Example output and explanations

InStrain produces a variety of output in the IS folder depending on which operations are run. Generally, output that is meant for human eyes to be easily interpretable is located in the output folder.

inStrain profile

A typical run of inStrain will yield the following files in the output folder:

scaffold_info.tsv

This gives basic information about the scaffolds in your sample at the highest allowed level of read identity.

scaffold_info.tsv
scaffold length breadth coverage median_cov std_cov bases_w_0_coverage mean_clonality median_clonality mean_microdiversity median_microdiversity unmaskedBreadth expected_breadth SNPs Referece_SNPs BiAllelic_SNPs MultiAllelic_SNPs consensus_SNPs population_SNPs conANI popANI
S3_003_000X1_scaffold_21039 1049 0.9609151572926596 7.778836987607247 9 3.6242339424115295 41 0.9984115827692688 1.0 0.0015884172307313313 0.0 0.7836034318398475 0.9989601856174312 1 0 1 0 0 0 1.0 1.0
S3_003_000X1_scaffold_21063 1048 0.3721374045801527 0.6698473282442748 0 0.978669048484894 658         0.0 0.4464898509344126 0 0 0 0 0 0 0.0 0.0
S3_003_000X1_scaffold_21081 1047 0.2082139446036294 0.2082139446036294 0 0.4060306612513717 829         0.0 0.1679418203027453 0 0 0 0 0 0 0.0 0.0
S3_003_000X1_scaffold_21188 1043 0.3547459252157239 0.4688398849472674 0 0.6908089219842111 673         0.0 0.338989542420026 0 0 0 0 0 0 0.0 0.0
S3_003_000X1_scaffold_21225 1042 0.7821497120921305 4.341650671785029 5 3.4491608427332947 227 1.0 1.0 0.0 0.0 0.5374280230326296 0.9783700757950428 0 0 0 0 0 0 1.0 1.0
scaffold
The name of the scaffold in the input .fasta file
length
Full length of the scaffold in the input .fasta file
breadth
The percentage of bases in the scaffold that are covered by at least a single read. A breadth of 1 means that all bases in the scaffold have at least one read covering them
coverage
The average depth of coverage on the scaffold. If half the bases in a scaffold have 5 reads on them, and the other half have 10 reads, the coverage of the scaffold will be 7.5
median_cov
The median coverage value of all bases in the scaffold, included bases with 0 coverage
std_cov
The standard deviation of all coverage values
bases_w_0_coverage
The number of bases with 0 coverage
mean_clonality
The mean clonality value of all bases in the scaffold that have a clonality value calculated. So if only 1 base on the scaffold meats the minimum coverage to calculate clonality, the mean_clonality of the scaffold will be the clonality of that base
median_clonality
The median clonality value of all bases in the scaffold that have a clonality value calculated
mean_microdiversity
The mean mean_microdiversity value of all bases in the scaffold that have a mean_microdiversity value calculated (microdiveristy = 1 - clonality)
median_microdiversity
The median microdiversity value of all bases in the scaffold that have a microdiversity value calculated
unmaskedBreadth
The percentage of bases in the scaffold that have at least the min_cov number of bases. This value multiplied by the length of the scaffold gives the percentage of bases for which clonality is calculated and on which SNPs can be called
SNPs
The total number of SNPs called on this scaffold
expected_breadth
This tells you the breadth that you should expect if reads are evenly distributed along the genome, given the reported coverage value. Based on the function breadth = -1.000 * e^(0.883 * coverage) + 1.000. This is useful to establish whether or not the scaffold is actually in the reads, or just a fraction of the scaffold. If your coverage is 10x, the expected breadth will be ~1. If your actual breadth is significantly lower then the expected breadth, this means that reads are mapping only to a specific region of your scaffold (transposon, etc.)
SNPs
The total number of SNPs called on this scaffold
Referece_SNPs
The number of SNPs called on this scaffold with allele_count = 1. This means that the only allele detected in the reads is different from the reference base
BiAllelic_SNPs
The number of SNPs called on this scaffold with allele_count = 2. This means that there are two possible alleles at this position
MultiAllelic_SNPs
The number of SNPs called on this scaffold with allele_count > 2. This means that there are more than two possible alleles at this position
consensus_SNPs
The number of SNPs called on this scaffold with allele_count > 0 and where consensus base is not the reference base. This should be the same as Reference_SNPs under almost all circumstances
population_SNPs
These are SNPs where the reference base isn’t detected at all, regardless of the allele count.
conANI
The average nucleotide identity between the reads in the sample and the .fasta file based on consensus SNPs. Calculated using the formula ANI = (unmaskedBreadth * length) - consensus_SNPs)/ (unmaskedBreadth * length))
popANI
The average nucleotide identity between the reads in the sample and the .fasta file based on consensus SNPs. Calculated using the formula ANI = (unmaskedBreadth * length) - population_SNPs)/ (unmaskedBreadth * length))

