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ccne: Carbapenemase-encoding gene Copy Number Estimator

Introduction

Carbapenemase-encoding gene Copy Number Estimator (ccne) is a tool to estimate the copy number of AMR genes. It uses housekeeping gene as the reference and compares the count of reads that mapped to AMR genes with the count of reads that mapped to the reference gene.

Quick start

ccne-fast

$ ccne-fast --amr KPC-2 --sp Kpn --in File.list --out result.txt --cpus 4
All finished! Enjoy!

$ ls
File.list result.txt SRR14561347_1.fastq.gz SRR14561347_2.fastq.gz

$ head File.list
SRR14561347	./SRR14561347_1.fastq.gz	./SRR14561347_2.fastq.gz

$ head result.txt
ID      rpoB reads depth        SD of rpoB reads depth  KPC-2 reads depth       SD of KPC-2 reads depth Estimated KPC-2 copy number
SRR14561347     653.944899478779        53.7865295303472        2006.6179138322 96.5807513871426        3.06848163420428

ccne-acc

$ ccne-acc --amr KPC-2 --in File.list --out result.txt --cpus 4
All finished! Enjoy!

$ ls
File.list result.txt SRR14561347_1.fastq.gz SRR14561347_2.fastq.gz  SRR14561347.fasta

$ head File.list
SRR14561347	./SRR14561347_1.fastq.gz	./SRR14561347_2.fastq.gz  SRR14561347.fasta

$ head result.txt
ID      Average reference reads depth   KPC-2 reads depth       Estimated KPC-2 copy number
SRR14561347     570     2127    3.73157894736842

Installation

Bioconda install with bioconda Anaconda-Server Badge

If you use Conda you can use the Bioconda channel:

#Add channels for bioconda
conda config --add channels defaults
conda config --add channels bioconda
conda config --add channels conda-forge
#Install ccne
conda install ccne

Too slow? Try mamba

mamba install ccne

Source

Install the latest version direct from Github.

$ cd $HOME

$ git clone https://github.com/biojiang/ccne.git

$ $HOME/ccne/bin/ccne --help

Check installation

Check the ccne version:

$ ccne --version

Check dependencies:
The ccne will check the dependencies automatically each time before running.

Usage

ccne-fast

Name:
  ccne-fast 1.1.0 by Jianping Jiang <jiangjianping@fudan.edu.cn>
Synopsis:
  Carbapenemase-encoding gene copy number estimator
Usage:
  ccne-fast --amr KPC-2 --sp Kpn --in File.list --out result.txt
General:
  --help             This help
  --version          Print version and exit
  --quiet            No screen output (default OFF)
Setup:
  --dbdir [X]        CCNE database root folders (default '$CCNE_bin/db')
  --listdb           List all configured AMRs
  --listsp           List all configured species and housekeeping genes
  --fmtdb            Format all the bwa index
Input:
  --amr [X]          AMR gene name, such as KPC-2, NDM-1, etc or AMR ID. Please refer to --listdb (required)
  --sp [X]           Species name[Kpn|Eco|Aba|Pae|Pls|...]. Please refer to --listsp. (required)
  --ref [X]          Reference gene defalut(such as Kpn:rpoB Aba:rpoB Eco:polB Pae:pps), please refer to --listsp. Note: When --sp is set to Pls, this parameter should be set to a replicon type.
  --in [X]           Input file name (required)
Outputs:
  --out [X]          Output file name (required)
Computation:
  --flank [N]        The flanking length of sequence to be excluded (default '0')
  --cpus [N]         Number of CPUs to use (default '1')
  --multiref         Use the reads depth of all the available sequences (default OFF)

ccne-acc

Name:
  ccne-acc 1.1.0 by Jianping Jiang <jiangjianping@fudan.edu.cn>
Synopsis:
  Carbapenemase-encoding gene copy number estimator
Usage:
  ccne-acc --amr KPC-2 --in File.list --out result.txt
General:
  --help             This help
  --version          Print version and exit
  --quiet            No screen output (default OFF)
Setup:
  --dbdir [X]        CCNE database root folders (default '$CCNE_bin/db')
  --listdb           List all configured AMRs
  --fmtdb            Format all the bwa index
Input:
  --amr [X]          AMR gene name, such as KPC-2, NDM-1, etc or AMR ID. Please refer to --listdb (required)
  --in [X]           Input file name (required)
Outputs:
  --out [X]          Output file name (required)
Computation:
  --cpus [N]         Number of CPUs to use (default '1')

