Expected output =================== 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. .. csv-table:: scaffold_info.tsv scaffold,length,coverage,breadth,nucl_diversity,coverage_median,coverage_std,coverage_SEM,breadth_minCov,breadth_expected,nucl_diversity_median,nucl_diversity_rarefied,nucl_diversity_rarefied_median,breadth_rarefied,conANI_reference,popANI_reference,SNS_count,SNV_count,divergent_site_count,consensus_divergent_sites,population_divergent_sites N5_271_010G1_scaffold_100,1148,1.89808362369338,0.9764808362369338,0.0,2,1.0372318863390368,0.030626273060932862,0.018292682926829267,0.8128805020451009,0.0,,,0.0,1.0,1.0,0,0,0,0,0 N5_271_010G1_scaffold_102,1144,2.388986013986014,0.9956293706293706,0.003678160837326971,2,1.3042095721915248,0.038576628450898466,0.07604895104895107,0.8786983245100435,0.0,,,0.0,1.0,1.0,0,0,0,0,0 N5_271_010G1_scaffold_101,1148,1.7439024390243902,0.9599303135888502,,2,0.8728918441975071,0.025773816178570358,0.0,0.7855901382035807,,,,0.0,0.0,0.0,0,00,0,0 N5_271_010G1_scaffold_103,1142,2.039404553415061,0.9938704028021016,0.0,2,1.1288397384374758,0.03341869350286944,0.04028021015 scaffold The name of the :term:`scaffold` in the input .fasta file length Full length of the :term:`scaffold` in the input .fasta file 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 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 nucl_diversity The mean :term:`nucleotide diversity` of all bases in the scaffold that have a nucleotide diversity value calculated. So if only 1 base on the scaffold meets the minimum coverage to calculate nucleotide diversity, the nucl_diversity of the scaffold will be the nucleotide diversity of that base. Will be blank if no positions have a base over the minimum coverage. coverage_median The median depth of coverage value of all bases in the scaffold, included bases with 0 coverage coverage_std The standard deviation of all coverage values coverage_SEM The standard error of the mean of all coverage values (calculated using `scipy.stats.sem `_) breadth_minCov The percentage of bases in the scaffold that have at least min_cov coverage (e.g. the percentage of bases that have a nucl_diversity value and meet the minimum sequencing depth to call SNVs) breadth_expected :term:`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, prophage, etc.) nucl_diversity_median The median :term:`nucleotide diversity` value of all bases in the scaffold that have a :term:`nucleotide diversity` value calculated nucl_diversity_rarefied The average :term:`nucleotide diversity` among positions that have at least ``--rarefied_coverage`` (50x by default). These values are also calculated by randomly subsetting the reads at that position to ``--rarefied_coverage`` reads nucl_diversity_rarefied_median The median rarefied :term:`nucleotide diversity` (similar to that described above) breadth_rarefied The percentage of bases in a scaffold that have at least ``--rarefied_coverage`` conANI_reference The :term:`conANI` between the reads and the reference genome popANI_reference The :term:`popANI` between the reads and the reference genome SNS_count The total number of :term:`SNSs` called on this scaffold SNV_count The total number of :term:`SNVs` called on this scaffold divergent_site_count The total number of :term:`divergent sites` called on this scaffold consensus_divergent_sites The total number of :term:`divergent sites` in which the reads have a different consensus allele than the reference genome. These count as "differences" in the conANI_reference calculation, and ``breadth_minCov`` * ``length`` counts as the denominator. population_divergent_sites The total number of :term:`divergent sites` in which the reads do not have the reference genome base as any allele at all (major or minor). These count as "differences" in the popANI_reference calculation, and ``breadth_minCov`` * ``length`` counts as the denominator. mapping_info.tsv +++++++++++++++++ This provides an overview of the number of reads that map to each scaffold, and some basic metrics about their quality. The header line (starting with #; not shown in the table below) describes the parameters that were used to filter the reads .. csv-table:: mapping_info.tsv scaffold,pass_pairing_filter,filtered_pairs,median_insert,mean_PID,pass_min_insert,unfiltered_reads,unfiltered_pairs,pass_min_read_ani,filtered_priority_reads,unfiltered_singletons,mean_insert_distance,pass_min_mapq,mean_mistmaches,mean_mapq_score,unfiltered_priority_reads,pass_max_insert,filtered_singletons,mean_pair_length all_scaffolds,22886,9435,318.75998426985933,0.942328296264744,22804.0,71399,22886,9499.0,0,25627,322.1849602376999,22886.0,14.325963471117715,17.16896792799091,0,22828.0,0,255.52 N5_271_010G1_scaffold_1,432,346,373.0,0.9719013034762376,432.0,959,432,346.0,0,95,373.72222222222223,432.0,7.643518518518517,33.030092592592595,0,432.0,0,274.7106481481 N5_271_010G1_scaffold_0,741,460,389.0,0.9643004762700924,740.0,1841,741,461.0,0,359,387.94466936572195,741.0,10.2361673414305,26.537112010796218,0,741.0,0,285.5033738191 N5_271_010G1_scaffold_2,348,252,369.5,0.965446218901576,347.0,865,348,253.0,0,169,349.0172413793104,348.0,8.227011494252874,31.557471264367813,0,347.0,0,243.3103448275 