ampliconflow

opens the authoritative record at ENA, SRA or BioSample; this page never replaces it

PRJEB3386 released 25 Sept 2026

PRJEB3386

Pipeline 0.1.0 Contract v0.1 Licence CC-BY-4.0

Tags

derived from the release metadata, not hand-written

Study

The study record carries no description, and its registered title is the accession itself. The figures below are computed from the 22 released samples and 22 runs.

Samples
22
Runs
22
Collection
2011-06 to 2011-06

Linked publication

Effect of metal oxide nanoparticles on microbial community structure and function in two different soil types.

10.1371/journal.pone.0084441 · 2013 · via europepmc

Linked by the enrich stage. Fields taken from the paper: primers.

abstract

Increased availability of nanoparticle-based products will, inevitably, expose the environment to these materials. Engineered nanoparticles (ENPs) may thus find their way into the soil environment via wastewater, dumpsters and other anthropogenic sources; metallic oxide nanoparticles comprise one group of ENPs that could potentially be hazardous for the environment. Because the soil bacterial community is a major service provider for the ecosystem and humankind, it is critical to study the effects of ENP exposure on soil bacteria. These effects were evaluated by measuring bacterial community activity, composition and size following exposure to copper oxide (CuO) and magnetite (Fe3O4) nanosized (<50 nm) particles. Two different soil types were examined: a sandy loam (Bet-Dagan) and a sandy clay loam (Yatir), under two ENP concentrations (1%, 0.1%). Results indicate that the bacterial community in Bet-Dagan soil was more susceptible to change due to exposure to these ENPs, relative to Yatir soil. More specifically, CuO had a strong effect on bacterial hydrolytic activity, oxidative potential, community composition and size in Bet-Dagan soil. Few effects were noted in the Yatir soil, although 1% CuO exposure did cause a significant decreased oxidative potential and changes to community composition. Fe3O4 changed the hydrolytic activity and bacterial community composition in Bet-Dagan soil but did not affect the Yatir soil bacterial community. Furthermore, in Bet-Dagan soil, abundance of bacteria annotated to OTUs from the Bacilli class decreased after addition of 0.1% CuO but increased with 1% CuO, while in Yatir soil their abundance was reduced with 1% CuO. Other important soil bacterial groups, including Rhizobiales and Sphingobacteriaceae, were negatively affected by CuO addition to soil. These results indicate that both ENPs are potentially harmful to soil environments. Furthermore, it is suggested that the clay fraction and organic matter in different soils interact with the ENPs and reduce their toxicity.

Linked by the enrich stage from europepmc.

Location

sampling sites from the release coordinates
22sampling sites · drag to pan, scroll or pinch to zoom

Place name hierarchy

  1. ▸ ישראל
  2. › מחוז המרכז

Latitude 31.98333 to 31.98333, longitude 34.81667 to 34.81667. Names resolved with OpenStreetMap Nominatim from the release's own coordinates; Coordinates parsed from the released lat_lon text field, which the pipeline keeps but does not split into latitude/longitude columns.

How the sequences were obtained

sample to release
01 study metadata

Sample collection

22 samples, 2011-06 to 2011-06

31.9833 to 31.9833 N, 34.8167 to 34.8167 E

02 not reported

Storage

not reported

neither the archive nor the linked paper states storage conditions

03 not reported

Processing

not reported

no extraction kit or lysis protocol in the archive or the linked paper

04 per-run QC and the linked paper

PCR

16S rRNA V4, primers 1100R, 530F, 907R

primers: present

05 not reported

Sequencing preparation

not reported

no library kit or index strategy in the archive or the linked paper

06 study metadata

Sequencing

454 GS FLX

22 runs; SINGLE 356.4545 bp reads; the linked paper's text supports 454

07 this release

Denoising

dada2 1.38.0

2,846 ASVs from 31,500 reads

ampliconflow branches off at step 6, Sequencing

this release

ampliconflow starts here: 31,500 reads from 22 runs, QC to 89.2% 16S identity and 65.3% above Q30, primers trimmed, dada2 1.38.0 to 2,846 ASVs, taxonomy against a SINTAX reference, then the release (CC-BY-4.0).