Running

Input Requirements

ccne-fast

  • Sequence read file(s) in FASTQ format (can be .gz compressed) format
  • AMR gene name (refer to --listdb)
  • The species code ( refer to --listsp or species code table)

ccne-acc

  • Sequence read file(s) in FASTQ format (can be .gz compressed) format
  • AMR gene name (refer to --listdb)
  • The genome assembly

Output File

The ccne will output the result to the file with the name the user provided.

Columns in the output file

ccne-fast

Name Description
ID The sample ID user provided in the input file
rpoB reads coverage The estimated reads coverage of the input reference housekeeping gene
SD of rpoB reads coverage The standard deviation of rpoB reads coverage
KPC-2 reads coverage The estimated reads coverage of the input carbapenemase-encoding gene
SD of KPC-2 reads coverage The standard deviation of KPC-2 reads coverage
Estimated KPC-2 copy number Divide the reads coverage of AMR gene into that of housekeeping gene

ccne-acc

Name Description
ID The sample ID user provided in the input file
Average reads coverage The estimated reads coverage of the genome
KPC-2 reads coverage The estimated reads coverage of the input carbapenemase-encoding gene
Estimated KPC-2 copy number Divide the reads coverage of AMR gene into that of housekeeping gene

Tutorial

  1. Fetch the reads files (SRR14561347) in fastq format from NCBI SRA database. (SRR14561347 generated from a Klebsiella pneumoinae clinical isolate with triple KPC-2 encoding genes on the plasmid)
$ fasterq-dump --split-3 SRR14561347
  1. Copy input file templete from templete folder.
$ cp ./templete/templete.list File.list
  1. Modify the input file.
$ head File.list
SRR14561347	./SRR14561347_1.fastq.gz	./SRR14561347_2.fastq.gz
  1. Run ccne-fast or ccne-acc.
$ ccne-fast --amr KPC-2 --sp Kpn --in File.list --out result.txt

or

$ ccne-acc --amr KPC-2 --in File.list --out result.txt
  1. Check the result.
$ head result.txt
ID      rpoB reads depth        SD of rpoB reads depth  KPC-2 reads depth       SD of KPC-2 reads depth Estimated KPC-2 copy number
SRR14561347     653.944899478779        53.7865295303472        2006.6179138322 96.5807513871426        3.06848163420428