N5_271_010G1_scaffold_3,301,205,367.0,0.9639376512009891,301.0,1088,301,205.0,0,486,327.81395348837214,301.0,8.70764119601329,29.089700996677745,0,300.0,0,251.2624584717 N5_271_010G1_scaffold_4,213,153,389.0,0.9649427929020106,213.0,502,213,153.0,0,76,372.3896713615024,213.0,9.27699530516432,30.70422535211268,0,213.0,0,269.2300469483 N5_271_010G1_scaffold_5,134,114,366.0,0.977820509122326,134.0,349,134,116.0,0,81,376.4552238805969,134.0,5.164179104477612,37.61194029850746,0,132.0,0,246.8059701492 N5_271_010G1_scaffold_6,140,130,384.5,0.9813174696928879,140.0,316,140,130.0,0,36,372.45,140.0,4.864285714285714,38.43571428571428,0,140.0,0,261.3071428571429 scaffold The name of the :term:`scaffold` in the input .fasta file. For the top row this will read ``all_scaffolds``, and it has the sum of all rows. pass_pairing_filter The number of individual reads that pass the selecting pairing filter (only paired reads will pass this filter by default) filtered_pairs The number of pairs of reads that pass all cutoffs 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 pass_min_insert The number of pairs of reads mapping to this scaffold that pass the minimum insert size cutoff 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_min_read_ani The number of pairs of reads mapping to this scaffold that pass the min_read_ani cutoff filtered_priority_reads The number of priority reads that pass the rest of the filters (will only be non-0 if a priority reads input file is provided) unfiltered_singletons The number of reads detected in which only one read of the pair is mapped 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) pass_min_mapq The number of pairs of reads mapping to this scaffold that pass the minimum mapQ score cutoff mean_mistmaches Among all pairs of reads mapping to this scaffold, the mean number of mismatches mean_mapq_score Among all pairs of reads mapping to this scaffold, the average mapQ score unfiltered_priority_reads The number of reads that pass the pairing filter because they were part of the ``priority_reads`` input file (will only be non-0 if a priority reads input file is provided). 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) filtered_singletons The number of reads detected in which only one read of the pair is mapped AND which make it through to be considered. This will only be non-0 if the filtering settings allows non-paired reads mean_pair_length Among all pairs of reads mapping to this scaffold, the average length of both reads in the pair summed together .. warning:: Adjusting the pairing filter will result in odd values for the "filtered_pairs" column; this column reports the number of pairs AND singletons that pass the filters. To calculate the true number of filtered pairs, use the formula filtered_pairs - filtered_singletons SNVs.tsv +++++++++++++++++ This describes the :term:`SNVs` and :term:`SNSs` that are detected in this mapping. While we should refer to these mutations as :term:`divergent sites`, sometimes SNV is used to refer to both SNVs and SNSs .. warning:: inStrain reports 0-based values for "position". The first base in a scaffold will be position "0", second based position "1", etc. .. csv-table:: SNVs.tsv scaffold,position,position_coverage,allele_count,ref_base,con_base,var_base,ref_freq,con_freq,var_freq,A,C,T,G,gene,mutation,mutation_type,cryptic,class N5_271_010G1_scaffold_120,174,5,2,C,C,A,0.6,0.6,0.4,2,3,0,0,,,I,False,SNV N5_271_010G1_scaffold_120,195,6,1,T,C,A,0.0,1.0,0.0,0,6,0,0,,,I,False,SNS N5_271_010G1_scaffold_120,411,8,2,A,A,C,0.75,0.75,0.25,6,2,0,0,N5_271_010G1_scaffold_120_1,N:V163G,N,False,SNV N5_271_010G1_scaffold_120,426,9,2,G,G,T,0.7777777777777778,0.7777777777777778,0.2222222222222222,0,0,2,7,N5_271_010G1_scaffold_120_1,N:S178Y,N,False,SNV N5_271_010G1_scaffold_120,481,6,2,C,T,C,0.3333333333333333,0.6666666666666666,0.3333333333333333,0,2,4,0,N5_271_010G1_scaffold_120_1,N:D233N,N,False,con_SNV N5_271_010G1_scaffold_120,484,6,2,G,A,G,0.3333333333333333,0.6666666666666666,0.3333333333333333,4,0,0,2,N5_271_010G1_scaffold_120_1,N:P236S,N,False,con_SNV N5_271_010G1_scaffold_120,488,5,1,T,C,T,0.2,0.8,0.2,0,4,1,0,N5_271_010G1_scaffold_120_1,S:240,S,False,SNS N5_271_010G1_scaffold_120,811,5,1,T,A,T,0.2,0.8,0.2,4,0,1,0,N5_271_010G1_scaffold_120_1,N:N563Y,N,False,SNS N5_271_010G1_scaffold_120,897,7,2,G,G,T,0.7142857142857143,0.7142857142857143,0.2857142857142857,0,0,2,5,,,I,False,SNV See the :doc:`module_descriptions` for what constitutes a SNP (what makes it into this table) scaffold The scaffold that the SNV is on position The genomic position of the SNV position_coverage The number of reads detected at this position allele_count The number of bases that are detected above background levels (according to the :term:`null model`. An allele_count of 0 means no bases are supported by the reads, an allele_count of 1 means that only 1 base is supported by the reads, an allele_count of 2 means two bases are supported by the reads, etc. ref_base The reference base in the .fasta file at that position con_base The consensus base (the base