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BioHPC Cloud:
: User Guide

 


BioHPC Cloud Software

There is 770 software titles installed in BioHPC Cloud. The sofware is available on all machines (unless stated otherwise in notes), complete list of programs is below, please click on a title to see details and instructions. Tabular list of software is available here

Please read details and instructions before running any program, it may contain important information on how to properly use the software in BioHPC Cloud.

454 gsAssembler or gsMapper, a5, ABRicate, ABruijn, ABySS, AdapterRemoval, adephylo, Admixtools, Admixture, agrep, albacore, Alder, AlleleSeq, ALLMAPS, ALLPATHS-LG, AMOS, AMPHORA, amplicon.py, AMRFinder, analysis, ANGSD, Annovar, antiSMASH, anvio, apollo, arcs, Arlequin, aspera, assembly-stats, atac-seq-pipeline, athena_meta, ATLAS, Atlas-Link, ATLAS_GapFill, ATSAS, Augustus, AWS command line interface, axe, BactSNP, bam2fastx, bamtools, bamUtil, BarNone, Basset, BayeScan, Bayescenv, BBmap, BCFtools, bcl2fastq, BCP, Beagle, Beast2, bedops, BEDtools, bfc, bgc, bgen, bigQF, bigWig, bioawk, biobambam, Bioconductor, biom-format, BioPerl, BioPython, Birdsuite, Bismark, blasr, BLAST, blast2go, BLAT, BLUPF90, BMGE, bmtagger, Boost, Bowtie, Bowtie2, BPGA, Bracken, BRAKER, BRAT-NextGen, BreedingSchemeLanguage, breseq, brocc, BSseeker2, BUSCO, BWA, bwa-meth, cactus, CAFE, canu, CAP3, CarveMe, cBar, CBSU RNAseq, CCTpack, cd-hit, cdbfasta, CEGMA, CellRanger, cellranger-atac, cellranger-dna, centrifuge, centroFlye, CFM-ID, CFSAN SNP pipeline, CheckM, chimera, chromosomer, Circlator, Circos, Circuitscape, CITE-seq-Count, CLUMPP, clust, Clustal Omega, CLUSTALW, Cluster, cmake, CNVnator, compat, CONCOCT, Conda, copyNumberDiff, cortex_var, CRISPRCasFinder, CRISPResso, CrossMap, CRT, cuda, Cufflinks, cutadapt, dadi, dadi-1.6.3_modif, danpos, dDocent, DeconSeq, Deepbinner, DeepTE, deepTools, defusion, delly, DESMAN, destruct, DETONATE, diamond, diploSHIC, discoal, Discovar, Discovar de novo, distruct, DiTASiC, DIYABC, Docker, dREG, dREG.HD, drep, Drop-seq, dropEst, dropSeqPipe, dsk, Dsuite, dTOX, duphold, dynare, ea-utils, ecopcr, ecoPrimers, ectyper, EDGE, edirect, eems, EgaCryptor, EGAD, EIGENSOFT, EMBOSS, Empress, entropy, ephem, epic2, ermineJ, ete3, exabayes, exonerate, ExpansionHunterDenovo-v0.8.0, eXpress, FALCON, FALCON_unzip, Fast-GBS, fasta, FastANI, fastcluster, FastME, FastML, fastp, FastQ Screen, fastq_pair, fastq_species_detector, FastQC, fastsimcoal26, fastStructure, FastTree, FASTX, feh, FFmpeg, fineRADstructure, fineSTRUCTURE, FIt-SNE, flash, flash2, flexbar, Flexible Adapter Remover, Flye, FMAP, FragGeneScan, FragGeneScan, freebayes, FunGene Pipeline, G-PhoCS, GAEMR, Galaxy, GATK, gatk4, gatk4amplicon.py, Gblocks, GBRS, gcc, GCTA, GDAL, gdc-client, GEM library, GEMMA, geneid, GeneMark, GeneMarker, Genome STRiP, GenomeMapper, GenomeStudio (Illumina), GenomeThreader, genometools, GenomicConsensus, gensim, GEOS, germline, gerp++, GET_PHYLOMARKERS, GffCompare, gffread, giggle, glactools, GlimmerHMM, GMAP/GSNAP, GNU Compilers, GNU parallel, go-perl, GO2MSIG, GoShifter, gradle-4.4, graftM, GraPhlAn, graphviz, GRiD, Grinder, GROMACS, GSEA, gsort, GTDB-Tk, GTFtools, Gubbins, GUPPY, hail, HapCompass, HAPCUT, HAPCUT2, hapflk, HaploMerger, Haplomerger2, HapSeq2, HarvestTools, hdf5, hh-suite, HiC-Pro, HiCExplorer, HISAT2, HMMER, Homer, HOTSPOT, HTSeq, htslib, HUMAnN2, hyperopt, HyPhy, iAssembler, IBDLD, IDBA-UD, IDP-denovo, idr, IgBLAST, IGoR, IGV, IMa2, IMa2p, IMAGE, ImageJ, ImageMagick, Immcantation, impute2, IMSA-A, INDELseek, infernal, Infomap, InStruct, Intel MKL, InteMAP, InterProScan, ipyrad, IQ-TREE, iRep, jags, Jane, java, jbrowse, JCVI, jellyfish, JoinMap, juicer, julia, jupyter, kallisto, Kent Utilities, keras, khmer, kinfin, king, KmerFinder, kraken, kSNP, kWIP, LACHESIS, lammps, LAST, lcMLkin, LDAK, leeHom, Lep-MAP3, lftp, Lighter, LinkedSV, LINKS, LocARNA, LocusZoom, lofreq, longranger, LS-GKM, LTR_retriever, LUCY, LUCY2, LUMPY, lyve-SET, MACE, MACS, MaCS