AMR genes (2412 genes) in ccne

Antimicrobial agents Subtypes Gene or protein names1
Aminoglycosides AAC(2')(7), AAC(3)(20), AAC(6')(65), ANT(2'')(1), ANT(3'')(35), ANT(4')(4), ANT(6)(5), ANT(9)(2), APH(2'')(7), APH(3'')(3), APH(3')(18), APH(4)(2), APH(6)(7), APH(7'')(1), APH(9)(3), ApmA(1), ArmA(1), KamB(1), NpmA(1), RmtA(1), RmtB(1), RmtC(1), RmtD(2), RmtE(2), RmtF(1), RmtG(1), RmtH(1), SAT(3), Sgm(1), Sta(1), StrA(1), StrB(1)
β-lactams β-lactamase ACC(4), ACT(35), ADC(14), AER(1), AIM(1), AQU(3), ARL(6), AST-1(1), AmpC1(1), BAT-1(1), BCL-1(1), BIL(1), BJP(1), BPU-1(1), BRO(3), BUT-1(1), BcI(1), BcII(1), Bla1(1), Bla2(1), CAM-1(1), CARB(20), CAU(1), CBP(1), CKO(1), CMH(1), CMY(114), CPS(1), CblA(1), CepS(1), CfiA(1), CfxA(4), CphA(10), DHA(19), EBR(1), ESP(1), FEZ(1), FONA(6), FOX(9), FTU(1), GES(4), GIM(2), GOB(13), HERA(7), HMB(1), IND(16), JOHN-1(1), KHM(1), L1(1), LAP(2), LCR(1), LHK(1), LRA(13), MIR(16), MOX(9), MSI(2), MUS(2), NPS(1), OXA(114), PC1(1), PDC(10), PEDO(3), PNGM(1), R39(1), RCP(1), RHO(1), RM3(1), ROB(2), RSA(2), SCO(1), SDA-A(1), SED(1), SFB(1), SIM(1), SLB(1), SMB(1), SPG(1), SRT(1), TEM(51), THIN-B(1), TMB(1), TRU(1), TUS(1), blaA(1), blaB21(1), blaF(1)
β-lactams ESBL ACI(1), ADC(32), BEL(3), BES(1), CARB(1), CGA(1), CIA(4), CME(1), CMY(5), CTX-M(141), CepA(1), CfxA(3), DES(1), ERP(1), FAR(1), GES(9), OCH(8), OXA(25), OXY(24), PDC(3), PER(7), SFO-1(1), SHV-OKP-LEN(42), SRT(1), TEM(84), TLA(4), VEB(10)
β-lactams Carbapenem BIC(1), BKC(1), CGB(1), CTX-M(1), DIM(1), EBR(1), FIM(1), FPH(1), FRI(3), GES(13), IMI(7), IMP(48), KPC(20), NDM(27), OXA(300), SFH(1), SME(5), SPM(1), TMB(1), VCC(1), VIM(40)
β-lactams Chromosomal β-lactamase SHV-OKP-LEN(163)
β-lactams Inhibitor-resistant β-lactamase SHV-OKP-LEN(6), TEM(23)
β-lactams Inhibitor-resistant ESBL TEM(9)
Colistin ICR-Mo(1), Mcr1(14), Mcr2(2), Mcr3(12), Mcr4(5), Mcr5(2), Mcr6(1), Mcr7(1), Mcr8(1), Mcr9(1)
Fosfomycin Fom(2), FosA(4), FosB(7), FosC(2), FosD(1), FosK(1), FosX(2)
Fluoroquinolone CrpP(1), NorA(1), QepA(1), Qnr(1), QnrA(7), QnrB(71), QnrC(1), QnrD(2), QnrE(2), QnrS(12), QnrVC(6)