that is supported by the most reads) var_base Variant base; the base with the second most reads ref_freq The fraction of reads supporting the ref_base con_freq The fraction of reds supporting the con_base var_freq The fraction of reads supporting the var_base A, C, T, and G The number of mapped reads encoding each of the bases gene If a gene file was included, this column will be present listing if the SNV is in the coding sequence of a gene 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. **NOTE** - the position of the amino acid is always calculated from left to right on the genome file, whether or not it's the forward or reverse strand. Codons are calculated correctly (considering strandedness), this only impacts the reported "position" in this column. I know this is weird behavior and it will change in future inStrain versions. 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 cryptic If an SNV 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. class The classification of this divergent site. The options are :term:`SNS` (meaning allele_count is 1 and con_base does not equal ref_base), :term:`SNV` (meaning allele_count is > 1 and con_base *does* equal ref_base), con_SNV (meaning allele_count is > 1, con_base does not equal ref_base, and ref_base *is* present in the reads; these count as differences in conANI calculations), pop_SNV (meaning allele_count is > 1, con_base does not equal ref_base, and ref_base *is not* present in the reads; these count as differences in popANI and conANI calculations), DivergentSite (meaning allele count is 0), and AmbiguousReference (meaning the ref_base is not A, C, T, or G) linkage.tsv +++++++++++++++++ This describes the :term:`linkage` between pairs of SNPs in the mapping that are found on the same read pair at least min_snp times. .. warning:: inStrain reports 0-based values for "position". The first base in a scaffold will be position "0", second based position "1", etc. .. csv-table:: linkage.tsv scaffold,position_A,position_B,distance,r2,d_prime,r2_normalized,d_prime_normalized,allele_A,allele_a,allele_B,allele_b,countab,countAb,countaB,countAB,total N5_271_010G1_scaffold_93,58,59,1,0.021739130434782702,1.0,0.031141868512110725,1.0,C,T,G,A,0,3,4,20,27 N5_271_010G1_scaffold_93,58,70,12,0.012820512820512851,1.0,,,C,T,T,A,0,2,4,22,28 N5_271_010G1_scaffold_93,58,80,22,0.016722408026755814,1.0,0.005847953216374271,1.0,C,T,G,A,0,2,5,21,28 N5_271_010G1_scaffold_93,58,84,26,0.7652173913043475,1.0000000000000002,0.6296296296296297,1.0,C,T,G,C,4,0,1,22,27 N5_271_010G1_scaffold_93,58,101,43,0.00907029478458067,1.0,,,C,T,C,A,0,2,2,19,23 N5_271_010G1_scaffold_93,58,126,68,0.01754385964912257,1.0,0.002770083102493075,1.0,C,T,A,T,0,2,3,16,21 N5_271_010G1_scaffold_93,58,133,75,0.008333333333333352,1.0,,,C,T,G,T,0,1,3,17,21 N5_271_010G1_scaffold_93,59,70,11,0.010869565217391413,1.0,0.02777777777777779,1.0,G,A,T,A,0,2,3,21,26 N5_271_010G1_scaffold_93,59,80,21,0.6410256410256397,1.0,1.0,1.0,G,A,G,A,2,0,1,25,28 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 has 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 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 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 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) gene_info.tsv +++++++++++++++++ This describes some basic information about the genes being profiled .. warning:: inStrain reports 0-based values for "position", including the "start" and "stop" in this table. The first base in a scaffold will be position "0", second based position "1", etc. .. csv-table:: gene_info.tsv scaffold,gene,gene_length,coverage,breadth,breadth_minCov,nucl_diversity,start,end,direction,partial,dNdS_substitutions,pNpS_variants,SNV_count,SNV_S_count,SNV_N_count,SNS_count,SNS_S_count,SNS_N_count,divergent_site_count N5_271_010G1_scaffold_0,N5_271_010G1_scaffold_0_1,141.0,0.7092198581560284,0.7092198581560284,0.0,,143,283,-1,False,,,0.0,0.0,0.0,0.0,0.0,0.0,0.0 N5_271_010G1_scaffold_0,N5_271_010G1_scaffold_0_2,219.0,4.849315068493151,1.0,0.45662100456620996,0.012312216758728069,2410,2628,-1,False,,0.0,0.0,0.0,0.0,0.0,0.0,0.0 N5_271_010G1_scaffold_0,N5_271_010G1_scaffold_0_3,282.0,7.528368794326241,1.0,0.9609929078014184,0.00805835530326815,3688,3969,-1,False,,0.0,0.0,0.0,0.0,0.0,0.0,0.0 N5_271_010G1_scaffold_1,N5_271_010G1_scaffold_1_1,336.0,2.7261904761904763,1.0,0.0625,0.0,0,335,-1,False,,,0.0,0.0,0.0,0.0,0.0,0.0,0.0 N5_271_010G1_scaffold_1,N5_271_010G1_scaffold_1_2,717.0,7.714086471408647,1.0,0.8926080892608089,0.011336830817162968,378,1094,-1,False,,0.554203539823008,9.0,2.0,6.0,0.0,0.0,0.0,9.0 N5_271_010G1_scaffold_1,N5_271_010G1_scaffold_1_3,114.0,13.105263157894735,1.0,1.0,0.016291986431991808,1051,1164,-1,False,,0.3956834532374099,4.0,1.0,2.0,0.0,0.0,0.0,4.0 N5_271_010G1_scaffold_1,N5_271_010G1_scaffold_1_4,111.0,11.342342342342342,1.0,1.0,0.02102806761458109,1164,1274,-1,False,,,5.0,0.0,5.0,0.0,0.0,0.0,5.0 N5_271_010G1_scaffold_1,N5_271_010G1_scaffold_1_5,174.0,9.057471264367816,1.0,1.0,0.006896087493019509,1476,1649,-1,False,,0.0,2.0,2.0,0.0,0.0,0.0,0.0,2.0 