Steps 1 to 6 are how the sequences were obtained, from the study's own archive metadata. Step 7 is what the authors report doing with the sequences in the linked paper. ampliconflow starts at the deposited reads rather than repeating the wet lab.

Taxonomy assigned with SILVA 138.2 (SINTAX).

The linked paper's methods run to 17,176 characters. It supports: platform, primers.

Conflict on sequencing platform: the release has 454 GS FLX, the linked paper's text supports 454.

22

Samples

22 runs

2.8k

Features

OTUs at 97%

65.9k

Reads

mapped total

135 MB

Release size

73 files

Depth floor

1,000 reads

no samples below

QC warnings

22

100% of runs warned

Reads per sample

log scale
min
1,132
median
2,417
max
6,700

Feature detection

100.0% non-zero

2,846 / 2,846 features

Features with at least one observed read. The remainder are present in the reference set but not detected in these samples.

Composition

Top phyla

  • Pseudomonadota 22,974 (34.9%)
  • Actinomycetota 11,795 (17.9%)
  • Bacillota 8,982 (13.6%)
  • Bacteroidota 7,363 (11.2%)
  • Gemmatimonadota 5,015 (7.6%)
  • Acidobacteriota 3,827 (5.8%)
  • Chloroflexota 2,182 (3.3%)
  • Myxococcota 1,163 (1.8%)
  • Verrucomicrobiota 740 (1.1%)
  • Armatimonadota 507 (0.8%)
  • Bdellovibrionota 403 (0.6%)
  • Planctomycetota 273 (0.4%)
  • Patescibacteria 201 (0.3%)
  • Cyanobacteriota 132 (0.2%)
  • Methylomirabilota 101 (0.2%)
  • Candidatus Kapabacteria 75 (0.1%)
  • Thermodesulfobacteriota 41 (0.1%)
  • Nitrospirota 18 (0.0%)
  • Latescibacterota 9 (0.0%)
  • MBNT15 8 (0.0%)

Top genera

  • Incertae Sedis 17,502 (26.6%)
  • Sphingomonas 3,397 (5.2%)
  • Massilia 2,767 (4.2%)
  • Microvirga 2,625 (4.0%)
  • Flavisolibacter 2,431 (3.7%)
  • Neobacillus 2,332 (3.5%)
  • Noviherbaspirillum 2,271 (3.4%)
  • Nocardioides 1,823 (2.8%)
  • Daejeonella 1,693 (2.6%)
  • Lysinibacillus 1,688 (2.6%)
  • Lysobacter 1,629 (2.5%)
  • Blastococcus 1,422 (2.2%)
  • Caenimonas 1,378 (2.1%)
  • Rubrobacter 1,068 (1.6%)
  • Bacillus 1,002 (1.5%)
  • Solirubrobacter 858 (1.3%)
  • Azohydromonas 819 (1.2%)
  • Pontibacter 791 (1.2%)
  • Mesobacillus 786 (1.2%)
  • Phenylobacterium 754 (1.1%)