Glycopeptide VanA(1), VanB(1), VanC(1), VanD(1), VanE(1), VanF(1), VanG(1), VanHA(1), VanHB(1), VanHD(1), VanHE(1), VanHM(1), VanHO(1), VanI(1), VanJ(1), VanL(1), VanM(1), VanN(1), VanO(1), VanRA(1), VanRB(1), VanRC(1), VanRD(1), VanRE(1), VanRF(1), VanRG(1), VanRI(1), VanRL(1), VanRM(1), VanRN(1), VanRO(1), VanSA(1), VanSB(1), VanSC(1), VanSD(1), VanSE(1), VanSF(1), VanSG(1), VanSL(1), VanSM(1), VanSN(1), VanSO(1), VanTC(1), VanTE(1), VanTG(1), VanTN(1), VanTmL(1), VanTrL(1), VanUG(1), VanVB(1), VanWB(1), VanWG(1), VanWI(1), VanXA(1), VanXB(1), VanXD(1), VanXE(1), VanXI(1), VanXM(1), VanXO(1), VanXYC(1), VanXYE(1), VanXYG(1), VanXYL(1), VanXYN(1), VanYA(1), VanYB(1), VanYD(1), VanYF(1), VanYG1(1), VanYM(1), VanZA(1), VanZF(1)
Macrolides CarA(1), CfrA(1), CfrB(1), CfrC(1), Emt(1), EreA(2), EreB(1), EreD(1), Erm(47), LinG(1), LnuA(1), LnuB(1), LnuC(1), LnuD(1), LnuF(2), LnuG(1), LnuP(1), LsaA(1), LsaB(1), LsaC(1), LsaE(1), MefB(1), Mel(1), MgtA(1), MphA(1), MphB(2), MphC(2), MphE(2), MphF(1), MphG(1), MphH(1), MphI(1), MphJ(1), MphK(1), MphL(1), MphM(1), MphN(1), MphO(1), MsrA(2), MsrC(2), MsrE(1), MyrA(1), OleB(1), OleC(1), OleD(1), OleI(1), OptrA(1), PoxtA(1), SrmB(1), TirC(1), TvaA(1), VatA(1), VatB(1), VatC(1), VatD(2), VatE(1), VatF(1), VatH(1), VatI(1), VgaA(2), VgaB(1), VgaC(1), VgaD(1), VgaE(2), VgbA(1), VgbB(1), VgbC(1), VmlR(1), clbB(1), clbC(1), clcD(1), gimA(1)
Phenicols Cat(33), CatBx(1), CmlA(5), CmlB(2), CmlR(1), CmlV(1), Cmr(1), CmrA(2), FloR(2), PexA(1)
Rifampin Arr(7), IRI(1), RphB(1)
Sulfonamide Sul(4)
Tetracycline OtrA(1), OtrB(1), OtrC(1), Tcr3(1), Tet-30(1), Tet-31(1), Tet-32(2), Tet-33(1), Tet-35(1), Tet-36(1), Tet-37(1), Tet-38(1), Tet-39(1), Tet-40(1), Tet-41(1), Tet-42(1), Tet-43(1), Tet-44(1), Tet-45(1), Tet-48(1), Tet-49(1), Tet-50(1), Tet-51(1), Tet-52(1), Tet-53(1), Tet-54(1), Tet-55(1), Tet-56(1), Tet-59(1), TetA(7), TetB(6), TetC(1), TetD(1), TetE(2), TetG(2), TetH(2), TetJ(1), TetK(1), TetL(2), TetM(2), TetO(1), TetQ(1), TetS(1), TetT(1), TetU(1), TetV(1), TetW(2), TetX(1), TetY(1), TetZ(1)
Tigecycline TetX(2), tmexC(1), tmexD(1), toprJ(1)
Trimethoprim Dfr(52)