N5_271_010G1_scaffold_1,N5_271_010G1_scaffold_1_6,174.0,6.195402298850576,1.0,0.7413793103448276,0.028698649055273976,1656,1829,-1,False,,0.5790697674418601,4.0,1.0,3.0,0.0,0.0,0.0,4.0 scaffold Scaffold that the gene is on gene Name of the gene being profiled gene_length Length of the gene in nucleotides :term:`breadth` The number of bases in the gene that have at least 1x coverage breadth_minCov The number of bases in the gene that have at least min_cov coverage nucl_diversity The mean :term:`nucleotide diversity` of all bases in the gene that have a nucleotide diversity value calculated. So if only 1 base on the scaffold meets the minimum coverage to calculate nucleotide diversity, the nucl_diversity of the scaffold will be the nucleotide diversity of that base. Will be blank if no positions have a base over the minimum coverage. start Start of the gene (position on scaffold; 0-indexed) end End of the gene (position on scaffold; 0-indexed) 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 :term:`dNdS_substitutions` The :term:`dN/dS` of :term:`SNSs` detected in this gene. Will be blank if 0 N and/or 0 S substitutions are detected :term:`pNpS_variants` The :term:`pN/pS` of :term:`SNVs` detected in this gene. Will be blank if 0 N and/or 0 S SNVs are detected SNV_count Total number of :term:`SNVs` detected in this gene SNV_S_count Number of synonymous :term:`SNVs` detected in this gene SNV_N_count Number of non-synonymous :term:`SNVs` detected in this gene SNS_count Total number of :term:`SNSs` detected in this gens SNS_S_count Number of synonymous :term:`SNSs` detected in this gens SNS_N_count Number of non-synonymous :term:`SNSs` detected in this gens divergent_site_count Number of :term:`divergent sites` detected in this gens genome_info.tsv ++++++++++++++++ Describes many of the above metrics on a genome-by-genome level, rather than a scaffold-by-scaffold level. .. csv-table:: genome_info.tsv genome,coverage,breadth,nucl_diversity,length,true_scaffolds,detected_scaffolds,coverage_median,coverage_std,coverage_SEM,breadth_minCov,breadth_expected,nucl_diversity_rarefied,conANI_reference,popANI_reference,iRep,iRep_GC_corrected,linked_SNV_count,SNV_distance_mean,r2_mean,d_prime_mean,consensus_divergent_sites,population_divergent_sites,SNS_count,SNV_count,filtered_read_pair_cou nt,reads_unfiltered_pairs,reads_mean_PID,reads_unfiltered_reads,divergent_site_count fobin.fasta,132.07770270270268,0.9974662162162162,0.035799449026225894,1184,1,1,113,114.96590198492832,3.6668428018497408,0.9822635135135136,1.0,0.034319907739082,0.979363714531 3844,0.9939810834049873,False,1064.0,120.48214285714286,0.07781470898619759,0.8710788695476385,24,7,7,97,926,5991,0.9239440924157436,19260,104 maxbin2.maxbin.001.fasta,6.5637243038012985,0.8940915760335204,0.007116301715134402,264436,166,166,5,9.475490303923918,0.019704930458769948,0.5080246259964604,0.99695960719657,0.0002 8497234066195295,0.997201131457496,0.9990248622897128,False,777.0,80.73101673101674,0.2979679685064011,0.9518999449773424,376,131,127,1246,7368,9309,0.9783316024248924,2 5281,1373 genome The name of the genome being profiled. If all scaffolds were a single genome, this will read "all_scaffolds" coverage Average :term:`coverage depth` of all scaffolds of this genome breadth The :term:`breadth` of all scaffolds of this genome nucl_diversity The average :term:`nucleotide diversity` of all scaffolds of this genome length The full length of this genome across all scaffolds true_scaffolds The number of scaffolds present in this genome based off of the scaffold-to-bin file detected_scaffolds The number of scaffolds with at least a single read-pair mapping to them coverage_median The median :term:`coverage` among all bases in the genome coverage_std The standard deviation of all coverage values coverage_SEM The standard error of the mean of all coverage values (calculated using `scipy.stats.sem `_) breadth_minCov The percentage of bases in the scaffold that have at least min_cov coverage (e.g. the percentage of bases that have a nucl_diversity value and meet the minimum sequencing depth to call SNVs) breadth_expected 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, prophage, etc.) nucl_diversity_rarefied The average :term:`nucleotide diversity` among positions that have at least ``--rarefied_coverage`` (50x by default). These values are also calculated by randomly subsetting the reads at that position to ``--rarefied_coverage`` reads conANI_reference The :term:`conANI` between the reads and the reference genome popANI_reference The :term:`popANI` between the reads and the reference genome iRep The :term:`iRep` value for this genome (if it could be successfully calculated) iRep_GC_corrected A True / False value of whether the iRep value was corrected for GC bias linked_SNV_count The number of :term:`divergent sites` that could be :term:`linked` in this genome SNV_distance_mean Average distance between linked :term:`divergent sites` r2_mean Average r2 between linked SNVs (see explanation of linkage.tsv above for more info) d_prime_mean Average d prime between linked SNVs (see explanation of linkage.tsv above for more info) consensus_divergent_sites The total number of :term:`divergent