User Manual
Generating inStrain input
There are two main inputs to inStrain: a fasta file containing reference genome sequences, and a bam file containing reads mapped to these sequences. Additionally and optionally, by providing a genes .fna file inStrain can calculate gene-level metrics, and by providing a scaffold-to-bin file inStrain can calculate metrics on a genome level. Here we go over some considerations involved in generating these inputs.
Preparing the .fasta file
A fasta file contains the DNA sequences of the contigs that you map your reads to. Choosing what fasta file you will use (consensus / reference genomes) is important and will affect the interpretation of your inStrain results. Below we describe the three most common strategies.
Please note that the fasta file provided to inStrain must always be the same as, or a subset of, the fasta file used to create the bam file (i.e. the fasta file that reads were mapped to).
Using de novo assembled genomes (recommended)
This strategy involves assembling genomes from the metagenomic samples that you’d like to profile. This is the recommended workflow for running inStrain:
Assemble reads into contigs for each sample collected from the environment. Recommended software: IDBA_UD, MEGAHIT, metaSPADES.
Bin genomes out of each assembly using differential coverage binning. Recommended software: Bowtie2 (for mapping), MetaBAT, CONCOCT, DasTOOL (for binning).
Dereplicate the entire set of genomes that you would like to profile (all genomes from all environments) at 97-99% identity, and filter out low quality genomes. Recommended software: dRep, checkM.
Create a scaffold-to-bin file from the genome set. Recommended software: parse_stb.py
Create a bowtie2 index of the representative genomes from this dereplicated set and map reads to this set from each sample. Recommended software: Bowtie2
Profile the resulting mapping .bam files using inStrain to calculate genome-level microdiveristy metrics for each originally binned genome.
An important aspect of this workflow is to map to many genomes at once. Mapping to just one genome at a time is highly discouraged, because this encourages mismapped reads from other genomes to be recruited by this genome. By including many (dereplicated) genomes in your bowtie2 index, you will be able to far more accurately filter out mismapped reads and reduce false positive SNPs. See Important concepts for more info.
For instructions on merging your genomes with a public database, see Tutorial #3 of Tutorial.
Using a single genome .fasta file
If your .fasta file is a single genome, the main consideration is that it should be a good representative genome for some organism in your sample. Ideally, it was assembled directly from that sample, isolated from that sample, or you have some other evidence that this genome is highly representative of a species in that sample. Regardless, you should check your inStrain plot output and scaffold_info.tsv output file to be sure that your inStrain run had decent coverage and breadth of coverage of the genome that you use before attempting to interpret the results.
Remember, your .fasta file can be a subset of the .fasta file that was used to create the .bam file. You can create a .bam with all dereplicated genomes from your environment, but then just pass a .fasta file for only the genomes of particular interest. This approach is recommended as opposed to creating a bam file for just each genome, as it reduces mismapped reads
Using a metagenomic assembly
You can also pass inStrain an entire metagenomic assembly from a sample, including both binned and unbinned contigs. In this case, the output inStrain profile will include population information for each contig in the set. To break it down by microbial genome / species, you can include a scaffold-to-bin file to generate results by genome.
Preparing the .bam file
InStrain is designed primarily for paired-end Illumina read sequencing, though un-paired reads can also be used by adjusting the run-time parameters. We recommend using the program Bowtie2 to map your reads to your genome.
Bowtie2 default parameters are what we use for mapping, but it may be worth playing around with them to see how different settings perform on your data. It is important to note that the -X flag (capital X) is the expected insert length and is by default 500. In many cases (e.g., 2x250 bp or simply datasets with longer inserts) it may be worthwhile to increase this value up to -X 1000 for passing to Bowtie2. By default, if a read maps equally well to multiple genomes, Bowtie2 will pick one of the positions randomly and give the read a MAPQ score of 1. Thus, if you’d like to remove multi-mapped reads, you can set the minimum mapQ score to 2.