simulator, MACS2, MAFFT, mafTools, Magic-BLAST, magick, MAKER, MAQ, MASH, mashtree, Mashtree, MaSuRCA, Mauve, MaxBin, McClintock, mccortex, mcl, MCscan, megahit, MeGAMerge, MEGAN, MELT, MEME Suite, MERLIN, MetaBAT, MetaCRAST, metaCRISPR, MetAMOS, MetaPathways, MetaPhlAn, MetaVelvet, MetaVelvet-SL, MGmapper, Migrate-n, mikado, MinCED, Minimac3, Minimac4, minimap2, mira, miRDeep2, MISO (misopy), MITObim, MiXCR, MixMapper, MKTest, mlst, MMAP, MMSEQ, MMseqs2, moments, mono, monocle3, mosdepth, mothur, MrBayes, mrsFAST, msld, MSMC, msprime, MSR-CA Genome Assembler, msstats, MSTMap, mugsy, MultiQC, multiz-tba, MUMmer, muscle, MUSIC, muTect, nag-compiler, nanofilt, Nanopolish, ncftp, NECAT, Nemo, Netbeans, NEURON, new_fugue, Nextflow, NextGenMap, nf-core/rnaseq, NGS_data_processing, NGSadmix, ngsDist, ngsF, ngsLD, NgsRelate, ngsTools, NGSUtils, NINJA, NLR-Annotator, NLR-Parser, Novoalign, NovoalignCS, NRSA, nvidia-docker, Oases, OBITools, Octave, OMA, openmpi, OrthoFinder, orthologr, Orthomcl, pacbio, PacBioTestData, PAGIT, paleomix, PAML, panaroo, pandas, pandaseq, PanPhlAn, Panseq, Parsnp, PASA, PASTEC, PAUP*, pb-assembly, pbalign, pbbam, pbh5tools, PBJelly, pbmm2, PBSuite, PCAngsd, pcre, pcre2, PeakRanger, PeakSplitter, PEAR, PEER, PennCNV, peppro, PfamScan, pgap, PGDSpider, ph5tools, Phage_Finder, PHAST, phenopath, Phobius, PHRAPL, PHYLIP, PhyloCSF, phyloFlash, phylophlan, PhyloPhlAn2, phylophlan3, PhyML, Picard, pigz, Pilon, Pindel, piPipes, PIQ, PlasFlow, Platypus, plink, plink2, Plotly, popbam, PopCOGenT, Porechop, portcullis, pplacer, PRANK, prinseq, prodigal, progenomics, progressiveCactus, PROJ, prokka, Proseq2, PSASS, psutil, pyani, PyCogent, pycoQC, pyfaidx, pyGenomeTracks, PyMC, pyopencl, pypy, pyRAD, Pyro4, PySnpTools, python, PyTorch, PyVCF, QIIME, QIIME2, QTCAT, Quake, Qualimap, QuantiSNP2, QUAST, QUMA, R, RACA, racon, RADIS, RadSex, RAPTR-SV, RAxML, raxml-ng, Ray, rclone, Rcorrector, RDP Classifier, REAGO, REAPR, ReferenceSeeker, Relate, RelocaTE2, RepeatMasker, RepeatModeler, RERconverge, RFMix, rgdal, RGI, Rgtsvm, ripgrep, rJava, RNAMMER, rnaQUAST, Rnightlights, Roary, Rqtl, Rqtl2, RSEM, RSeQC, RStudio, rtfbs_db, ruby, sabre, SaguaroGW, salmon, Sambamba, samblaster, sample, SampleTracker, samtabix, Samtools, Satsuma, Satsuma2, SCALE, scanorama, scikit-learn, Scoary, scythe, seaborn, SecretomeP, selscan, Sentieon, SeqPrep, seqtk, Seurat, sf, sgrep, sgrep sorted_grep, SHAPEIT, SHAPEIT4, shasta, Shiny, shore, SHOREmap, shortBRED, SHRiMP, sickle, SignalP, SimPhy, simuPOP, singularity, sinto, sistr_cmd, SKESA, skewer, SLiM, SLURM, smcpp, smoove, SMRT Analysis, SMRT LINK, snakemake, snap, SnapATAC, SNAPP, snATAC, SNeP, snippy, snp-sites, SnpEff, SNPgenie, SNPhylo, SNPsplit, SNVPhyl, SOAP2, SOAPdenovo, SOAPdenovo-Trans, SOAPdenovo2, SomaticSniper, sorted_grep, spaceranger, SPAdes, SPALN, SparCC, SPARTA, sqlite, SRA Toolkit, srst2, stacks, Stacks 2, stairway-plot, stampy, STAR, Starcode, statmodels, STITCH, STPGA, StrainPhlAn, strawberry, Strelka, stringMLST, StringTie, STRUCTURE, Structure_threader, supernova, SURPI, sutta, SV-plaudit, SVDetect, SVseq2, svtools, svtyper, SWAMP, SweepFinder, sweepsims, tabix, Taiji, Tandem Repeats Finder (TRF), tardis, TargetP, TASSEL 3, TASSEL 4, TASSEL 5, tbl2asn, tcoffee, TensorFlow, TEToolkit, texlive, tfTarget, ThermoRawFileParser, TMHMM, tmux, Tomahawk, TopHat, Torch, traitRate, Trans-Proteomic Pipeline (TPP), TransComb, TransDecoder, TRANSIT, transrate, TRAP, treeCl, treemix, Trim Galore!, trimal, trimmomatic, Trinity, Trinotate, tRNAscan-SE, UCSC Kent utilities, UMAP, UMI-tools, Unicycler, UniRep, unrar, usearch, Variant Effect Predictor, VarScan, VCF-kit, vcf2diploid, vcfCooker, vcflib, vcftools, vdjtools, Velvet, vep, VESPA, vg, ViennaRNA, VIP, viral-ngs, virmap, VirSorter, VirusDetect, VirusFinder 2, VizBin, vmatch, vsearch, vt, WASP, wgs-assembler (Celera), Wise2 (Genewise), Xander_assembler, yaha