sites` in which the reads have a different consensus allele than the reference genome. These count as "differences" in the conANI_reference calculation, and ``breadth_minCov`` * ``length`` counts as the denominator. population_divergent_sites The total number of :term:`divergent sites` in which the reads do not have the reference genome base as any allele at all (major or minor). These count as "differences" in the popANI_reference calculation, and ``breadth_minCov`` * ``length`` counts as the denominator. SNS_count The total number of :term:`SNSs` called on this genome SNV_count The total number of :term:`SNVs` called on this genome filtered_read_pair_count The total number of read pairs that pass filtering and map to this genome reads_unfiltered_pairs The total number of pairs, filtered or unfiltered, that map to this genome reads_mean_PID The average ANI of mapped read pairs to the reference genome for this genome reads_unfiltered_reads The total number of reads, filtered or unfiltered, that map to this genome divergent_site_count The total number of :term:`divergent sites` called on this genome inStrain parse_annotations --------------------- A typical run of inStrain `parse_gene_annotations` will yield the following files in the output folder. For more information, see :doc:`user_manual` LongFormData.csv +++++++++++++++++ All of the annotation information a very long table .. csv-table:: LongFormData.csv sample,anno,genomes,genes,bases 2bag10_1.bam,K03737,{'REFINED_METABAT215_TOP10_CONTIGS_1500_ASSEMBLY_K77_MERGED__Hadza_MoBio_hadza-E-H_A_23_1707.16.fa'},1,6666 2bag10_1.bam,K06973,{'REFINED_METABAT215_TOP10_CONTIGS_1500_ASSEMBLY_K77_MERGED__Hadza_MoBio_hadza-E-H_A_23_1707.16.fa'},1,1068 2bag10_1.bam,K04066,"{'REFINED_METABAT215_TOP10_CONTIGS_1500_ASSEMBLY_K77_MERGED__Hadza_MoBio_hadza-E-H_A_23_1707.16.fa', 'Bifidobacterium_longum_subsp_infantis_ATCC_15697.fna'}",2,195761 2bag10_1.bam,K15558,"{'REFINED_METABAT215_TOP10_CONTIGS_1500_ASSEMBLY_K77_MERGED__Hadza_MoBio_hadza-E-H_A_23_1707.16.fa', 'Bifidobacterium_longum_subsp_infantis_ATCC_15697.fna'}",96,10748749 2bag10_1.bam,K19762,"{'REFINED_METABAT215_TOP10_CONTIGS_1500_ASSEMBLY_K77_MERGED__Hadza_MoBio_hadza-E-H_A_23_1707.16.fa', 'Bifidobacterium_longum_subsp_infantis_ATCC_15697.fna'}",97,10920075 2bag10_1.bam,3000025,"{'REFINED_METABAT215_TOP10_CONTIGS_1500_ASSEMBLY_K77_MERGED__Hadza_MoBio_hadza-E-H_A_23_1707.16.fa', 'Bifidobacterium_longum_subsp_infantis_ATCC_15697.fna'}",2,168916 2bag10_1.bam,K18888,"{'REFINED_METABAT215_TOP10_CONTIGS_1500_ASSEMBLY_K77_MERGED__Hadza_MoBio_hadza-E-H_A_23_1707.16.fa', 'Bifidobacterium_longum_subsp_infantis_ATCC_15697.fna'}",3,504008 2bag10_1.bam,K20386,"{'REFINED_METABAT215_TOP10_CONTIGS_1500_ASSEMBLY_K77_MERGED__Hadza_MoBio_hadza-E-H_A_23_1707.16.fa', 'Bifidobacterium_longum_subsp_infantis_ATCC_15697.fna'}",98,11007871 2bag10_1.bam,K07979,{'REFINED_METABAT215_TOP10_CONTIGS_1500_ASSEMBLY_K77_MERGED__Hadza_MoBio_hadza-E-H_A_23_1707.16.fa'},1,742 sample The sample this row refers to (based on the name of the .bam file used to create the inStrain profile) anno The annotation this row refers to (based on the input annotation table) genomes The specific genomes that have this particular annotation. Represented as a python set genes The total number of genes detected with this annotation in this sample bases The total number of base-pairs mapped to all genes with this annotation in this sample SampleAnnotationTotals.csv +++++++++++++++++++++++++++++ Totals for each sample. Used to generate the `_fraction` tables enumerated below. .. csv-table:: SampleAnnotationTotals.csv sample,detected_genes,detected_genomes,bases_mapped_to_genes,detected_annotations,detected_genes_with_anno 2bag10_1.bam,2625,2,222405987,3302,1677 2bag10_2.bam,20909,10,2418511040,32225,15513 sample The sample this row refers to (based on the name of the .bam file used to create the inStrain profile) detected_genes The total number of genes detected in this sample after passing the set filters detected_genomes The total number of genomes detected in this sample after passing the set filters bases_mapped_to_genes The total number of bases mapped to detected genes. See `ParsedGeneAnno_bases.csv` below for more info detected_annotations The total number of annotations detected; this can be higher than `detected_genes_with_anno` if some genes have multiple annotations detected_genes_with_anno The total number of genes detected with at least one annotation ParsedGeneAnno_*.csv +++++++++++++++++++++++++++++ There are a total of 6 tables like this generated in the output folder, each looking like the following: .. csv-table:: ParsedGeneAnno_bases.csv sample,3000005,3000024,3000025,3000026,3000027,3000074,3000118,3000165,3000166 2bag10_1.bam,131097,1286827,168916,1656,0,0,0,0,0 2bag10_2.bam,104013,5016854,955645,2552,633275,1034042,95617,409295,541951 In each case the column `sample` is the sample the row refers to (based on the name of the .bam file used to create the inStrain profile), and all other columns are annotations from the input annotation_table provides. The number values differ depending on the individual output table