Other mapping software can also be used to generate .bam files for inStrain. However, some software (e.g. BBmap and SNAP) use the fasta file scaffold descriptions when generating the .bam files, which causes problems for inStrain. If using mapping software that does this, include the flag --use_full_fasta_header to let inStrain account for this.
Note
If the reads that you’d like to run with inStrain are not working, please post an issue on GitHub. We’re happy to upgrade inStrain to work with new mapping software and/or reads from different technologies.
Preparing the genes file
You can run prodigal on your fasta file to generate an .fna file with the gene-level information. This .fna file can then be provided to inStrain profile to get gene-level characterizations.
Example:
$ prodigal -i assembly.fasta -d genes.fna -a genes.faa
Preparing a scaffold-to-bin file
After running inStrain profile, most results are presented on a scaffold-by-scaffold basis. There are a number of ways of telling inStrain which scaffold belongs to which genome, so that results can be analyzed on a genome-by-gene level as well.
Individual .fasta files. As recommended above, if you want to run inStrain on multiple genomes in the same sample, you should first concatenate all of the individual genomes into a single .fasta file and map to that. To view the results of the individual genomes used to create the concatenated .fasta file, you can pass a list of the individual .fasta files the
-sargument.Scaffold-to-bin file. This is a text file consists of two columns, with one column listing the scaffold name, and the second column listing the genome bin name. Columns should be separated by tabs. The script parse_stb.py can help you create a scaffold-to-bin file from a list of individual .fasta files, or to split a concatenated .fasta file into individual genomes. The script comes packaged with the program dRep, and can be installed with the command
pip install drep.Nothing. If all of your scaffolds belong to the same genome, by running
inStrain profilewithout any -s options it will summarize the results of all scaffolds together as if they all belong to the same genome.
Description of inStrain modules and arguments
The functionality of inStrain is broken up into modules. To see a list of available modules, check the help:
$ inStrain -h
...::: inStrain v1.3.2 :::...
Matt Olm and Alex Crits-Christoph. MIT License. Banfield Lab, UC Berkeley. 2019
Choose one of the operations below for more detailed help. See https://instrain.readthedocs.io for documentation.
Example: inStrain profile -h
Workflows:
profile -> Create an inStrain profile (microdiversity analysis) from a mapping.
compare -> Compare multiple inStrain profiles (popANI, coverage_overlap, etc.)
Single operations:
profile_genes -> Calculate gene-level metrics on an inStrain profile [DEPRECATED; USE profile INSTEAD]
genome_wide -> Calculate genome-level metrics on an inStrain profile
quick_profile -> Quickly calculate coverage and breadth of a mapping using coverM
filter_reads -> Commands related to filtering reads from .bam files
plot -> Make figures from the results of "profile" or "compare"
other -> Other miscellaneous operations
profile
Module description
The heart of inStrain. The input is a fasta file and a bam file, and the output is an IS_profile. The functionality of inStrain profile is broken into several steps.
First, all reads in the .bam file are filtered to only keep those that map with sufficient quality. All non-paired reads will be filtered out by default, and an additional set of filters are applied to each read pair (not the individual reads). Command line parameters can be adjusted to change the specifics, but in general:
Pairs must be mapped in the proper orientation with an expected insert size. The minimum insert distance can be set with a command line parameter. The maximum insert distance is a multiple of the median insert distance. So if pairs have a median insert size of 500bp, by default all pairs with insert sizes over 1500bp will be excluded. For the max insert cutoff, the median_insert for all scaffolds is used.
Pairs must have a minimum mapQ score. MapQ scores are confusing and how they’re calculated varies based on the mapping algorithm being used, but are meant to represent both the number of mismatches in the mapping and how unique that mapping is. With bowtie2, if the read maps equally well to two positions on the genome (multi-mapped read), its mapQ score will be set to 2. The read in the pair with the higher mapQ is used for the pair.
Pairs must be above some minimum nucleotide identity (ANI) value. For example if reads in a pair are 100bp each, and each read has a single mismatch, the ANI of that pair would be 0.99
Next, using only read pairs that pass filters, a number of microdiversity metrics are calculated on a scaffold-by-scaffold basis. This includes:
Calculate the coverage at each position along the scaffold
Calculate the nucleotide diversity at each position along the scaffold in which the coverage is greater than the min_cov argument.