1Numbers in the last brackets are the number of alleles. Details refer to CARD AMR genes in Kleborate.

Supported species in ccne-fast

Class Group/Family Genus Species
Aerobic Gram-positive cocci
Staphlococcaceae Staphylococcus Staphylococcus aureus, Staphylococcus epidermidis, Staphylococcus haemolyticus, Stapylococcus hominis, Staphylococcus lugdunensis, Staphylococcus pseudintermedius
Streptococcaceae Streptococcus Streptococcus agalactiae, Streptococcus canis, Streptococcus dysgalactiae, Streptococcus gallolyticus, Streptococcus oralis, Streptococcus pneumoniae, Streptococcus pyogenes, Streptococcus suis, Streptococcus thermophilus, Streptococcus uberis, Streptococcus equi
Enterococcaceae Enterococcus Enterococcus faecalis, Enterococcus faecium
Aerobic Gram-positive bacillus
Listeriaceae Listeria Listeria monocytogenes
Lactobacillaceae Lactobacillus Lactobacillus salivarius
Bacillaceae Bacillus Bacillus cereus, Bacillus licheniformis, Bacillus subtilis
Corynebacteriaceae Corynebacterium Corynebacterium diphtheriae
Streptomycetaceae Streptomyces Streptomyces spp.
Mycobacteriaceae Mycobacterium Mycobacterium abscessus, Mycobacterium massiliense
Aerobic Gram-negative cocci
Neisseriaceae Neisseria Neisseria spp.
Moraxellaceae Moraxella Moraxella catarrhalis
Aerobic Gram-negative bacillus
Enterobacteriaceae Escherichia Escherichia spp.
Shigella Shigella spp.
Salmonella Salmonella enterica
Yersinia Yersinia spp., Yersinia pseudotuberculosis, Yersinia ruckeri
Klebsiella Klebsiella oxytoca, Klebsiella pneumoniae, Klebsiella aerogenes
Enterobacter Enterobacter cloacae
Citrobacter Citrobacter freundii
Serratia Serratia marcescens
Proteus Proteus mirabilis
Edwardsiella Edwardsiella tarda
Aerobic Gram-negative bacillus (Non-Enterobacteriaceae)
Aeromonadaceae Aeromonas Aeromonas spp.
Vibrionaceae Vibrio Vibrio cholerae, Vibrio spp., Vibrio parahaemolyticus, Vibrio tapetis, Vibrio vulnificus
Aerobic Gram-negative bacillus (Sugar unfermented)
Pseudomonadaceae Pseudomonae Pseudomonas aeruginosa, Pseudomonas fluorescens
Moraxellaceae Acinetobacter Acinetobacter baumannii
Flavobacteriaceae Flavobacterium Flavobacterium psychrophilum
Burkholderiaceae Burkholderia Burkholderia cepacia, Burkholderia pseudomallei
Xanthomonadaceae Stenotrophomonas Stenotrophomonas maltophilia
Alcaligenaceae Achromobacter Achromobacter spp.
Other aerobic Gram-negative bacteria
Pasteurellaceae Hemophilus Haemophilus influenzae, Haemophilus parasuis, Haematopinus suis
Neisseriaceae Kingella Kingella kingae
Alcaligenaceae Bordetella Bordetella pertussis
Pasteurellaceae Pasteurella Pasteurella multocida
Bartonellaceae Bartonella Bartonella henselae
Anaerobic Gram-positive bacillus (Non-Spore-Forming)
Propionibacteriaceae Propionibacterium Propionibacterium acnes
Anaerobic Gram-positive bacillus (Spore-Forming)
Clostridiaceae Clostridium Clostridium botulinum, Clostridium difficile, Clostridium septicum
Anaerobic Gram-negativ bacillus
Porphyromonasaceae Porphyromonas Porphyromonas gingivalis
Gram-negative Campylobacter and Helicobacter
Campylobacteraceae Campylobacter Campylobacter coli, Campylobacter jejuni, Campylobacter concisus, Campylobacter fetus, Campylobacter helveticus, Campylobacter hyointestinalis, Campylobacter insulaenigrae, Campylobacter lanienae, Campylobacter lari, Campylobacter sputorum, Campylobacter upsaliensis
Arcobacter Arcobacter spp.
Helicobacteraceae Helicobacte Helicobacter cinaedi, Helicobacter pylori
Spirochetes
Leptospiraceae Leptospira Leptospira
Borrelia Borrelia spp.
Brachyspira Brachyspira hampsonii, Brachyspira hyodysenteriae, Brachyspira intermedia, Brachyspira pilosicoli, Brachyspira
Mycoplasma, Chlamydia etc.
Mycoplasmataceae Mycoplasma Mycoplasma agalactiae, Mycoplasma bovis, Mycoplasma hyorhinis
Chlamydiaceae Chlamydia Chlamydia spp.
Rickettsiaceae Orientia Orientia tsutsugamushi
Other
Anaplasma aphagocytophilum
Peptoclostridium difficile
Carnobacterium maltaromaticum
Cronobacter spp.
Mannheimia haemolytica
Melissococcus plutonius
Ornithobacterium rhinotracheale
Paenibacillus larvae
Pediococcus pentosaceus
Riemerella anatipestifer
Sinorhizobium spp.
Taylorella spp.
Tenacibaculum spp.
Wolbachia spp.
Xylella fastidiosa