being analyzed. Below you can find descriptions on what the numbers refer to: ParsedGeneAnno_bases.csv The total number of base pairs mapped to all genes with this annotation. The number of base pairs mapped for each gene with this annotation is calculated as the gene length * the coverage of the gene, and the number reported is the sum of this value of all genes ParsedGeneAnno_bases_fraction.csv The values in `ParsedGeneAnno_bases.csv` divided by the total number of bases mapped to all detected genes (the value `bases_mapped_to_genes` reported in `SampleAnnotationTotals.csv`) ParsedGeneAnno_genes.csv The total number of detected genes with this annotation ParsedGeneAnno_genes_fraction.csv The values in `ParsedGeneAnno_genes.csv` divided by the total number of genes detected (the value `detected_genes` reported in `SampleAnnotationTotals.csv`) ParsedGeneAnno_genomes.csv The total number of genomes with at least one detected gene with this annotation ParsedGeneAnno_genomes_fraction.csv The values in `ParsedGeneAnno_genomes.csv` divided by the total number of genomes detected (the value `detected_genomes` reported in `SampleAnnotationTotals.csv`) inStrain compare --------------------- A typical run of inStrain will yield the following files in the output folder: comparisonsTable.tsv +++++++++++++++++++++ Summarizes the differences between two inStrain profiles on a scaffold by scaffold level .. csv-table:: comparisonsTable.tsv scaffold,name1,name2,coverage_overlap,compared_bases_count,percent_genome_compared,length,consensus_SNPs,population_SNPs,popANI,conANI N5_271_010G1_scaffold_98,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,1.0,61,0.05290546400693842,1153,0,0,1.0,1.0 N5_271_010G1_scaffold_133,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,1.0,78,0.0741444866920152,1052,0,0,1.0,1.0 N5_271_010G1_scaffold_144,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,1.0,172,0.16715257531584066,1029,0,0,1.0,1.0 N5_271_010G1_scaffold_158,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,1.0,36,0.035749751737835164,1007,0,0,1.0,1.0 N5_271_010G1_scaffold_57,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,1.0,24,0.0183206106870229,1310,0,0,1.0,1.0 N5_271_010G1_scaffold_139,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,1.0,24,0.023121387283236997,1038,0,0,1.0,1.0 N5_271_010G1_scaffold_92,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,1.0,336,0.286934244235696,1171,0,0,1.0,1.0 N5_271_010G1_scaffold_97,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,1.0,22,0.01901469317199654,1157,0,0,1.0,1.0 N5_271_010G1_scaffold_100,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,1.0,21,0.018292682926829267,1148,0,0,1.0,1.0 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. Used to calculate :term:`conANI` 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. Used to calculate :term:`popANI` :term:`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 :term:`conNI` 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 pairwise_SNP_locations.tsv +++++++++++++++++++++++++++ .. warning:: inStrain reports 0-based values for "position". The first base in a scaffold will be position "0", second based position "1", etc. Lists the locations of all differences between profiles. Because it's a big file, this will only be created is you include the flag ``--store_mismatch_locations`` in your inStrain compare command. .. csv-table:: pairwise_SNP_locations.tsv scaffold,position,name1,name2,consensus_SNP,population_SNP,con_base_1,ref_base_1,var_base_1,position_coverage_1,A_1,C_1,T_1,G_1,con_base_2,ref_base_2,var_base_2,position_coverage_2,A_2,C_2,T_2,G_2 N5_271_010G1_scaffold_9,823,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G2.sorted.bam,True,False,G,G,A,10.0,3.0,0.0,0.0,7.0,A,G,G,6.0,3.0,0.0,0.0,3.0 N5_271_010G1_scaffold_11,906,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G2.sorted.bam,True,False,T,T,C,6.0,0.0,2.0,4.0,0.0,C,T,T,7.0,0.0,4.0,3.0,0.0 N5_271_010G1_scaffold_29,436,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G2.sorted.bam,True,False,C,T,T,6.0,0.0,3.0,3.0,0.0,T,T,C,7.0,0.0,3.0,4.0,0.0 N5_271_010G1_scaffold_140,194,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G2.sorted.bam,True,False,A,A,T,6.0,4.0,0.0,2.0,0.0,T,A,A,9.0,4.0,0.0,5.0,0.0 N5_271_010G1_scaffold_24,1608,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G2.sorted.bam,True,False,G,G,A,8.0,2.0,0.0,0.0,6.0,A,G,G,6.0,5.0,0.0,0.0,1.0 N5_271_010G1_scaffold_112,600,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G2.sorted.bam,True,False,A,G,G,6.0,4.0,0.0,0.0,2.0 N5_271_010G1_scaffold_88,497,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G2.sorted.bam,True,False,A,G,G,5.0,3.0,0.0,0.0,2.0 N5_271_010G1_scaffold_53,1108,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G2.sorted.bam,True,False,A,A,G,5.0,3.0,0.0,0.0,2.0,G,A,A,15.0,6.0,0.0,0.0,9.0 N5_271_010G1_scaffold_46,710,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G2.sorted.bam,True,False,A,C,C,6.0,4.0,2.0,0.0,0.0,C,C,A,6.0,2.0,4.0,0.0,0.0 scaffold The scaffold on which the difference is located position The position where the difference is located (0-based) name1 The name of