Identify SNSs and SNVs. The criteria for being reported as a divergent site are 1) More than min_cov number of bases at that position, 2) More than min_freq percentage of reads that are a variant base, 3) The number of reads with the variant base is more than the null model for that coverage.
Calculate linkage between divergent sites on the same read pair. For each pair harboring a divergent site, calculate the linkage of that site with other divergent sites within that same pair. This is only done for pairs of divergent sites that are both on at least MIN_SNP reads
Calculate scaffold-level properties. These include things like the overall coverage, breadth of coverage, average nucleotide identity (ANI) between the reads and the reference genome, and the expected breadth of coverage based on that true coverage.
Finally, this information is stored as an IS_profile object. This includes the locations of divergent sites, the number of read pairs that passed filters (and other information) for each scaffold, the linkage between SNV pairs, ect.
Module parameters
To see the command-line arguments for inStrain profile, check the help:
$ inStrain profile -h
usage: inStrain profile [-o OUTPUT] [--use_full_fasta_header] [-p PROCESSES]
[-d] [-h] [--version] [-l MIN_READ_ANI]
[--min_mapq MIN_MAPQ]
[--max_insert_relative MAX_INSERT_RELATIVE]
[--min_insert MIN_INSERT]
[--pairing_filter {paired_only,all_reads,non_discordant}]
[--priority_reads PRIORITY_READS]
[--detailed_mapping_info] [-c MIN_COV] [-f MIN_FREQ]
[-fdr FDR] [-g GENE_FILE] [-s [STB [STB ...]]]
[--mm_level] [--skip_mm_profiling] [--database_mode]
[--min_scaffold_reads MIN_SCAFFOLD_READS]
[--min_genome_coverage MIN_GENOME_COVERAGE]
[--min_snp MIN_SNP] [--store_everything]
[--scaffolds_to_profile SCAFFOLDS_TO_PROFILE]
[--rarefied_coverage RAREFIED_COVERAGE]
[--window_length WINDOW_LENGTH] [--skip_genome_wide]
[--skip_plot_generation]
bam fasta
REQUIRED:
bam Sorted .bam file
fasta Fasta file the bam is mapped to
I/O PARAMETERS:
-o OUTPUT, --output OUTPUT
Output prefix (default: inStrain)
--use_full_fasta_header
Instead of using the fasta ID (space in header before
space), use the full header. Needed for some mapping
tools (including bbMap) (default: False)
SYSTEM PARAMETERS:
-p PROCESSES, --processes PROCESSES
Number of processes to use (default: 6)
-d, --debug Make extra debugging output (default: False)
-h, --help show this help message and exit
--version show program's version number and exit
READ FILTERING OPTIONS:
-l MIN_READ_ANI, --min_read_ani MIN_READ_ANI
Minimum percent identity of read pairs to consensus to
use the reads. Must be >, not >= (default: 0.95)
--min_mapq MIN_MAPQ Minimum mapq score of EITHER read in a pair to use
that pair. Must be >, not >= (default: -1)
--max_insert_relative MAX_INSERT_RELATIVE
Multiplier to determine maximum insert size between
two reads - default is to use 3x median insert size.
Must be >, not >= (default: 3)
--min_insert MIN_INSERT
Minimum insert size between two reads - default is 50
bp. If two reads are 50bp each and overlap completely,
their insert will be 50. Must be >, not >= (default:
50)
--pairing_filter {paired_only,all_reads,non_discordant}
How should paired reads be handled?
paired_only = Only paired reads are retained
non_discordant = Keep all paired reads and singleton reads that map to a single scaffold
all_reads = Keep all reads regardless of pairing status (NOT RECOMMENDED; See documentation for deatils)
(default: paired_only)
--priority_reads PRIORITY_READS
The location of a list of reads that should be
retained regardless of pairing status (for example
long reads or merged reads). This can be a .fastq file
or text file with list of read names (will assume file
is compressed if ends in .gz (default: None)
READ OUTPUT OPTIONS:
--detailed_mapping_info
Make a detailed read report indicating deatils about
each individual mapped read (default: False)
VARIANT CALLING OPTIONS:
-c MIN_COV, --min_cov MIN_COV
Minimum coverage to call an variant (default: 5)
-f MIN_FREQ, --min_freq MIN_FREQ
Minimum SNP frequency to confirm a SNV (both this AND
the FDR snp count cutoff must be true to call a SNP).