Rank-abundance

log-log
1 10 100 1 10 100 16s-v4-v5:ASV_1 · Lysinibacillus: 809 reads 16s-v4:ASV_1 · Massilia: 410 reads 16s-v4-v5:ASV_2 · Neobacillus: 372 reads 16s-v4-v5:ASV_3 · Microvirga: 307 reads 16s-v4-v5:ASV_4 · Lysinibacillus: 256 reads 16s-v4:ASV_2 · Microvirga: 242 reads 16s-v4-v5:ASV_5 · Azohydromonas: 235 reads 16s-v4:ASV_3 · Daejeonella: 220 reads 16s-v4:ASV_4 · Pontibacter: 216 reads 16s-v5:ASV_1 · Neobacillus: 214 reads 16s-v4-v5:ASV_6 · Microvirga: 211 reads 16s-v4-v5:ASV_7 · Neobacillus: 206 reads 16s-v4-v5:ASV_8 · Bacillus: 206 reads 16s-v4-v5:ASV_9 · Neobacillus: 198 reads 16s-v4-v5:ASV_10 · Neobacillus: 188 reads 16s-v4-v5:ASV_11 · Daejeonella: 188 reads 16s-v4-v5:ASV_12 · Azohydromonas: 186 reads 16s-v4:ASV_5 · Sporosarcina: 176 reads 16s-v4:ASV_6 · Bacillus: 174 reads 16s-v4:ASV_7 · Neobacillus: 167 reads 16s-v4-v5:ASV_13 · Bacillus: 166 reads 16s-v5:ASV_2 · Lysinibacillus: 164 reads 16s-v4:ASV_8 · Neobacillus: 162 reads 16s-v4-v5:ASV_14 · Microvirga: 155 reads 16s-v4-v5:ASV_15 · Caenimonas: 155 reads 16s-v4-v5:ASV_16 · Neobacillus: 152 reads 16s-v4-v5:ASV_17 · Noviherbaspirillum: 150 reads 16s-v5:ASV_3 · Microvirga: 147 reads 16s-v4:ASV_9 · Massilia: 146 reads 16s-v4:ASV_10 · Massilia: 143 reads 16s-v4:ASV_11 · Nocardioides: 139 reads 16s-v4:ASV_12 · Noviherbaspirillum: 139 reads 16s-v4-v5:ASV_18 · Bacillus: 136 reads 16s-v4-v5:ASV_19 · Daejeonella: 136 reads 16s-v4-v5:ASV_20 · MND1: 134 reads 16s-v4:ASV_13 · Azohydromonas: 132 reads 16s-v4-v5:ASV_21 · Daejeonella: 131 reads 16s-v4-v5:ASV_22 · Caenimonas: 131 reads 16s-v4-v5:ASV_23 · Microvirga: 127 reads 16s-v4:ASV_14 · Massilia: 127 reads 16s-v4-v5:ASV_24 · Nocardioides: 126 reads 16s-v4:ASV_15 · Sphingomonas: 126 reads 16s-v4-v5:ASV_25 · Daejeonella: 123 reads 16s-v4-v5:ASV_26 · Noviherbaspirillum: 123 reads 16s-v4-v5:ASV_27 · Noviherbaspirillum: 122 reads 16s-v4-v5:ASV_28 · Rubellimicrobium: 122 reads 16s-v4:ASV_16 · Incertae Sedis: 122 reads 16s-v4-v5:ASV_29 · Noviherbaspirillum: 121 reads 16s-v4-v5:ASV_30 · Neobacillus: 116 reads 16s-v4-v5:ASV_31 · Incertae Sedis: 114 reads 16s-v4:ASV_17 · MND1: 114 reads 16s-v4-v5:ASV_32 · Nocardioides: 113 reads 16s-v4:ASV_18 · Massilia: 113 reads 16s-v4-v5:ASV_33 · Mesobacillus: 111 reads 16s-v4:ASV_19 · Lysinibacillus: 111 reads 16s-v4:ASV_20 · Neobacillus: 111 reads 16s-v4-v5:ASV_34 · Azohydromonas: 110 reads 16s-v4-v5:ASV_35 · Flavisolibacter: 110 reads 16s-v4:ASV_21 · Massilia: 110 reads 16s-v4-v5:ASV_36 · Flavisolibacter: 109 reads 16s-v4-v5:ASV_37 · Incertae Sedis: 109 reads 16s-v4-v5:ASV_38 · Flavisolibacter: 109 reads 16s-v4-v5:ASV_39 · Flavisolibacter: 107 reads 16s-v4:ASV_22 · Massilia: 107 reads 16s-v4:ASV_23 · Incertae Sedis: 107 reads 16s-v5:ASV_4 · Flavisolibacter: 107 reads 