the first `inStrain profile` being compared name2 The name of the second `inStrain profile` being compared consensus_SNP A True / False column listing whether or not this difference counts towards :term:`conANI` calculations population_SNP A True / False column listing whether or not this difference counts towards :term:`popANI` calculations con_base_1 The consensus base of the profile listed in ``name1`` at this position ref_base_1 The reference base of the profile listed in ``name1`` at this position (will be the same as ``ref_base_2``) var_base_1 The variant base of the profile listed in ``name1`` at this position position_coverage_1 The number of reads mapping to this position in ``name1`` A_1, C_1, T_1, G_1 The number of mapped reads with each nucleotide in ``name1`` con_base_2, ref_base_2, ... The above columns are also listed for the ``name2`` sample genomeWide_compare.tsv +++++++++++++++++++++++++++ A genome-level summary of the differences detected by inStrain compare. Generated by running ``inStrain genome_wide`` on the results of ``inStrain compare``, or by providing an stb file to the original inStrain compare command. .. csv-table:: genomeWide_compare.tsv genome,name1,name2,coverage_overlap,compared_bases_count,consensus_SNPs,population_SNPs,popANI,conANI,percent_compared all_scaffolds,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,1.0,100712,0,0,1.0,1.0,0.3605549091560011 all_scaffolds,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G2.sorted.bam,0.6852932198159855,71900,196,,50.9999304589707928,0.9972739916550765,0.25740624720307886 all_scaffolds,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G2.sorted.bam,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G2.sorted.bam,1.0,145663,0,0,1.0,1.0,0.5214821444553835 genome The genome 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 genome 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. Used to calculate :term:`conANI` 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. Used to calculate :term:`popANI` :term:`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 :term:`conNI` 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 strain_clusters.tsv +++++++++++++++++++++++++++ The result of clustering the pairwise comparison data provided in ``genomeWide_compare.tsv`` to generate strain-level clusters. Performed using hierarchical clustering in the same manner as the program ``dRep``; `see the dRep documentation for some info on the oddities of hierarchical clustering `_ .. csv-table:: genomeWide_compare.tsv cluster,sample,genome 1_1,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,fobin.fasta 1_1,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G2.sorted.bam,fobin.fasta 2_1,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,maxbin2.maxbin.001.fasta 2_2,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G2.sorted.bam,maxbin2.maxbin.001.fasta cluster The strain identity of this genome in this sample. Each "strain" assigned by the hierarchical clustering algorithm will have a unique cluster. In the example table above strains of the genome ``fobin.fasta`` are the same in both samples (they have the same "cluster" identities), but strains of the genome ``maxbin2.maxbin.001.fasta`` are different in the two samples (they have different "cluster" identities). sample The sample that the genome was detected in. genome The genome that the cluster is referring to. pooled_SNV_info.tsv, pooled_SNV_data.tsv, and pooled_SNV_data_keys.tsv +++++++++++++++++++++++++++ The tables `pooled_SNV_info.tsv`, `pooled_SNV_data.tsv`, and `pooled_SNV_data_keys.tsv` can be generated by inStrain compare by providing .bam files to the inStrain compare command. See :doc:`user_manual` for more information. .. csv-table:: pooled_SNV_info.tsv scaffold,position,depth,A,C,T,G,ref_base,con_base,var_base,sample_detections,sample_5x_detections,DivergentSite_count,SNS_count,SNV_count,con_SNV_count,pop_SNV_count,sample_con_bases N5_271_010G1_scaffold_114,3,10,2,0,7,1,T,T,A,2,1,0,0,1,0,0,['T'] N5_271_010G1_scaffold_114,20,33,0,31,2,0,C,C,T,2,2,0,0,1,0,0,['C'] N5_271_010G1_scaffold_114,24,35,29,0,2,4,A,A,G,2,2,0,0,2,0,0,['A'] N5_271_010G1_scaffold_114,25,38,2,36,0,0,C,C,A,2,2,0,0,1,0,0,['C'] N5_271_010G1_scaffold_114,55,71,66,5,0,0,A,A,C,2,2,0,0,1,0,0,['A'] N5_271_010G1_scaffold_114,57,67,2,0,0,65,G,G,A,2,2,0,0,1,0,0,['G'] N5_271_010G1_scaffold_114,75,95,4,90,0,1,C,C,A,2,2,0,0,1,0,0,['C'] N5_271_010G1_scaffold_114,76,95,0,90,2,3,C,C,G,2,2,0,0,2,0,0,['C'] N5_271_010G1_scaffold_114,79,98,0,3,0,95,G,G,C,2,2,0,0,1,0,0,['G'] This table has information about each SNV, summarized across all samples scaffold The scaffold being analyzed position The position in the scaffold where the SNV is located (0-based) depth The total number of reads mapping to this scaffold across samples A The number of reads with `A` at this position in this scaffold across samples C The number of reads with `C` at this position in this scaffold across samples T The number of reads with `T` at this position in this scaffold across samples G The number of reads with `G` at this position in this scaffold across samples ref_base The reference