All Projects → ctlab → metacherchant

ctlab / metacherchant

Licence: MIT license
No description or website provided.

Programming Languages

java
68154 projects - #9 most used programming language
shell
77523 projects

Projects that are alternatives of or similar to metacherchant

catch
A package for designing compact and comprehensive capture probe sets.
Stars: ✭ 55 (+189.47%)
Mutual labels:  metagenomics
metacal
Metagenomics calibration R package
Stars: ✭ 16 (-15.79%)
Mutual labels:  metagenomics
Jovian
Metagenomics/viromics pipeline that focuses on automation, user-friendliness and a clear audit trail. Jovian aims to empower classical biologists and wet-lab personnel to do metagenomics/viromics analyses themselves, without bioinformatics expertise.
Stars: ✭ 14 (-26.32%)
Mutual labels:  metagenomics
matam
Mapping-Assisted Targeted-Assembly for Metagenomics
Stars: ✭ 18 (-5.26%)
Mutual labels:  metagenomics
SemiBin
No description or website provided.
Stars: ✭ 25 (+31.58%)
Mutual labels:  metagenomics
Maaslin2
MaAsLin2: Microbiome Multivariate Association with Linear Models
Stars: ✭ 76 (+300%)
Mutual labels:  metagenomics
melonnpan
Model-based Genomically Informed High-dimensional Predictor of Microbial Community Metabolic Profiles
Stars: ✭ 20 (+5.26%)
Mutual labels:  metagenomics
charcoal
Remove contaminated contigs from genomes using k-mers and taxonomies.
Stars: ✭ 32 (+68.42%)
Mutual labels:  metagenomics
micca
micca - MICrobial Community Analysis
Stars: ✭ 19 (+0%)
Mutual labels:  metagenomics
traitar
From genomes to phenotypes: Traitar, the microbial trait analyzer
Stars: ✭ 41 (+115.79%)
Mutual labels:  metagenomics
GraphBin
GraphBin: Refined binning of metagenomic contigs using assembly graphs
Stars: ✭ 35 (+84.21%)
Mutual labels:  metagenomics
virnet
VirNet: A deep attention model for viral reads identification
Stars: ✭ 26 (+36.84%)
Mutual labels:  metagenomics
recentrifuge
Recentrifuge: robust comparative analysis and contamination removal for metagenomics
Stars: ✭ 79 (+315.79%)
Mutual labels:  metagenomics
DAtest
Compare different differential abundance and expression methods
Stars: ✭ 34 (+78.95%)
Mutual labels:  metagenomics
DRAM
Distilled and Refined Annotation of Metabolism: A tool for the annotation and curation of function for microbial and viral genomes
Stars: ✭ 159 (+736.84%)
Mutual labels:  metagenomics
Binning refiner
Improving genome bins through the combination of different binning programs
Stars: ✭ 26 (+36.84%)
Mutual labels:  metagenomics
functree-ng
An interactive radial tree for functional hierarchies and omics data visualization
Stars: ✭ 18 (-5.26%)
Mutual labels:  metagenomics
MetaCoAG
Binning Metagenomic Contigs via Composition, Coverage and Assembly Graphs
Stars: ✭ 29 (+52.63%)
Mutual labels:  metagenomics
bonsai
Bonsai: Fast, flexible taxonomic analysis and classification
Stars: ✭ 66 (+247.37%)
Mutual labels:  metagenomics
ORNA
Fast in-silico normalization algorithm for NGS data
Stars: ✭ 21 (+10.53%)
Mutual labels:  metagenomics

MetaCherchant is a tool for analysing genomic environment of a nucleotide sequence within a metagenome. The implementation is based on MetaFast source code.

Starting from version 0.1.0 it supports Hi-C reads input to facilitate genomic context extraction for extrachromosomal DNA. For detailed instructions, please refer to wiki page.

It also provides user with tools for comparing two metagenomes. For more details, please consult the reads classifier description.

Content

========

Installation

To run MetaCherchant you need to have JRE version 1.8 or higher installed and either of these three files: metacherchant.sh for Linux/MacOS, metacherchant.bat for Windows or metacherchant.jar for any OS.