16s-v4:ASV_24 · Daejeonella: 106 reads 16s-v4-v5:ASV_40 · Incertae Sedis: 105 reads 16s-v4-v5:ASV_41 · Incertae Sedis: 103 reads 16s-v4:ASV_25 · Flavisolibacter: 102 reads 16s-v4:ASV_26 · Neobacillus: 102 reads 16s-v4-v5:ASV_42 · Incertae Sedis: 101 reads 16s-v4:ASV_27 · Massilia: 101 reads 16s-v4:ASV_28 · Caenimonas: 101 reads 16s-v4-v5:ASV_43 · Phenylobacterium: 100 reads 16s-v4-v5:ASV_44 · Nocardioides: 99 reads 16s-v4-v5:ASV_45 · Nocardioides: 99 reads 16s-v4:ASV_29 · Blastococcus: 98 reads 16s-v4:ASV_30 · Lysobacter: 97 reads 16s-v4:ASV_31 · Lysinibacillus: 96 reads 16s-v4:ASV_32 · YC-ZSS-LKJ147: 95 reads 16s-v4:ASV_33 · Phenylobacterium: 94 reads 16s-v4:ASV_34 · Massilia: 94 reads 16s-v4:ASV_35 · Incertae Sedis: 94 reads 16s-v4-v5:ASV_46 · Incertae Sedis: 93 reads 16s-v4-v5:ASV_47 · Microvirga: 93 reads 16s-v4:ASV_36 · Microvirga: 92 reads 16s-v4-v5:ASV_48 · Nocardioides: 91 reads 16s-v4-v5:ASV_49 · Microvirga: 91 reads 16s-v4:ASV_37 · Microvirga: 91 reads 16s-v4-v5:ASV_50 · Microvirga: 90 reads 16s-v4-v5:ASV_51 · Noviherbaspirillum: 90 reads 16s-v4:ASV_38 · Sphingomonas: 90 reads 16s-v4:ASV_39 · Solirubrobacter: 90 reads 16s-v4:ASV_40 · Noviherbaspirillum: 89 reads 16s-v4-v5:ASV_52 · Noviherbaspirillum: 88 reads 16s-v4:ASV_41 · Noviherbaspirillum: 88 reads 16s-v4:ASV_42 · Lysobacter: 88 reads 16s-v4-v5:ASV_53 · Nocardioides: 86 reads 16s-v4-v5:ASV_54 · Lysobacter: 86 reads 16s-v4-v5:ASV_55 · Sporosarcina: 85 reads 16s-v4:ASV_43 · Sphingomonas: 85 reads 16s-v4-v5:ASV_56 · Sphingomonas: 84 reads 16s-v4-v5:ASV_57 · Incertae Sedis: 84 reads 16s-v4:ASV_44 · Microvirga: 84 reads 16s-v4-v5:ASV_58 · Daejeonella: 83 reads 16s-v4-v5:ASV_59 · Arenimicrobium: 83 reads 16s-v4:ASV_45 · Sphingomonas: 83 reads 16s-v4:ASV_46 · Incertae Sedis: 83 reads 16s-v4-v5:ASV_60 · Rubrobacter: 82 reads 16s-v4-v5:ASV_61 · Daejeonella: 82 reads 16s-v4-v5:ASV_62 · Sphingomonas: 81 reads 16s-v4:ASV_47 · Sphingomonas: 81 reads 16s-v4:ASV_48 · Solirubrobacter: 81 reads 16s-v4-v5:ASV_63 · Pontibacter: 80 reads 16s-v4-v5:ASV_64 · Sphingomonas: 80 reads 16s-v4-v5:ASV_65 · Sphingomonas: 79 reads 16s-v4:ASV_49 · Sphingomonas: 79 reads 16s-v4:ASV_50 · Caenimonas: 79 reads 16s-v5:ASV_5 · Nocardioides: 79 reads 16s-v4-v5:ASV_66 · Incertae Sedis: 78 reads 16s-v4-v5:ASV_67 · Nocardioides: 78 reads 16s-v4:ASV_51 · Incertae Sedis: 78 reads 16s-v4:ASV_52 · Noviherbaspirillum: 78 reads 16s-v5:ASV_6 · Noviherbaspirillum: 77 reads 16s-v4-v5:ASV_68 · Incertae Sedis: 76 reads 16s-v4-v5:ASV_69 · Lysinibacillus: 76 reads 16s-v4-v5:ASV_70 · Microvirga: 76 reads 16s-v4:ASV_53 · Daejeonella: 76 reads 16s-v4:ASV_54 · MND1: 76 reads 16s-v4:ASV_55 · Phenylobacterium: 76 reads 16s-v4:ASV_56 · Noviherbaspirillum: 76 reads 16s-v5:ASV_7 · Incertae Sedis: 76 reads 16s-v4-v5:ASV_71 · Lysobacter: 75 reads 16s-v4-v5:ASV_72 · Blastococcus: 75 reads 16s-v4:ASV_57 · Flavisolibacter: 75 reads 16s-v4:ASV_58 · Noviherbaspirillum: 75 reads 16s-v5:ASV_8 · Daejeonella: 75 reads 16s-v4-v5:ASV_73 · Lysinibacillus: 74 reads 16s-v4:ASV_59 · Acidovorax: 74 reads 16s-v4:ASV_60 · Lysobacter: 74 reads 16s-v4:ASV_61 · Longimicrobium: 74 reads 16s-v4-v5:ASV_74 · Incertae Sedis: 73 reads 16s-v4-v5:ASV_75 · Sphingomonas: 73 reads 16s-v4-v5:ASV_76 · YC-ZSS-LKJ147: 73 reads 16s-v4-v5:ASV_77 · Flavisolibacter: 73 reads 16s-v4:ASV_62 · Microvirga: 73 reads 16s-v4:ASV_63 · Noviherbaspirillum: 73 reads 16s-v4:ASV_64 · Blastococcus: 73 reads 16s-v4-v5:ASV_78 · Flavisolibacter: 72 reads 16s-v4-v5:ASV_79 · Daejeonella: 72 reads 16s-v4-v5:ASV_80 · Lysobacter: 72 reads 16s-v4-v5:ASV_81 · Incertae Sedis: 72 reads 16s-v4:ASV_65 · Sphingomonas: 72 reads 16s-v4:ASV_66 · Sphingomonas: 72 reads 16s-v4-v5:ASV_82 · Incertae Sedis: 71 reads 16s-v4-v5:ASV_83 · Sphingomonas: 71 reads 16s-v4:ASV_67 · Sphingoaurantiacus: 71 reads 16s-v4:ASV_68 · Incertae Sedis: 71 reads 16s-v4-v5:ASV_84 · Flavisolibacter: 70 reads 16s-v4-v5:ASV_85 · Sphingomonas: 70 reads 16s-v4:ASV_69 · Nocardioides: 70 reads 16s-v4:ASV_70 · P3OB-42: 70 reads 16s-v4:ASV_71 · Flavisolibacter: 70 reads 16s-v4:ASV_72 · Caenimonas: 70 reads 16s-v4:ASV_73 · Sphingomonas: 70 reads 16s-v4-v5:ASV_86 · Longimicrobium: 69 reads 16s-v4:ASV_74 · Flavisolibacter: 69 reads 16s-v4:ASV_75 · Noviherbaspirillum: 69 reads 16s-v4-v5:ASV_87 · Massilia: 68 reads 16s-v4-v5:ASV_88 · Incertae Sedis: 68 reads 16s-v4:ASV_76 · Noviherbaspirillum: 68 reads 16s-v4-v5:ASV_89 · Microvirga: 67 reads 16s-v4:ASV_77 · Massilia: 67 reads 16s-v4:ASV_78 · Incertae Sedis: 67 reads 16s-v4:ASV_79 · Brevundimonas: 67 reads 16s-v4:ASV_80 · Incertae Sedis: 67 reads 16s-v4-v5:ASV_90 · Priestia: 66 reads 16s-v4-v5:ASV_91 · Streptomyces: 66 reads 16s-v4-v5:ASV_92 · Flavisolibacter: 66 reads 16s-v4:ASV_81 · Noviherbaspirillum: 66 reads 16s-v4:ASV_82 · Incertae Sedis: 66 reads 16s-v4-v5:ASV_93 · Incertae Sedis: 65 reads 16s-v4-v5:ASV_94 · Mesobacillus: 65 reads 16s-v4-v5:ASV_95 · Blastococcus: 65 reads 16s-v4:ASV_83 · Massilia: 65 reads 16s-v4-v5:ASV_96 · Blastococcus: 64 reads 16s-v4-v5:ASV_97 · Daejeonella: 64 reads 16s-v4-v5:ASV_98 · Sphingomonas: 64 reads 16s-v4:ASV_84 · Nocardioides: 64 reads 16s-v4:ASV_85 · Solirubrobacter: 64 reads 16s-v4:ASV_86 · Massilia: 64 reads 16s-v4-v5:ASV_100 · Incertae Sedis: 63 reads 16s-v4-v5:ASV_101 · Incertae Sedis: 63 reads 16s-v4-v5:ASV_102 · Massilia: 63 reads 16s-v4-v5:ASV_99 · Noviherbaspirillum: 63 reads 16s-v4:ASV_87 · Ellin6055: 63 reads 16s-v4:ASV_88 · Mesobacillus: 63 reads 16s-v4:ASV_89 · Mesobacillus: 62 reads 16s-v4:ASV_90 · Incertae Sedis: 62 reads rank reads