base at this position in this scaffold across samples con_base The consensus base (most common) at this position in this scaffold across samples var_base The variant base (second most common) at this position in this scaffold across samples sample_detections The number of samples in which this position at this scaffold has at least one read mapping to it sample_5x_detections The number of samples in which this position at this scaffold has at least 5 reads mapping to it DivergentSite_count The number of samples with a :term:`divergent sites` detected at this position SNS_count The number of samples with a :term:`SNSs` detected at this position SNV_count The number of samples with a :term:`SNVs` detected at this position con_SNV_count The number of samples with consenus SNPs (:term:`conANI`) detected at this position pop_SNV_count The number of samples with population SNPs (:term:`popANI`) detected at this position sample_con_bases The number of different consensus bases at this position across all analyzed samples .. csv-table:: pooled_SNV_data.tsv sample,scaffold,position,A,C,T,G 0,0,3,2,0,5,1 0,0,20,0,21,2,0 0,0,24,21,0,0,4 0,0,25,2,26,0,0 0,0,55,38,5,0,0 0,0,57,2,0,0,38 0,0,75,3,55,0,0 0,0,76,0,56,0,3 0,0,79,0,1,0,57 This table has information about each SNV in each sample. Because the table can be huge, names of scaffolds and samples are listed as "keys" to be translated using the also-provided `pooled_SNV_data_keys.tsv` table sample The key for the sample being analyzed (as detailed in the `pooled_SNV_data_keys.tsv` table below) scaffold The key for the scaffold being analyzed (as detailed in the `pooled_SNV_data_keys.tsv` table below) position The position in the scaffold where the SNV is located (0-based) A,C,T,G The number of reads with this base in this sample in this scaffold at this position .. csv-table:: pooled_SNV_data_keys.tsv key,sample,scaffold 0,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G1.sorted.bam,N5_271_010G1_scaffold_114 1,N5_271_010G1_scaffold_min1000.fa-vs-N5_271_010G2.sorted.bam,N5_271_010G1_scaffold_63 2,,N5_271_010G1_scaffold_89 3,,N5_271_010G1_scaffold_33 4,,N5_271_010G1_scaffold_95 5,,N5_271_010G1_scaffold_11 6,,N5_271_010G1_scaffold_74 7,,N5_271_010G1_scaffold_71 8,,N5_271_010G1_scaffold_96 This table has "keys" needed to translate the `pooled_SNV_data.tsv` table key The key in question. This is the number presented in the `sample` or `scaffold` column in the `pooled_SNV_data.tsv` table above sample The name of the sample with this key. For example: for the row with a `0` as the `key`, sample `0` in `pooled_SNV_data.tsv` refers to the sample listed here scaffold The name of the scaffold with this key. For example: for the row with a `0` as the `key`, scaffold `0` in `pooled_SNV_data.tsv` refers to the sample listed here inStrain plot ---------------- This is what the results of inStrain plot look like. 1) Coverage and breadth vs. read mismatches ++++++++++++++++++++++++++++++++++++++++++++++++ .. figure:: images/ExampleIS_plots/Example1.png :width: 800px :align: center 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 ++++++++++++++++++++++++++++++++++++++++++++++++ .. figure:: images/ExampleIS_plots/genomeWide_microdiveristy_metrics_1.png :width: 800px :align: center .. figure:: images/ExampleIS_plots/genomeWide_microdiveristy_metrics_2.png :width: 800px :align: center 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 ++++++++++++++++++++++++++++++++++++++++++++++++ .. figure:: images/ExampleIS_plots/readANI_distribution.png :width: 800px :align: center 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 ++++++++++++++++++++++++++++++++++++++++++++++++ .. figure:: images/ExampleIS_plots/MajorAllele_frequency_plot.png :width: 800px :align: center 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 ++++++++++++++++++++++++++++++++++++++++++++++++ .. figure:: images/ExampleIS_plots/LinkageDecay_plot.png :width: 800px :align: center .. figure:: images/ExampleIS_plots/Example5.png :width: 800px :align: center 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 ++++++++++++++++++++++++++++++++++++++++++++++++ .. figure:: images/ExampleIS_plots/ReadFiltering_plot.png :width: 800px :align: center 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) ++++++++++++++++++++++++++++++++++++++++++++++++ .. figure:: images/ExampleIS_plots/ScaffoldInspection_plot.png :width: 800px :align: center 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) ++++++++++++++++++++++++++++++++++++++++++++++++ .. figure:: images/ExampleIS_plots/LinkageDecay_types_plot.png :width: 800px :align: center Linkage plot for pairs of non-synonymous SNPs and all pairs of SNPs 9) Gene histograms (GENES REQUIRED) ++++++++++++++++++++++++++++++++++++++++++++++++ .. figure:: images/ExampleIS_plots/GeneHistogram_plot.png :width: 800px :align: center Histogram of values for all genes profiled 10) Compare dendrograms (RUN ON COMPARE; NOT PROFILE) ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ .. figure:: images/ExampleIS_plots/Example10.png :width: 800px :align: center A dendrogram comparing all samples based on popANI and based on shared_bases.