read_report.tsv

This provides an overview of the number of reads that map to each scaffold, and some basic metrics about their quality.

read_report.tsv
scaffold unfiltered_reads unfiltered_pairs pass_filter_cutoff pass_max_insert pass_min_insert pass_min_mapq filtered_pairs mean_mistmaches mean_insert_distance mean_mapq_score mean_pair_length median_insert mean_PID
all_scaffolds 3802370 1790817 1674511 1784011 1790699 1790817 1668496 2.7480758782164787 293.0713925543481 23.46918082640493 298.38404705785126 246.0 0.9906729188638016
S3_002_000X1_scaffold_1162 12 6 6 6 6 6 6 1.0 281.1666666666667 25.16666666666667 300.0 287.0 0.9966666666666668
S3_002_000X1_scaffold_1005 10 5 5 5 5 5 5 0.2 318.0 33.2 299.8 208.0 0.9993333333333332
S3_002_000X1_scaffold_1151 6 3 3 3 3 3 3 5.666666666666668 280.3333333333333 19.666666666666668 300.0 293.0 0.9811111111111112
S3_002_000X1_scaffold_1004 14 6 6 6 6 6 6 0.5 295.5 16.666666666666668 300.0 248.0 0.9983333333333334

The following metrics are provided for all individual scaffolds, and for all scaffolds together (scaffold “all_scaffolds”). For the max insert cutoff, the median_insert for all_scaffolds is used

header line
The header line (starting with #; not shown in the above table) describes the parameters that were used to filter the reads
scaffold
The name of the scaffold in the input .fasta file
unfiltered_reads
The raw number of reads that map to this scaffold
unfiltered_pairs
The raw number of pairs of reads that map to this scaffold. Only paired reads are used by inStrain
pass_filter_cutoff
The number of pairs of reads mapping to this scaffold that pass the ANI filter cutoff (specified in the header as “filter_cutoff”)
pass_max_insert
The number of pairs of reads mapping to this scaffold that pass the maximum insert size cutoff- that is, their insert size is less than 3x the median insert size of all_scaffolds. Note that the insert size is measured from the start of the first read to the end of the second read (2 perfectly overlapping 50bp reads will have an insert size of 50bp)
pass_min_insert
The number of pairs of reads mapping to this scaffold that pass the minimum insert size cutoff
pass_min_mapq
The number of pairs of reads mapping to this scaffold that pass the minimum mapQ score cutoff
filtered_pairs
The number of pairs of reads that pass all cutoffs
mean_mistmaches
Among all pairs of reads mapping to this scaffold, the mean number of mismatches
mean_insert_distance
Among all pairs of reads mapping to this scaffold, the mean insert distance. Note that the insert size is measured from the start of the first read to the end of the second read (2 perfectly overlapping 50bp reads will have an insert size of 50bp)
mean_mapq_score
Among all pairs of reads mapping to this scaffold, the average mapQ score
mean_pair_length
Among all pairs of reads mapping to this scaffold, the average length of both reads in the pair summed together
median_insert
Among all pairs of reads mapping to this scaffold, the median insert distance.
mean_PID
Among all pairs of reads mapping to this scaffold, the average percentage ID of both reads in the pair to the reference .fasta file

SNVs.tsv

This describes the SNPs that are detected in this mapping.

