: python /N/soft/rhel7/busco/3.0.2/scripts/run_BUSCO.py -i TswallowmakerRun_SET3_Run3_2.fasta -o TswallowmakerRun_SET3_Run3_2_aves -l aves_odb9/ -m transcriptome -c 4
#
# Summarized benchmarking in BUSCO notation for file TswallowmakerRun_SET3_Run3_2.fasta
# BUSCO was run in mode: transcriptome
C:85.5%[S:68.5%,D:17.0%],F:9.0%,M:5.5%,n:4915
4202 Complete BUSCOs (C)
3367 Complete and single-copy BUSCOs (S)
835 Complete and duplicated BUSCOs (D)
444 Fragmented BUSCOs (F)
269 Missing BUSCOs (M)
4915 Total BUSCO groups searched
# BUSCO version is: 3.0.2
# The lineage dataset is: vertebrata_odb9 (Creation date: 2016-02-13, number of species: 65, number of BUSCOs: 2586)
# To reproduce this run: python /N/soft/rhel7/busco/3.0.2/scripts/run_BUSCO.py -i TswallowmakerRun_SET3_Run3_2.fasta -o TswallowmakerRun_SET3_Run3_2_vertebrata -l vertebrata_odb9/ -m transcriptome -c 4
#
# Summarized benchmarking in BUSCO notation for file TswallowmakerRun_SET3_Run3_2.fasta
# BUSCO was run in mode: transcriptome
C:89.3%[S:67.6%,D:21.7%],F:8.5%,M:2.2%,n:2586
2310 Complete BUSCOs (C)
1748 Complete and single-copy BUSCOs (S)
562 Complete and duplicated BUSCOs (D)
219 Fragmented BUSCOs (F)
57 Missing BUSCOs (M)
2586 Total BUSCO groups searched
Reference Genome Modified Genome
---------------- ---------------
Total sequence length 1174359429 1174359429
Number of genes 22268 22268
Number of mRNAs 28304 28304
Number of exons 274051 274051
Number of introns 245747 245747
Number of CDS 28304 28304
Overlapping genes 2145 2145
Contained genes 441 441
CDS: complete 0 18688
CDS: start, no stop 0 2633
CDS: stop, no start 0 4664
CDS: no stop, no start 28304 2319
Total gene length 330963641 330963641
Total mRNA length 443505639 443505639
Total exon length 55891840 55891840
Total intron length 388105293 388105293
Total CDS length 42517977 42517977
Shortest gene 48 48
Shortest mRNA 48 48
Shortest exon 2 2
Shortest intron 4 4
Shortest CDS 6 6
Longest gene 1787792 1787792
Longest mRNA 1787792 1787792
Longest exon 21606 21606
Longest intron 193879 193879
Longest CDS 29967 29967
mean gene length 14863 14863
mean mRNA length 15669 15669
mean exon length 204 204
mean intron length 1579 1579
mean CDS length 1502 1502
% of genome covered by genes 28.2 28.2
% of genome covered by CDS 3.6 3.6
mean mRNAs per gene 1 1
mean exons per mRNA 10 10
mean introns per mRNA 9 9