Package: iqkm
iqKM (Identification and Quantification of KEGG Modules)iqKM is an easy to use pipeline to assign and/or quantify KEGG Orthology (KO) and KEGG modules (KMs) in metagenome/genome.iqKM-igenome.fna-oout_dir--help_dirhelp_dir
iqKM-imetagenome.fna-oout_dir--help_dirhelp_dir--fqraw_reads.fastq(.gz)--meta--quantify
iqKM-hDetailed pipeline walkthroughInstallationiqKM is a command line tool developed for Linux and macOS and is available to install fromgithub,biocondaorpypi.Install via conda (recommended)Installing iqKM via conda will automatically install all dependencies.Step 1: Create the iqKM environmentcondacreate-niqkm-cbiocondaiqKMStep 2: Download Kofam HMM db and help filescondaactivateiqkm# download help_dir, which contains Kofam HMM db and other help_fileswgetftp_link&&unziphelp_dirInstall via pipStep 1: Install third-party dependenciesBefore installing iqKM using pip, make sure the following softwares are on the system path, they are all easy-to-install tools.SoftwareVersionHMMER>=3.1Prodigal>=2.6.3bwa>= 0.7.17samtools>= 1.3.1Step 2: Install iqKMpipinstalliqKMStep 3: Download Kofam HMM db and help files# download help_dir, which contains Kofam HMM db and other help_fileswgetftp_link&&unziphelp_dirInstall from githubStep 1: Install third-party dependenciesBefore installing iqKM, make sure the following softwares are on the system path, they are all easy-to-install tools.SoftwareVersionHMMER>=3.1Prodigal>=2.6.3bwa>= 0.7.17samtools>= 1.3.1Step 2: Clone the repo and installgitclonehttps://github.com/lijingdi/iqKM.gitcd/path/to/iqKM
python3setup.pyinstallStep 3: Download Kofam HMM db and help files# go to our ftp site https://drive.google.com/u/0/uc?export=download&confirm=H3_U&id=1_Kxhox_hqrs7c_fVD8LC8mbwf4vp0ehX and download help_dir.zipunziphelp_dir&&cdhelp_dirpwd# /path/to/help_dir# now you can use above path as --help_dir /path/to/help_dir when running iqkmUsageBasic usageKMs assignment for individual genomesiqKM-igenome.fna-oout_dir--help_dirhelp_dirKMs assignment and quantification for individual genomesiqKM-igenome.fna-oout_dir--help_dirhelp_dir--fqraw_reads_1.fastq(.gz)--rqraw_reads_2.fastq(.gz)--quantifyKMs assignment for metagenomesiqKM-imetagenome.fna-oout_dir--help_dirhelp_dir--metaKMs assignment and quantification for metagenomesiqKM-imetagenome.fna-oout_dir--help_dirhelp_dir--fqraw_reads_1.fastq(.gz)--rqraw_reads_2.fastq(.gz)--meta--quantifyArgumentsiqKM -hiqkm -i input_genome -o out_dir[--fq fastq_1.gz] [--rq fastq_2.gz] [--prefix PREFIX] [--db HMMdb] [--com float] [--skip] [--quantify] [--meta] [-w] [-n int] [-f] [-d] [-g file]Required arguments-i, --inputinput genome/metagenome-o, --out_diroutput folder--help_dirFolder containing Kofam HMM database and essential help files, refer toinstallto downloadOptional arguments--fqinput first/single read file, fastq(.gz), only required when '--quantify' is specified--rqinput reverse read file, fastq(.gz), only required when '--quantify' is specified--prefixprefix of output files, default: input genome filename without postfix--dbYour customised Kofam HMM database, default=None--comKM completeness threshold (%) on contig basis, default=66.67--skipForce skipping steps if output files exist, default=False-q, --quantifyRun both KM assignment and quantification, default=False-m, --metaRun in metagenome mode, default=False-w,--include_weightsEnable normalizing KM abundance using KO weights, default=True-n, --threadsNumber of threads used for computation, default=1-f, --forceForce rerunning the whole pipeline, don't resume previous run, default=False-d, --distApply KM minimum distance threshold, default=True-g,--genome_equivalentGenome equivalent output generated from microbe-census, can be used for library-size normalization, optionalFiles outputoutputprodigal(intermediate output files)[prefix].cds[prefix].pep[prefix].gff[prefix].cds.bwa_index(only when '--quantify' is specified)hmmsearch(intermediate output files)[prefix]_hmmsearch.log[prefix]_hmmsearch.tblKO_parsing(intermediate output files)[prefix].koKM_assignment_unfiltered(intermediate output files)[prefix].summary.kegg_contigs.tsv[prefix].summary.kegg_pathways.tsvKM_assignment_filtered(KM assignment output)[prefix]_km_on_contig.tsv[prefix]_km_sample_count.tsvout_remap(intermediate output files, only when '--quantify' is specified)[prefix]_remapping.log[prefix]_unique.tabout_abundance(KM abundance output, only when '--quantify' is specified)km_abd_contig[prefix]_km_contig_abd.tsvkm_abd_sample[prefix]_km_sample_abd.tsvko_abd[prefix]_ko_abd.tsvAcknowledgementsAuthor of pipeline:Jingdi LiPrincipal Investigators:Rob FinnIf you find any errors or bugs, please do not hesitate to contactlijingdioo@outlook.comor open a new Issue thread on this github page, we will get back to you as soon as possible.