SNVs.tsv
scaffold position refBase A C T G conBase varBase allele_count cryptic baseCoverage varFreq refFreq
S3_003_000X1_scaffold_21039 833 C 2 7 0 0 C A 2 False 9 0.2222222222222222 0.7777777777777778
S3_003_000X1_scaffold_20 99 C 0 0 5 0 T A 1 False 5 0.0 1.0
S3_003_000X1_scaffold_20 123 A 0 0 0 11 G A 1 False 11 0.0 1.0
S3_003_000X1_scaffold_20 261 T 19 0 0 0 A A 1 False 19 1.0 1.0
S3_003_000X1_scaffold_20 291 C 0 16 2 0 C T 2 False 18 0.1111111111111111 0.8888888888888888

See the module_descriptions for what constitutes a SNP (what makes it into this table)

scaffold
The scaffold that the SNP is on
position
The genomic position of the SNP
refBase
The reference base in the .fasta file at that position
A, C, T, and G
The number of mapped reads encoding each of the bases
conBase
The consensus base; the base that is supported by the most reads
varBase
Variant base; the base with the second most reads
morphia
The number of bases that are detected above background levels. In order to be detected above background levels, you must pass an fdr filter. See module descriptions for a description of how that works. A morphia of 0 means no bases are supported by the reads, a morphia of 1 means that only 1 base is supported by the reads, a morphia of 2 means two bases are supported by the reads, etc.
cryptic
If a SNP is cryptic, it means that it is detected when using a lower read mismatch threshold, but becomes undetected when you move to a higher read mismatch level. See “dealing with mm” in the advanced_use section for more details on what this means.
baseCoverage
The total number of reads at this position
varFreq
The fraction of reads supporting the varBase
refFreq
The fraction of reds supporting the refBase
conFreq
The fraction of reds supporting the conBase

linkage.tsv

This describes the linkage between pairs of SNPs in the mapping that are found on the same read pair at least min_snp times.

linkage.tsv
r2 d_prime r2_normalized d_prime_normalized total countAB countAb countaB countab allele_A allele_a allele_B allele_b distance position_A position_B scaffold
1.0 1.0 1.0 1.0 27 0 14 13 0 G A T C 45 191425 191470 S3_003_000X1_scaffold_20
0.10743801652892566 1.0000000000000002 0.05263157894736843 1.0 24 13 0 9 2 G A C A 80 191425 191505 S3_003_000X1_scaffold_20
0.08333333333333348 1.0 0.07894736842105264 1.0 26 11 2 13 0 T C C A 35 191470 191505 S3_003_000X1_scaffold_20
1.0000000000000009 1.0 1.0 1.0 30 22 0 0 8 C T T C 12 99342 99354 S3_003_000X1_scaffold_88
1.0000000000000004 1.0 1.0 1.0 22 17 0 0 5 C T T A 60 99342 99402 S3_003_000X1_scaffold_88