Details for pgap (hide)

Name:pgap
Version:2020-03-11
OS:Linux
About:The NCBI Prokaryotic Genome Annotation Pipeline.
Added:10/9/2019 9:31:35 PM
Updated:3/11/2020 1:08:20 AM
Link:https://github.com/ncbi/pgap
Manual:https://github.com/ncbi/pgap/wiki
Notes:

#Reserve a computer. You need medium memory gen1 or  higher level BioHPC computer to do annotation. The pipeline use all available cpu cores on the computer. it would not work on the general computer (8-core and 16gb RAM). 

#Prepare software. This step might take up to one hour. If your internet connection is not stable, do it in "screen"

mkdir /workdir/$USER
cd /workdir/$USER
wget https://github.com/ncbi/pgap/raw/prod/scripts/pgap.py
chmod uog+x pgap.py 
./pgap.py -D singularity --update

#Run PGAP on test genome

cd /workdir/$USER
./pgap.py -D singularity -r -o mg37_results test_genomes/MG37/input.yaml
  • When you work with your own genome, you need to prepare .yaml input files, and keep the genome fasta in the same directory as .yaml file. You can either modify the example input.yaml file, or you can following instructions on this site: https://github.com/ncbi/pgap/wiki/Input-Files 
  • If you need to annotate many genomes during a period of time, it might be desirable to keep the PGAP version fixed during your project. If you work on a BioHPC rental machine, you might want to save the files in the /workdir directory to your home directory. Next time, you can copy the files back to /workdir to run annotation. 

*************************************************************************

Alternatively, you can use Docker (docker1 in BioHPC) to run pgap which gives you better control of the CPU and memory allocation for the container. With docker1, you will need to modify the pgap.py file before running it. Here is the procedure to use Docker.

mkdir -p /workdir/$USER/pgap
cd /workdir/$USER/pgap
wget https://github.com/ncbi/pgap/raw/prod/scripts/pgap.py
chmod uog+x pgap.py 
./pgap.py -D docker1 --update

Modify this line of pgap.py file:

self.cmd = [self.params.docker_cmd, 'run', '-i', '--rm' ]

To:

self.cmd = [self.params.docker_cmd, 'run', '-i', '--rm', '--noworkdir' ]

Run pgap:

./pgap.py -D docker1 -r -o mg37_results test_genomes/MG37/input.yaml

With Docker, you can use "--cpus 4" and/or "--memory 100g" to restrict CPU and memory allocated to a docker container. In our test, it does not work well.


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