(default: 0.05)
-fdr FDR, --fdr FDR SNP false discovery rate- based on simulation data
with a 0.1 percent error rate (Q30) (default: 1e-06)
GENE PROFILING OPTIONS:
-g GENE_FILE, --gene_file GENE_FILE
Path to prodigal .fna genes file. If file ends in .gb
or .gbk, will treat as a genbank file (EXPERIMENTAL;
the name of the gene must be in the gene qualifier)
(default: None)
GENOME WIDE OPTIONS:
-s [STB [STB ...]], --stb [STB [STB ...]]
Scaffold to bin. This can be a file with each line
listing a scaffold and a bin name, tab-seperated. This
can also be a space-seperated list of .fasta files,
with one genome per .fasta file. If nothing is
provided, all scaffolds will be treated as belonging
to the same genome (default: [])
READ ANI OPTIONS:
--mm_level Create output files on the mm level (see documentation
for info) (default: False)
--skip_mm_profiling Dont perform analysis on an mm level; saves RAM and
time; impacts plots and raw_data (default: False)
PROFILE OPTIONS:
--database_mode Set a number of parameters to values appropriate for
mapping to a large fasta file. Will set:
--min_read_ani 0.92 --skip_mm_profiling
--min_genome_coverage 1 (default: False)
--min_scaffold_reads MIN_SCAFFOLD_READS
Minimum number of reads mapping to a scaffold to
proceed with profiling it (default: 1)
--min_genome_coverage MIN_GENOME_COVERAGE
Minimum number of reads mapping to a genome to proceed
with profiling it. MUST profile .stb if this is set
(default: 0)
--min_snp MIN_SNP Absolute minimum number of reads connecting two SNPs
to calculate LD between them. (default: 20)
--store_everything Store intermediate dictionaries in the pickle file;
will result in significantly more RAM and disk usage
(default: False)
--scaffolds_to_profile SCAFFOLDS_TO_PROFILE
Path to a file containing a list of scaffolds to
profile- if provided will ONLY profile those scaffolds
(default: None)
--rarefied_coverage RAREFIED_COVERAGE
When calculating nucleotide diversity, also calculate
a rarefied version with this much coverage (default:
50)
--window_length WINDOW_LENGTH
Break scaffolds into windows of this length when
profiling (default: 10000)
OTHER OPTIONS:
--skip_genome_wide Do not generate tables that consider groups of
scaffolds belonging to genomes (default: False)
--skip_plot_generation
Do not make plots (default: False)
compare
Module description
Compare provides the ability to compare multiple inStrain profiles (created by running inStrain profile).
Note
inStrain can only compare inStrain profiles that have been mapped to the same .fasta file
inStrain compare does pairwise comparisons between each input inStrain profile. For each pair, a series of steps are undertaken.
All positions in which both IS_profile objects have at least min_cov coverage (5x by default) are identified. This information can be stored in the output by using the flag –store_coverage_overlap, but due to it’s size, it’s not stored by default
Each position identified in step 1 is compared to calculate both conANI and popANI. The way that it compares positions is by testing whether the consensus base in sample 1 is detected at all in sample 2 and vice-versa. Detection of an allele in a sample is based on that allele being above the set -min_freq and -fdr. All detected differences between each pair of samples can be reported if the flag –store_mismatch_locations is set.