Linkage is used primarily to determine if organisms are undergoing horizontal gene transfer or not. It’s calculated for pairs of SNPs that can be connected by at least min_snp reads. It’s based on the assumption that each SNP as two alleles (for example, a A and b B). This all gets a bit confusing and has a large amount of literature around each of these terms, but I’ll do my best to briefly explain what’s going on

scaffold
The scaffold that both SNPs are on
position_A
The position of the first SNP on this scaffold
position_B
The position of the second SNP on this scaffold
distance
The distance between the two SNPs
allele_A
One of the two bases at position_A
allele_a
The other of the two bases at position_A
allele_B
One of the bases at position_B
allele_b
The other of the two bases at position_B
countAB
The number of read-pairs that have allele_A and allele_B
countAb
The number of read-pairs that have allele_A and allele_b
countaB
The number of read-pairs that have allele_a and allele_B
countab
The number of read-pairs that have allele_a and allele_b
total
The total number of read-pairs that have have information for both position_A and position_B
r2
This is the r-squared linkage metric. See below for how it’s calculated
d_prime
This is the d-prime linkage metric. See below for how it’s calculated
r2_normalized, d_prime_normalized
These are calculated by rarefying to min_snp number of read pairs. See below for how it’s calculated

Python code for the calculation of these metrics:

freq_AB = float(countAB) / total
freq_Ab = float(countAb) / total
freq_aB = float(countaB) / total
freq_ab = float(countab) / total

freq_A = freq_AB + freq_Ab
freq_a = freq_ab + freq_aB
freq_B = freq_AB + freq_aB
freq_b = freq_ab + freq_Ab

linkD = freq_AB - freq_A * freq_B

if freq_a == 0 or freq_A == 0 or freq_B == 0 or freq_b == 0:
    r2 = np.nan
else:
    r2 = linkD*linkD / (freq_A * freq_a * freq_B * freq_b)

linkd = freq_ab - freq_a * freq_b

# calc D-prime
d_prime = np.nan
if (linkd < 0):
    denom = max([(-freq_A*freq_B),(-freq_a*freq_b)])
    d_prime = linkd / denom

elif (linkD > 0):
    denom = min([(freq_A*freq_b), (freq_a*freq_B)])
    d_prime = linkd / denom

################
# calc rarefied

rareify = np.random.choice(['AB','Ab','aB','ab'], replace=True, p=[freq_AB,freq_Ab,freq_aB,freq_ab], size=min_snp)
freq_AB = float(collections.Counter(rareify)['AB']) / min_snp
freq_Ab = float(collections.Counter(rareify)['Ab']) / min_snp
freq_aB = float(collections.Counter(rareify)['aB']) / min_snp
freq_ab = float(collections.Counter(rareify)['ab']) / min_snp

freq_A = freq_AB + freq_Ab
freq_a = freq_ab + freq_aB
freq_B = freq_AB + freq_aB
freq_b = freq_ab + freq_Ab

linkd_norm = freq_ab - freq_a * freq_b

if freq_a == 0 or freq_A == 0 or freq_B == 0 or freq_b == 0:
    r2_normalized = np.nan
else:
    r2_normalized = linkd_norm*linkd_norm / (freq_A * freq_a * freq_B * freq_b)


# calc D-prime
d_prime_normalized = np.nan
if (linkd_norm < 0):
    denom = max([(-freq_A*freq_B),(-freq_a*freq_b)])
    d_prime_normalized = linkd_norm / denom

elif (linkd_norm > 0):
    denom = min([(freq_A*freq_b), (freq_a*freq_B)])
    d_prime_normalized = linkd_norm / denom

rt_dict = {}
for att in ['r2', 'd_prime', 'r2_normalized', 'd_prime_normalized', 'total', 'countAB', \
            'countAb', 'countaB', 'countab', 'allele_A', 'allele_a', \
            'allele_B', 'allele_b']:
    rt_dict[att] = eval(att)

inStrain compare

A typical run of inStrain will yield the following files in the output folder:

comparisonsTable.tsv
scaffold name1 name2 coverage_overlap compared_bases_count percent_genome_compared length consensus_SNPs population_SNPs conANI popANI
S3_016_000X1_scaffold_14208 Sloan3AllGenomeInventory.fasta-vs-S3_003_000X1.sorted.bam Sloan3AllGenomeInventory.fasta-vs-S3_016_000X1.sorted.bam 0.9825304393859184 1856 0.9814912744579588 1891 7 0 0.996228448275862 1.0
S3_016_000X1_scaffold_9493 Sloan3AllGenomeInventory.fasta-vs-S3_003_000X1.sorted.bam Sloan3AllGenomeInventory.fasta-vs-S3_016_000X1.sorted.bam 0.9778541428025964 2561 0.977107974055704 2621 2 0 0.9992190550566185 1.0
S3_016_000X1_scaffold_12686 Sloan3AllGenomeInventory.fasta-vs-S3_003_000X1.sorted.bam Sloan3AllGenomeInventory.fasta-vs-S3_016_000X1.sorted.bam 0.9787336877718704 2025 0.9768451519536904 2073 7 0 0.9965432098765432 1.0
S3_016_000X1_scaffold_11829 Sloan3AllGenomeInventory.fasta-vs-S3_003_000X1.sorted.bam Sloan3AllGenomeInventory.fasta-vs-S3_016_000X1.sorted.bam 0.9739130434782608 2128 0.9712460063897764 2191 14 0 0.9934210526315792 1.0
S3_016_000X1_scaffold_8891 Sloan3AllGenomeInventory.fasta-vs-S3_003_000X1.sorted.bam Sloan3AllGenomeInventory.fasta-vs-S3_016_000X1.sorted.bam 0.9826212889210716 2714 0.9826212889210716 2762 5 0 0.9981577008106116 1.0
scaffold
The scaffold being compared
name1
The name of the first inStrain profile being compared
name2
The name of the second inStrain profile being compared
coverage_overlap
The percentage of bases that are either covered or not covered in both of the profiles (covered = the base is present at at least min_snp coverage). The formula is length(coveredInBoth) / length(coveredInEither). If both scaffolds have 0 coverage, this will be 0.
compared_bases_count
The number of considered bases; that is, the number of bases with at least min_snp coverage in both profiles. Formula is length([x for x in overlap if x == True]).
percent_genome_compared
The percentage of bases in the scaffolds that are covered by both. The formula is length([x for x in overlap if x == True])/length(overlap). When ANI is np.nan, this must be 0. If both scaffolds have 0 coverage, this will be 0.
length
The total length of the scaffold
consensus_SNPs
The number of locations along the genome where both samples have the base at >= 5x coverage, and the consensus allele in each sample is different
population_SNPs
The number of locations along the genome where both samples have the base at >= 5x coverage, and no alleles are shared between either sample. See inStrain manuscript for more details.
popANI
The average nucleotide identity among compared bases between the two scaffolds, based on population_SNPs. Calculated using the formula popANI = (compared_bases_count - population_SNPs) / compared_bases_count
conANI
The average nucleotide identity among compared bases between the two scaffolds, based on consensus_SNPs. Calculated using the formula conANI = (compared_bases_count - consensus_SNPs) / compared_bases_count

inStrain profile_genes

A typical run of inStrain profile_genes will yield the following additional files in the output folder:

gene_info.tsv

This describes some basic information about the genes being profiled

gene_info.tsv
gene scaffold direction partial start end coverage breadth clonality microdiversity masked_breadth SNPs_per_bp min_ANI
S3_002_028G1_scaffold_0_1 S3_002_028G1_scaffold_0 -1 False 957 2219             0
S3_002_028G1_scaffold_0_2 S3_002_028G1_scaffold_0 -1 False 2189 3136             0
S3_002_028G1_scaffold_0_3 S3_002_028G1_scaffold_0 1 False 3274 5013             0
S3_002_028G1_scaffold_0_4 S3_002_028G1_scaffold_0 -1 False 5018 5746             0
S3_002_028G1_scaffold_0_5 S3_002_028G1_scaffold_0 1 False 5888 6862             0
gene
Name of the gene being profiled
scaffold
Scaffold that the gene is on
direction
Direction of the gene (based on prodigal call). If -1, means the gene is not coded in the direction expressed by the .fasta file
partial
If True this is a partial gene; based on not having partial=00 in the record description provided by Prodigal
start
Start of the gene (position on scaffold; 0-indexed)
end
End of the gene (position on scaffold; 0-indexed)
coverage
The mean coverage across the length of the gene
breadth
The number of bases in the gene that have at least 1x coverage
microdiversity
The mean nucleotide diversity (pi) among positions on the gene with at least 5x coverage
clonality
1 - microdiversity
masked_breadth
The percentage of positions in the gene with at least 5x coverage
SNPs_per_bp
The number of positions on the gene where a SNP is called
min_ANI
The minimum read ANI level when profile_genes was run (0 means the value is whatever was set with Profile was originally run)