Species codes and default housekeeping genes

Codes in ccne Species Default housekeeping genes
Aba Acinetobacter baumannii rpoB
Ach Achromobacter spp. rpoB
Aer Aeromonas spp. gltA
Arc Arcobacter spp. gltA
Aap Anaplasma aphagocytophilum atpA
Bcc Burkholderia cepacia atpD
Bce Bacillus cereus glp
Bha Brachyspira hampsonii adh
Bhe Bartonella henselae rpoB
Bhy Brachyspira hyodysenteriae adh
Bin Brachyspira intermedia adh
Bli Bacillus licheniformis rpoB
Bpe Bordetella pertussis adk
Bor Borrelia spp. clpA
Bpi Brachyspira pilosicoli adh
Bps Burkholderia pseudomallei ace
Bra Brachyspira spp. adh
Bsu Bacillus subtilis glpF
Cco Campylobacter coli aspA
Cje Campylobacter jejuni aspA
Cbo Clostridium botulinum rpoB
Ccn Campylobacter concisus aspA
Cdi Clostridium difficile adk
Pdi Peptoclostridium difficile adk
Cdp Corynebacterium diphtheriae rpoB
Cfe Campylobacter fetus aspA
Cfr Citrobacter freundii mdh
Che Campylobacter helveticus aspA
Chl Chlamydia spp. enoA
Chy Campylobacter hyointestinalis aspA
Cin Campylobacter insulaenigrae aspA
Cla Campylobacter lanienae aspA
Clr Campylobacter lari adk
Cma Carnobacterium maltaromaticum dapE
Cro Cronobacter spp. atpD
Cse Clostridium septicum ddl
Csp Campylobacter sputorum aspA
Cup Campylobacter upsaliensis adk
Ecl Enterobacter cloacae rpoB
Eco Escherichia spp. rpoB
Shi Shigella spp. rpoB
Eta Edwardsiella tarda adk
Efa Enterococcus faecalis aroE
Efm Enterococcus faecium adk
Fps Flavobacterium psychrophilum atpA
Hci Helicobacter cinaedi aroE
Hin Haemophilus influenzae adk
Hpa Haemophilus parasuis rpoB
Hpy Helicobacter pylori atpA
Hsu Haematopinus suis atpA
Kki Kingella kingae abcZ
Kox Klebsiella oxytoca rpoB
Kpn Klebsiella pneumoniae rpoB
Kae Klebsiella aerogenes rpoB
Lep Leptospira spp. adk
Lmo Listeria monocytogenes abcZ
Lsa Lactobacillus salivarius nrdB
Mab Mycobacterium abscessus rpoB
Mag Mycoplasma agalactiae dnaA
Mbo Mycoplasma bovis adh1
Mca Moraxella catarrhalis abcZ
Mha Mannheimia haemolytica adk
Mhy Mycoplasma hyorhinis rpoB
Mma Mycobacterium massiliense rpoB
Mpl Melissococcus plutonius argE
Nei Neisseria spp. abcZ
Orh Ornithobacterium rhinotracheale mdh
Ots Orientia tsutsugamushi mdh
Pac Propionibacterium acnes aroE
Pae Pseudomonas aeruginosa ppsA
Pfl Pseudomonas fluorescens glnS
Pgi Porphyromonas gingivalis ftsQ
Pla Paenibacillus larvae rpoB
Pmu Pasteurella multocida adk
Ppe Pediococcus pentosaceus dalR
Ran Riemerella anatipestifer rpoB
Sag Streptococcus agalactiae adhP
Pau Staphylococcus aureus arcC
Sca Streptococcus canis gki
Sdy Streptococcus dysgalactiae atoB
Sen Salmonella enterica aroC
Sep Staphylococcus epidermidis arcC
Sga Streptococcus gallolyticus aroE
Sha Staphylococcus haemolyticus arcC
Sho Stapylococcus hominis arcC
Sin Sinorhizobium spp. asd
Slu Staphylococcus lugdunensis aroE
Sma Stenotrophomonas maltophilia atpD
Sor Streptococcus oralis aroE
Spn Streptococcus pneumoniae aroE
Sps Staphylococcus pseudintermedius ack
Spy Streptococcus pyogenes gki
Ssu Streptococcus suis aroA
Sth Streptococcus thermophilus rpoB
Str Streptomyces spp. atpD
Sub Streptococcus uberis arcC
Seq Streptococcus equi arcC
Tay Taylorella spp. adk
Ten Tenacibaculum spp. atpA
Vch Vibrio cholerae adk
Vib Vibrio spp. atpA
Vpa Vibrio parahaemolyticus dnaE
Vta Vibrio tapetis atpA
Vvu Vibrio vulnificus dtdS
Wol Wolbachia spp. coxA
Xfa Xylella fastidiosa cysG
Yer Yersinia spp. aarF
Yps Yersinia pseudotuberculosis adk
Yru Yersinia ruckeri glnA
Smr Serratia marcescens rpoC
Pmi Proteus mirabilis rpoB