The coverage overlap and the average nucleotide identity for each scaffold is reported. For details on how this is done, see Expected output
New in v1.6 Tables that list the coverage and base-frequencies of each SNV in all samples can be generated using the –bams parameter within inStrain compare. For each inStrain profile provided with the -i parameter, the corresponding bam file must be provided with the –bams parameter. The same read filtering parameters used in the original profile command will be used when running this analysis. See section SNV POOLING OPTIONS: in the help below for full information about this option, and see Expected output for the tables it creates.
Module parameters
To see the command-line options, check the help:
$ inStrain compare -h
usage: inStrain compare -i [INPUT [INPUT ...]] [-o OUTPUT] [-p PROCESSES] [-d]
[-h] [--version] [-s [STB [STB ...]]] [-c MIN_COV]
[-f MIN_FREQ] [-fdr FDR] [--database_mode]
[--breadth BREADTH] [-sc SCAFFOLDS] [--genome GENOME]
[--store_coverage_overlap]
[--store_mismatch_locations]
[--include_self_comparisons] [--skip_plot_generation]
[--group_length GROUP_LENGTH] [--force_compress]
[-ani ANI_THRESHOLD] [-cov COVERAGE_TRESHOLD]
[--clusterAlg {centroid,weighted,ward,single,complete,average,median}]
[-bams [BAMS [BAMS ...]]] [--skip_popANI]
REQUIRED:
-i [INPUT [INPUT ...]], --input [INPUT [INPUT ...]]
A list of inStrain objects, all mapped to the same
.fasta file (default: None)
-o OUTPUT, --output OUTPUT
Output prefix (default: instrainComparer)
SYSTEM PARAMETERS:
-p PROCESSES, --processes PROCESSES
Number of processes to use (default: 6)
-d, --debug Make extra debugging output (default: False)
-h, --help show this help message and exit
--version show program's version number and exit
GENOME WIDE OPTIONS:
-s [STB [STB ...]], --stb [STB [STB ...]]
Scaffold to bin. This can be a file with each line
listing a scaffold and a bin name, tab-seperated. This
can also be a space-seperated list of .fasta files,
with one genome per .fasta file. If nothing is
provided, all scaffolds will be treated as belonging
to the same genome (default: [])
VARIANT CALLING OPTIONS:
-c MIN_COV, --min_cov MIN_COV
Minimum coverage to call an variant (default: 5)
-f MIN_FREQ, --min_freq MIN_FREQ
Minimum SNP frequency to confirm a SNV (both this AND
the FDR snp count cutoff must be true to call a SNP).
(default: 0.05)
-fdr FDR, --fdr FDR SNP false discovery rate- based on simulation data
with a 0.1 percent error rate (Q30) (default: 1e-06)
DATABASE MODE PARAMETERS:
--database_mode Using the parameters below, automatically determine
which genomes are present in each Profile and only
compare scaffolds from those genomes. All profiles
must have run Profile with the same .stb (default:
False)
--breadth BREADTH Minimum breadth_minCov required to count a genome
present (default: 0.5)
OTHER OPTIONS:
-sc SCAFFOLDS, --scaffolds SCAFFOLDS
Location to a list of scaffolds to compare. You can
also make this a .fasta file and it will load the
scaffold names (default: None)
--genome GENOME Run scaffolds belonging to this single genome only.
Must provide an .stb file (default: None)
--store_coverage_overlap
Also store coverage overlap on an mm level (default:
False)
--store_mismatch_locations
Store the locations of SNPs (default: False)
--include_self_comparisons
Also compare IS profiles against themself (default:
False)
--skip_plot_generation
Dont create plots at the end of the run. (default:
False)
--group_length GROUP_LENGTH
How many bp to compare simultaneously (higher will use
more RAM and run more quickly) (default: 10000000)
--force_compress Force compression of all output files (default: False)
GENOME CLUSTERING OPTIONS:
-ani ANI_THRESHOLD, --ani_threshold ANI_THRESHOLD
popANI threshold to cluster genomes at. Must provide
.stb file to do so (default: 0.99999)
-cov COVERAGE_TRESHOLD, --coverage_treshold COVERAGE_TRESHOLD
Minimum percent_genome_compared for a genome
comparison to count; if below the popANI will be set
to 0. (default: 0.1)
--clusterAlg {centroid,weighted,ward,single,complete,average,median}
Algorithm used to cluster genomes (passed to
scipy.cluster.hierarchy.linkage) (default: average)
SNV POOLING OPTIONS:
-bams [BAMS [BAMS ...]], --bams [BAMS [BAMS ...]]