SNP_mutation_types.tsv

This describes whether SNPs are synonymous, nonsynonymous, or intergenic

SNP_mutation_types.tsv
scaffold position refBase A C T G conBase varBase allele_count baseCoverage varFreq refFreq mutation_type mutation gene
S3_002_056W1_scaffold_121 2134 C 0 3 2 0 C T 2 5 0.4 0.6 N N:H936Y S3_002_056W1_scaffold_121_2
S3_002_056W1_scaffold_121 8509 G 7 0 0 0 A A 1 7 1.0 1.0 N N:G459R S3_002_056W1_scaffold_121_11
S3_002_056W1_scaffold_121 8510 G 7 0 0 0 A A 1 7 1.0 1.0 N N:G460E S3_002_056W1_scaffold_121_11
S3_002_056W1_scaffold_121 16899 G 0 2 0 5 G C 2 7 0.2857142857142857 0.7142857142857143 N N:G1068R S3_002_056W1_scaffold_121_20
S3_002_056W1_scaffold_121 24347 C 0 9 2 0 C T 2 11 0.18181818181818185 0.8181818181818182 N N:Q894* S3_002_056W1_scaffold_121_25

All genes with an allele_count of 1 or 2 make it into this table; see the above description of SNVs.tsv for details on what most of these columns mean

mutation_type
What type of mutation this is. N = nonsynonymous, S = synonymous, I = intergenic, M = there are multiple genes with this base so you cant tell
mutation
Short-hand code for the amino acid switch. If synonymous, this will be S: + the position. If nonsynonymous, this will be N: + the old amino acid + the position + the new amino acid.
gene
The gene this SNP is in

inStrain genome_wide

A typical run of inStrain genome_wide will yield the following additional files in the output folder:

genomeWide_scaffold_info.tsv

This is a genome-wide version of the scaffold report described above. See above for column descriptions.

genomeWide_scaffold_info.tsv
genome detected_scaffolds true_scaffolds true_length SNPs Referece_SNPs BiAllelic_SNPs MultiAllelic_SNPs consensus_SNPs population_SNPs breadth coverage std_cov mean_clonality conANI popANI unmaskedBreadth expected_breadth
S3_002_S3_002_000X1_S3_002_000X1_scaffold_633.fasta.fa 1 1 19728 24 5 19 0 7 5 0.9462185725871858 4.5430859691808605 2.7106449701139903 0.998095248422326 0.9992792421746294 0.999485172981878 0.4922952149229522 0.9818945976123048
S3_002_S3_002_000X1_S3_002_000X1_scaffold_980.fasta.fa 1 1 11440 0 0 0 0 0 0 0.10113636363636364 0.10113636363636364 0.3015092031543595   0.0 0.0 0.0 0.08543195678460236
S3_002_S3_002_028Y1_S3_002_028Y1_scaffold_1.fasta.fa 1 1 21455 0 0 0 0 0 0 0.5250058261477512 0.925378699603822 1.1239958370555831 0.9985388128180482 1.0 1.0 0.010207410859939408 0.5582933883068741
S3_002_S3_002_028Y1_S3_002_028Y1_scaffold_22.fasta.fa 1 1 15306 62 2 60 0 10 2 0.9562263164771984 4.977525153534561 4.1617488447219975 0.9939042740586184 0.9983668136534378 0.9996733627306876 0.4000392003136025 0.9876630284821302
S3_002_S3_002_028Y1_S3_002_028Y1_scaffold_24.fasta.fa 1 1 10383 64 6 58 0 18 6 0.9650390060676104 4.310507560435327 2.783478652159297 0.9912517160274896 0.9957865168539326 0.9985955056179776 0.4114417798324184 0.9777670126398924