Species in blod are most commonly isolated species in clinical. (Data come from the CHINET)

Q&A

  1. How the reference genes in ccne were determined?

    The reference genes in ccne are single copy housekeeping genes. If the species has been curated in pubMLST, then the hosuekeeping genes in pubMLST will be used. Usually, the fisrt allele will be used as the reference in ccne. Otherwise, the reference genome and gene model of the species will be download from NCBI GenBank. The busco is used to determine the single copy genes. By reads simulation and mapping, the top 10 single copy genes with the lowest RMSE (the comparison between base pair wise read depths and simulated read depth) are selected as the reference genes.

  2. How to interpret the SD of reads depth?

    The SD of reads depth is the standard deviation of reads depth of a gene. If this value is large, then the reads depth will be unreliable. In our practical analysis, the SD of reads depth is usually less than 15% of the mean.

  3. "error while loading shared libraries: libncurses.so.5"

    sudo apt install libncurses5

  4. "blastn: error while loading shared libraries: libidn.so.11"

    sudo apt install libidn11-dev

  5. "UnsatisfiableError"

  UnsatisfiableError: The following specifications were found to be incompatible with each other:

Output in format: Requested package -> Available versionsThe following specifications were found to be incompatible with your system:

  - feature:/linux-64::__glibc==2.23=0
  - feature:|@/linux-64::__glibc==2.23=0

Your installed version is: 2.23"

Install htstream first.

Dependencies

ccne-fast & ccne-acc

  • HTStream
    Used for raw reads QC
    Petersen, Kristen R., David A. Streett, et al., 2015, Super deduper, fast PCR duplicate detection in fastq files. In Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics, pp. 491-492.
  • bwa
    Used for reads mapping
    Li H. and Durbin R., 2009, Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics, 25:1754-1760. [PMID: 19451168]
  • samtools
    Used for fetching mapped reads and sorting them by locus
    Li H., Handsaker B. et al., 2009, The Sequence alignment/map (SAM) format and SAMtools, Bioinformatics, 25(16):2078-9. [PMID:19505943]
  • bedtools
    Used for getting bed files
    Quinlan R A. and Hall M I., 2010, BEDTools: a flexible suite of utilities for comparing genomic features, Bioinformatics, 26(6):841-2. [PMID:20110278]
  • deepTools&
    Used for getting bed files
    Installation
    Ramírez, Fidel, Devon P. Ryan, et al., 2016, deepTools2: A next Generation Web Server for Deep-Sequencing Data Analysis, Nucleic Acids Research. [PMID:27079975]
    Requirements for deepTools:
    • Python 2.7 or Python 3.x
    • numpy >= 1.8.0
    • scipy >= 0.17.0
    • py2bit >= 0.1.0
    • pyBigWig >= 0.2.1
    • pysam >= 0.8
    • matplotlib >= 1.4.0
  • blast&
    Used for finding AMR gene on the genome
    Camacho C., Coulouris G., et al., 2008, BLAST+: architecture and applications, BMC Bioinformatics, 0:42. [PMID:20003500]
  • perl Math::CDF&
    Used for estimating AMR CN
    Math::CDF

& Only required for ccne-acc, the others are required for both ccne-fast and ccne-acc.

Test environment

Ubuntu 16.04 LTS with perl v5.26.2 (Theoretically compatible with other generic Linux version but not tested)

Bundled binaries

For Linux (compiled on Ubuntu 16.04 LTS) some of the binaries are included.

Licence

  • ccne is free software, released under the GPL V3

Author