Running MetaCherchant

To run MetaCherchant use the following syntax:

  • metacherchant.sh [<Launch options>]
  • metacherchant.bat [<Launch options>]
  • java -jar metacherchant.jar [<Launch options>]

Usage example

Single-metagenome mode

Here is a bash script showing a typical usage of MetaCherchant:

./metacherchant.sh --tool environment-finder \
	--k 31 \
	--coverage=5 \
	--reads $READS_DIR/*.fasta \
	--seq $GENE_FILE.fasta \
	--output $OUTPUT_DIR/output/ \
	--work-dir $OUTPUT_DIR/workDir \
	--maxkmers=100000 \
	--bothdirs=False \
	--chunklength=100
  • --k --- the size of k-mer used in de Bruijn graph.
  • --coverage the minimum coverage threshold for a k-mer to be included in the graph.
  • --reads list of all input files with metagenomic reads separated by space. FASTA and FASTQ formats are supported.
  • --seq a FASTA file with the target nucleotide sequences, for each of which a genomic environment will be built.
  • --output output folder.
  • --work-dir working directory with intermediate files and logs.
  • --maxkmers maximum allowed number of distinct k-mers present in the resulting genomic environment.
  • --bothdirs flag setting the BFS (breadth-first search) algorithm to make 1 bidirectional pass from the target sequence. If this flag is not set, BFS makes two one-directional passes.
  • --chunklength minimum length of a contracted graph node to be included in output FASTA file for further analysis.

After the end of analysis, found metagenomic environment can be visualised using de Bruijn graph, as on the figure below. For more information see output description section.

Single-metagenome environment

adeC gene in genome context of E.faecium. Target AR gene is shown in red.

Differential (multiple-metagenome) mode

In this mode, it is possible to join two or more graphs constructed as described above and join them into a single graph. The example command is:

./metacherchant.sh \
	--tool environment-finder-multi \
	--seq OXA-347.fasta \
	--work-dir "k31/TUE-S2_3_4/workDir" \
	--output "k31/TUE-S2_3_4" \
	--env "k31/TUE-S2_3/output/env.txt" "k31/TUE-S2_4/output/env.txt"
  • All parameters except the last one are described in the single-mode section.
  • --env ordered list of env.txt files (results of single mode analysis) to be joined into a single graph.

After the end of analysis, found metagenomic environment can be visualised using de Bruijn graph, as on the figure below. For more information see output description section.

Multiple-metagenome environment

Combined graph of AR gene context produced from two metagenomes of the same subject. Red color denotes the part of the graph present only at the time point 2, blue color — only at the point 3, black — at both points; green color denotes the graph nodes corresponding to the target AR gene

Output description

After the end of the analysis, the results can be found in the folder specified in --output parameter (if there were multiple sequences in file in --seq, there will be separate folder for each one).

  • graph.gfa - de Bruijn graph in GFA format. Is is recommended to be viewed using Bandage. Version 0.8.0 or later is recommended. Names(s) of the node(s) corresponding to the target sequence ends with a suffix _start (you can use 'Find Nodes' feature of Bandage to select them). For a single graph, there is no special coloring. For a graph constructed with a differential mode for exactly 2 metagenomes, green color corresponds to the starting sequence, red - nodes that are only present in the first graph, blue - only in the second graph, black nodes - in both. For 3 or more graphs, node color are greyscale, and darker shade of the node corresponds to more graphs in which that node is contained.

  • env.txt contains de Bruijn graph in a simple text format for later use: each line contains a k-mer and its coverage.

  • seqs.fasta - a FASTA file containing all sufficiently long unitigs (non-branching sequences in de Bruijn graph) for later analysis.

  • tsvs/* - graph descriptions in .tsv format for use in Cytoscape tool.

Citation

If you use MetaCherchant in your research, please cite the following publication:

Olekhnovich, E. I., Vasilyev, A. T., Ulyantsev, V. I., Kostryukova, E. S., & Tyakht, A. V. (2018). MetaCherchant: analyzing genomic context of antibiotic resistance genes in gut microbiota. Bioinformatics, 34(3), 434-444. https://doi.org/10.1093/bioinformatics/btx681

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].