genomeWide_read_report.tsv

This is a genome-wide version of the read report described above. See above for column descriptions.

genomeWide_read_report.tsv
genome scaffolds unfiltered_reads unfiltered_pairs pass_filter_cutoff pass_max_insert pass_min_insert pass_min_mapq filtered_pairs mean_mistmaches mean_insert_distance mean_mapq_score mean_pair_length median_insert mean_PID
S2_002_005G1_phage_Clostridioides_difficile.fasta 1 10605 5062 5048 5062 5062 5062 5048 0.3832477281706835 312.3638877913868 1.3024496246542872 293.6845120505729 308.0 0.998581261373412
S2_018_020G1_bacteria_Clostridioides_difficile.fasta 34 4453547 2163329 2149205 2163040 2162730 2163329 2148394 0.5636466689761853 321.3510672021471 41.47419579138972 293.33494491093336 312.5147058823529 0.9979527547934701

inStrain plot

This is what the results of inStrain plot look like.

1) Coverage and breadth vs. read mismatches

_images/Example1.png

Breadth of coverage (blue line), coverage depth (red line), and expected breadth of coverage given the depth of coverage (dotted blue line) versus the minimum ANI of mapped reads. Coverage depth continues to increase while breadth of plateaus, suggesting that all regions of the reference genome are not present in the reads being mapped.

2) Genome-wide microdiversity metrics

_images/genomeWide_microdiveristy_metrics_1.png
_images/genomeWide_microdiveristy_metrics_2.png

SNV density, coverage, and nucleotide diversity. Spikes in nucleotide diversity and SNV density do not correspond with increased coverage, indicating that the signals are not due to read mis-mapping. Positions with nucleotide diversity and no SNV-density are those where diversity exists but is not high enough to call a SNV

3) Read-level ANI distribution

_images/readANI_distribution.png

Distribution of read pair ANI levels when mapped to a reference genome; this plot suggests that the reference genome is >1% different than the mapped reads

4) Major allele frequencies

_images/MajorAllele_frequency_plot.png

Distribution of the major allele frequencies of bi-allelic SNVs (the Site Frequency Spectrum). Alleles with major frequencies below 50% are the result of multiallelic sites. The lack of distinct puncta suggest that more than a few distinct strains are present.

5) Linkage decay

_images/LinkageDecay_plot.png
_images/Example5.png

Metrics of SNV linkage vs. distance between SNVs; linkage decay (shown in one plot and not the other) is a common signal of recombination.

6) Read filtering plots

_images/ReadFiltering_plot.png

Bar plots showing how many reads got filtered out during filtering. All percentages are based on the number of paired reads; for an idea of how many reads were filtered out for being non-paired, compare the top bar and the second to top bar.

7) Scaffold inspection plot (large)

_images/ScaffoldInspection_plot.png

This is an elongated version of the genome-wide microdiversity metrics that is long enough for you to read scaffold names on the y-axis

8) Linkage with SNP type (GENES REQUIRED)

_images/LinkageDecay_types_plot.png

Linkage plot for pairs of non-synonymous SNPs and all pairs of SNPs

9) Gene histograms (GENES REQUIRED)

_images/GeneHistogram_plot.png

Histogram of values for all genes profiled

10) Compare dendrograms (RUN ON COMPARE; NOT PROFILE)

_images/Example10.png

A dendrogram comparing all samples based on popANI and based on shared_bases.