2,846 ranked features, top 200 shown. A steep drop means a few taxa carry most of the reads.

Per-sample reads

22 samples
min
1,132
median
2,417
max
6,700

Downstream QC and analysis

computed from the released tables

Eleven modules, computed from the released count table, the sample metadata and the per-run QC reports. Each panel states its own n and the test it used; a module that cannot run on this release is shown as a flagged gap rather than an empty frame.

Rarefaction

median with p10 to p90
2k 5k 209 0

Expected richness when 11 samples are subsampled to a common depth, resampled 31 draws. Median 36 features observed at full depth.

Depth against richness

log depth
222 0 reads per sample, log scale

One point per sample. Correlation of log reads with observed features is 0.913, so the depth floor is doing most of the work of deciding how many features a sample shows.

Per-run QC

  • 16S identity 89.2% alignment call per run
  • Q30 rate 65.3% mean Q 31
  • Amplicon V4 primers present
  • PhiX 0.0% control spike-in

22 run report(s), n/a GC, 0.0% ambiguous bases.

Diversity

Shannon
4.34
Simpson
0.983
Evenness
0.916
Chao1
118

Median across samples. Observed richness ranges 0 to 222.

Feature prevalence

0 of 2,846 features

present in at least half of the 22 samples (0.0%). 1,435 features appear in one sample only, which is the long tail rarefaction is fighting.

Ordination

pc1 pc2

One point per sample, 22 plotted. Choose the axes and the colour variable; hover a point for its sample id. The legend below the axes names the levels or the numeric range.

What explains each axis

pc1 · 37.6%

  • observed 77.0%
  • reads 61.2%
  • evenness 17.9%
  • chao1 7.3%

pc2 · 6.7%

  • evenness 17.9%
  • chao1 7.3%
  • reads 4.4%
  • shannon 2.0%

pc3 · 6.3%

  • evenness 20.3%
  • shannon 12.7%
  • chao1 8.0%
  • observed 1.8%

Categorical variables use eta-squared (between-group share of the axis), numeric ones the squared Pearson correlation. Computed from the released sample metadata.

Alpha diversity per sample

Shannon
5.0 11 samples

Median Shannon 4.344 across the release; observed richness runs 0 to 222.

Bray-Curtis dissimilarity

22 x 22, darker is closer

Sample order is the release order, 22 labels, and the matrix itself ships as beta_distance.tsv beside the analysis.

Phylogenetic diversity

Not available for this release: no Newick tree beside the table; run the tree stage, then re-run analyze. The legacy analysis computed Faith's PD when the container carried a tree, and this one reports the absence instead of an empty column.

Community states

CLR, k by silhouette

k = 2 silhouette 0.566

  • state 0 21 samples
  • state 1 1 samples

Clustered on the centred log-ratio of the top 200 features; 22 samples.

Batch-bias audit

states against

adjusted Rand n/a p = n/a

not enough levels to test

permutations. Every sample here carries both MiSeq and MiniSeq runs, so the batch variable used is the one with two levels, here .

Variance partitioning

mean R2 per feature, CLR

Joint R2 n/a, so the metadata explains a modest slice of the feature variation, and the two variables are not independent of one another.

Effect size

No two-level comparison available.

Taxa against all samples

with

features tested, 0 survive the correction at q ≤ 0.05

Nothing survives. The smallest q is n/a, which is the honest answer for a study whose samples are spread across three years with two to thirteen samples per year.

Group difference and spread

Bray-Curtis, 999 permutations
PERMANOVA pseudo-F
n/a · p n/a
PERMDISP F
n/a · p n/a
Distance decay (Mantel r)
n/a · p n/a

    The contamination class separates the communities beyond the spread within each class (PERMANOVA) with no evidence that the spread itself differs (PERMDISP). Distance decay runs over n/a to n/a km.