Location of .bam files used during inStrain profile
commands; needed to pull low-frequency SNVs. MUST BE
IN SAME ORDER AS THE INPUT FILES (default: None)
--skip_popANI Only run SNV Pooling; skip other compare operations
(default: False)
Other modules
The other modules are not commonly used, and mainly provide auxiliary functions or allow you to run certain steps of profile after the fact. It is recommended to provide a genes file and/or a scaffold-to-bin file during inStrain profile rather than using profile_genes or genome_wide, as it is more computationally efficient to do things that way.
parse_annotations
This is a new module (released in inStrain version 1.7) that provides a straightforward way to annotate genes for functional analysis with inStrain. It’s inputs are 1 or more inStrain profile objects (a set of genes must of been provided when running profile) and a gene annotation table. The format of the gene annotation MUST be a .csv file that looks like the following:
gene |
anno |
AF21-42.Scaf7_79 |
K14374 |
AF21-42.Scaf7_79 |
K12633 |
AF21-42.Scaf7_79 |
K16034 |
AF21-42.Scaf7_79 |
K12705 |
AF21-42.Scaf7_79 |
K15467 |
AF21-42.Scaf7_79 |
K20592 |
AF21-42.Scaf7_79 |
K15958 |
AF21-42.Scaf7_79 |
K22590 |
AF21-42.Scaf7_80 |
K02835 |
AF21-42.Scaf7_81 |
K03431 |
The top line MUST read gene,anno exactly, and all other lines must have the format gene, comma (,), annotation. The gene column must match the names of the genes provided to inStrain profile, and the second column can be whatever you want it to be. It is fine if a gene as multiple annotations, just make that gene have multiple lines in this file.
For tips on running the annotations themselves, see the section Gene Annotation below. Also see the section Running inStrain parse_annotations in Tutorial for more info.
To see the command-line options, check the help:
$ inStrain parse_annotations -h
usage: inStrain parse_annotations -i [INPUT [INPUT ...]] -a [ANNOTATIONS [ANNOTATIONS ...]] [-o OUTPUT] [-p PROCESSES] [-d] [-h] [--version] [-b MIN_GENOME_BREADTH]
[-g MIN_GENE_BREADTH] [--store_rawdata]
REQUIRED:
-i [INPUT [INPUT ...]], --input [INPUT [INPUT ...]]
A list of inStrain objects, all mapped to the same .fasta file (default: None)
-a [ANNOTATIONS [ANNOTATIONS ...]], --annotations [ANNOTATIONS [ANNOTATIONS ...]]
A table or set of tables with gene annotations.
Must be in specific format; see inStrain website for details (default: None)
-o OUTPUT, --output OUTPUT
Output prefix (default: annotation_output)
SYSTEM PARAMETERS:
-p PROCESSES, --processes PROCESSES
Number of processes to use (default: 6)
-d, --debug Make extra debugging output (default: False)
-h, --help show this help message and exit
--version show program's version number and exit
OTHER OPTIONS:
-b MIN_GENOME_BREADTH, --min_genome_breadth MIN_GENOME_BREADTH
Only annotate genomes on genomes with at least this genome breadth. Requires having genomes called. Set to 0 to include all genes. (default: 0.5)
-g MIN_GENE_BREADTH, --min_gene_breadth MIN_GENE_BREADTH
Only annotate genes with at least this breadth. Set to 0 to include all genes. (default: 0.8)
--store_rawdata Store the raw data dictionary (default: False)
quick_profile
This is a quirky module that is not really related to any of the others. It is used to quickly profile a bam file to pull out scaffolds from genomes that are at a sufficient breadth. To use it you must provide a .bam file, the .fasta file that you mapped to to generate the .bam file, and a scaffold to bin file (see above section for details). On the backend this module is really just calling the program coverM
To see the command-line options, check the help:
$ inStrain quick_profile -h
usage: inStrain quick_profile [-p PROCESSES] [-d] [-h] [--version]
[-s [STB [STB ...]]] [-o OUTPUT]
[--breadth_cutoff BREADTH_CUTOFF]
[--stringent_breadth_cutoff STRINGENT_BREADTH_CUTOFF]
bam fasta
REQUIRED:
bam Sorted .bam file
fasta Fasta file the bam is mapped to
SYSTEM PARAMETERS:
-p PROCESSES, --processes PROCESSES
Number of processes to use (default: 6)
-d, --debug Make extra debugging output (default: False)
-h, --help show this help message and exit
--version show program's version number and exit
OTHER OPTIONS:
-s [STB [STB ...]], --stb [STB [STB ...]]
