Growth Rate Index (GRiD) measures bacterial growth rate from reference genomes (including draft quality genomes) and metagenomic bins at ultra-low sequencing coverage (> 0.2x).
GRiD algorithm consists of two modules;
- < single > - which is applicable for growth analysis involving a single reference genome
- < multiplex > - for the high-throughput growth analysis of all identified bacteria in a sample. Prior knowledge of microbial composition is not required. To use this module, download the GRiD database, consisting of 32,819 representative bacteria genomes, from ftp://ftp.jax.org/ohlab/Index/
The easiest way to install GRiD is through miniconda which resolves all required dependencies.
- If you do not have anaconda or miniconda already installed, download miniconda https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh and run the install script. Reload .bashrc environment
source ~/.bashrc
-- Set up channels --
conda config --add channels r
conda config --add channels defaults
conda config --add channels conda-forge
conda config --add channels bioconda
- Install GRiD
conda install grid=1.0.6
NOTE: Ensure you include the GRiD version as above (grid=1.0.6) during conda installation
It is highly recommended to run the example test to ensure proper installation before running GRiD on your dataset. You do not need to have downloaded the GRiD database to run the test (see "Example test" below).
grid -h Display this help message
grid single <options> GRiD using a single genome
grid multiplex <options> GRiD high throughput
grid single <options>
<options>
-r Reads directory (single end reads)
-o Output directory
-g Reference genome (fasta)
-l Path to file listing a subset of reads
for analysis [default = analyze all samples in reads directory]
-n INT Number of threads for bowtie mapping (default 1)
-h Display this message
grid multiplex <options>
<options>
-r Reads directory (single end reads)
-o Output directory
-d GRiD database directory
-c FLOAT Coverage cutoff (>= 0.2) [default 1]
-p Enable reassignment of ambiguous reads using Pathoscope2
-t INT Theta prior for reads reassignment [default 0]. Requires the -p flag
-l Path to file listing a subset of reads
for analysis [default = analyze all samples in reads directory]
-m merge output tables into a single matrix file
-n INT Number of threads for bowtie mapping (default 1)
-h Display this message
NOTE: Sample reads must be in single-end format. If reads are only available in paired-end format, use either of the mate pairs, or concatenate both pairs into a single fastq file. In addition, reads must have the .fastq extension (and not .fq). Using either modules, the default is to analyze all samples present in the reads directory. However, analysis can be restricted to a subset of samples by using the -l flag and specifying a file that lists the subset of samples.
For the 'multiplex' module, reads mapping to multiple genomes are reassigned using Pathoscope 2 when the -p flag is set. The degree to which reads are reassigned is set by the -t (theta prior) flag. The theta prior value represents the number of non-unique reads that are not subject to reassignment. Finally, when the coverage cutoff (-c flag) is set below 1, only genomes with fragmentation levels below 90 fragments/Mbp are analyzed (see xxx et al. for more details). Note that to use the 'multiplex' module, you must have downloaded the GRiD database from ftp://ftp.jax.org/ohlab/Index/. However, you do not need the database to run the example test.
single module - two output files are generated
- A plot (.pdf) showing coverage information across the genome
- A table of results (.txt) displaying growth rate (GRiD), 95% confidence interval, unrefined GRiD value, species heterogeneity, genome coverage, dnaA/ori ratio, and ter/dif ratio. Species heterogeneity is a metric estimating the degree to which closely related strains/species contribute to variance in growth predictions (range between 0 - 1 where 0 indicate no heterogeneity). In most bacteria genomes, dnaA is located in close proximity to the ori whereas replication typically terminates at/near dif sequence. Thus, the closer dnaA/ori and ter/dif ratios are to one, the more likely the accuracy of GRiD scores.
multiplex module - two output files are generated per sample
- A heatmap (.pdf), displaying growth rate (GRiD) from genomes above the coverage cutoff with hierachical clustering.
- A table of results (.txt) displaying growth rate (GRiD) of genomes above the coverage cutoff, unrefined GRiD value, species heterogeneity, and genome coverage. If -m flag is set, all tables will be merged into a single matrix file called "merged_table.txt".
The test sample contain reads from Staphylococcus epidermids, Lactobacillus gasseri, and Campylobacter upsaliensis, each with coverage of ~ 0.5. Download the GRiD folder and run the test as shown below.
NOTE: Ensure GRiD-1.0.6 was installed via conda. Please see installation instructions
wget https://github.com/ohlab/GRiD/archive/1.0.6.tar.gz
tar xvf 1.0.6.tar.gz
cd GRiD-1.0.6/test
chmod +x ../grid
../grid single -r . -g S_epidermidis.LRKNS118.fna
../grid multiplex -r . -d . -p -c 0.2
For each module, output files (a pdf and a text file) are generated in the test folder.
The database can be updated with metagenomic bins or newly sequenced bacterial genomes by running the update_database script (requires bowtie2).
update_database <options>
<options>
-d GRiD database directory
-g Bacterial genomes directory
-n Name for new database
-l Path to file listing specific genomes
for inclusion in database [default = include all genomes in directory]
-h Display this message
NOTE: bacteria genomes must be in fasta format and must have either .fasta, .fa or .fna extensions.
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R (tested using v 3.2.3)
- Required R libraries - dplyr, getopt, ggplot2, gsubfn, gplots
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bowtie2 (tested using v 2.3.1)
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seqtk (tested using v 1.0-r31)
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samtools (tested using v 1.5)
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bedtools (tested using v 2.26.0)
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bamtools (tested using v 1.0.2)
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blast (tested using v 2.6.0)
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Pathoscope2