    Spatial structure

    observed richness over distance

    the study's coordinates fall on a single site (no spread), so spatial autocorrelation is not defined

    Co-occurrence network

    100 nodes · 506 edges

    positive
    506
    negative
    0
    density
    0.102
    components
    9
    mean degree
    10.1

    Spearman on log1p proportions, 100 features, |r| ≥ 0.50, FDR 0.05.

    Hubs by degree

      Phylogenetic and signal analyses need a tree

      no Newick tree beside the table; run the tree stage, then re-run analyze. The tree stage aligns the ASVs with MAFFT and builds with FastTree, both detected as external tools; neither is installed on the machine this page was built on, so Faith's PD, UniFrac, Pagel's lambda and Blomberg's K are left flagged rather than guessed.

      ASV phylogeny

      0 most abundant of the tree

      No tree in this release.

      ASV panel

      no sequence file

      The representative sequences are not in this release, so length and GC cannot be drawn.

      Most abundant ASVs

      ASVphylumgenusmeanprev.
      16s-v4:ASV_1PseudomonadotaMassilia18.65%
      16s-v4:ASV_2PseudomonadotaMicrovirga11.05%
      16s-v4:ASV_3BacteroidotaDaejeonella10.05%
      16s-v4:ASV_4BacteroidotaPontibacter9.85%
      16s-v4:ASV_5BacillotaSporosarcina8.05%
      16s-v4:ASV_6BacillotaBacillus7.95%
      16s-v4:ASV_7BacillotaNeobacillus7.65%
      16s-v4:ASV_8BacillotaNeobacillus7.45%
      16s-v4:ASV_9PseudomonadotaMassilia6.65%
      16s-v4:ASV_10PseudomonadotaMassilia6.55%
      16s-v4:ASV_11ActinomycetotaNocardioides6.35%
      16s-v4:ASV_12PseudomonadotaNoviherbaspirillum6.35%

      Similar studies

      composition, metadata, location, shared authors

      Ranked from the released tables: genus composition as Bray-Curtis similarity, shared environment and method terms, the distance between sample centroids, and authors shared with the linked publication.

      Missing or wrong data?

      Report a field that is empty or mistaken, or associate a paper with this study. No account is needed; the contact email is optional and used only to reply about this submission.

      Contribute to PRJEB3386

      Validated automatically where it can be, reviewed by a person where it cannot.

      Downloads

      14 files · sha256 in manifest

      Files are served from https://huggingface.co/datasets/hmacgregor/ampliconflow-releases/resolve/main/PRJEB3386-20260926/ once hosting is wired. Until then the links point at a placeholder base URL.

      Samples

      22 samples
      Sample Collected group Reads Features Shannon State
      SAMEA1712397 2011-06 0 0 0
      SAMEA1712399 2011-06 0 0 0
      SAMEA1712401 2011-06 1,243 79 4.003 0
      SAMEA1712403 2011-06 0 0 0
      SAMEA1712405 2011-06 6,700 215 4.804 1
      SAMEA1712407 2011-06 0 0 0
      SAMEA1712410 2011-06 0 0 0
      SAMEA1712412 2011-06 1,977 96 4.039 0
      SAMEA1712413 2011-06 0 0 0
      SAMEA1712415 2011-06 1,544 72 3.785 0
      SAMEA1712418 2011-06 0 0 0
      SAMEA1712420 2011-06 0 0 0
      SAMEA1712422 2011-06 0 0 0
      SAMEA1712424 2011-06 2,232 125 4.505 0
      SAMEA1712426 2011-06 0 0 0
      SAMEA1712428 2011-06 2,674 178 4.765 0
      SAMEA1712430 2011-06 1,507 81 4.029 0
      SAMEA1712432 2011-06 4,355 140 4.344 0
      SAMEA1712434 2011-06 2,264 115 4.399 0
      SAMEA1712436 2011-06 4,705 222 4.993 0
      SAMEA1712438 2011-06 0 0 0
      SAMEA1712440 2011-06 2,299 118 4.341 0

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