Scaffold to bin. This can be a file with each line
listing a scaffold and a bin name, tab-seperated. This
can also be a space-seperated list of .fasta files,
with one genome per .fasta file. If nothing is
provided, all scaffolds will be treated as belonging
to the same genome (default: [])
-o OUTPUT, --output OUTPUT
Output prefix (default: QuickProfile)
--breadth_cutoff BREADTH_CUTOFF
Minimum genome breadth to pull scaffolds (default:
0.5)
--stringent_breadth_cutoff STRINGENT_BREADTH_CUTOFF
Minimum breadth to let scaffold into coverm raw
results (done with greater than; NOT greater than or
equal to) (default: 0.0)
plot
This module produces plots based on the results of inStrain profile and inStrain compare. In both cases, before plots can be made, inStrain genome_wide must be run on the output folder first. In order to make plots 8 and 9, inStrain profile_genes must be run first as well.
The recommended way of running this module is with the default -pl a. It will just try and make all of the plots that it can, and will tell you about any plots that it fails to make.
See Expected output for an example of the plots it can make.
To see the command-line options, check the help:
$ inStrain plot -h
usage: inStrain plot -i IS [-pl [PLOTS [PLOTS ...]]] [-p PROCESSES] [-d] [-h]
REQUIRED:
-i IS, --IS IS an inStrain profile object (default: None)
-pl [PLOTS [PLOTS ...]], --plots [PLOTS [PLOTS ...]]
Plots. Input 'all' or 'a' to plot all
1) Coverage and breadth vs. read mismatches
2) Genome-wide microdiversity metrics
3) Read-level ANI distribution
4) Major allele frequencies
5) Linkage decay
6) Read filtering plots
7) Scaffold inspection plot (large)
8) Linkage with SNP type (GENES REQUIRED)
9) Gene histograms (GENES REQUIRED)
10) Compare dendrograms (RUN ON COMPARE; NOT PROFILE)
(default: a)
SYSTEM PARAMETERS:
-p PROCESSES, --processes PROCESSES
Number of processes to use (default: 6)
-d, --debug Make extra debugging output (default: False)
-h, --help show this help message and exit
other
This module holds odds and ends functionalities. As of version 1.4, all it can do is convert old IS_profile objects (>v0.3.0) to newer versions (v0.8.0) and create runtime summaries of complete inStrain runs. As the code base around inStrain matures, we expect more functionalities to be included here.
To see the command-line options, check the help:
$ inStrain other -h
usage: inStrain other [-p PROCESSES] [-d] [-h] [--version] [--old_IS OLD_IS]
[--run_statistics RUN_STATISTICS]
SYSTEM PARAMETERS:
-p PROCESSES, --processes PROCESSES
Number of processes to use (default: 6)
-d, --debug Make extra debugging output (default: False)
-h, --help show this help message and exit
--version show program's version number and exit
OTHER OPTIONS:
--old_IS OLD_IS Convert an old inStrain version object to the newer
version. (default: None)
--run_statistics RUN_STATISTICS
Generate runtime reports for an inStrain run.
(default: None)