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publicDec 2025View details →

Data from: Estimating waterfowl breeding pair and brood densities using distance sampling with uncrewed aerial systems

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publicJul 2023View details →

Sample extraction and SNP sequencing data for: Identification of sex-linked SNP markers in wild populations of monomorphic birds

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Data from: Standardising fossil disparity metrics using sample coverage

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Data from: Assessing error upon sampling bagged animal feed

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edi36/100

Urban Forest Effects Model (UFORE) to calculate forest structure and function from sample ground data. Two part set.

Within the City of Baltimore, 195 permanent 1/10 circular plots were established based on a stratified random sample among land uses in 1999. These plots were re-measured in 2004 and 2009 and will be re-measured again in 2014. On each plot, all trees (as defined as woody vegetation with a stem diameter at 4.5 ft (dbh) greater than one-inch) are recorded. For each tree, data are recorded on species, dbh, height, crown width, condition, crown competition, percent canopy missing and distance and direction to nearby residential buildings. These data are analyzed using the i-Tree model (www.itreetools.org) to assess ecosystem services and values. However, more importantly, these plots along with a comparable set of plots established in Syracuse, NY in 1999 are the first and most spatially comprehensive set of long-term urban forest monitoring data within cities globally. These data are being used to understand how urban forest structure and associated ecosystem services are changing through time in the City of Baltimore.

openCustomJan 2018View details →

edi36/100

US-Hungary Grassland Biodiversity (cross-site project): 4x4 m Sample Plot Data (1996-1997)

Plant cover estimates were collected from Bouteloua grasslands at 3 different LTER (SGS, SEV, JRN) sites in summer of 1996/1997. The purpose of the data collection was to compare species composition and diversity between LTER sites and sandy grassland sites in Hungary.

openOpenSep 2010View details →

opennotspecifiedJan 2020View details →

A dash indicates that data were not taken for that sample. a in Isolation of an archaeon at the prokaryote eukaryote interface

A dash indicates that data were not taken for that sample. a The iTAG analysis was performed for samples in which an increase of about 10 times or more in 16S rRNA gene copy numbers of MK-D1 was observed after incubation;data were analysed by qPCR assay.Detailed results are shown in Supplementary Table 1. b Final concentration of casamino acids was 0.05% (w/v). c Final concentration of each amino acid was 0.1 mM. d Powdered milk for baby (Hohoemi, Meiji) was used at a final concentration of 0.1% (w/v). e The concentration of hydrogen gas was in the head space of the culture bottle. f2-BES was added to inhibit methanogens. g Addition of nitrate completely suppressed the growth of MK-D1.This is probably because nitrate inhibits formate dehydrogenase activity of MK-D1 95. h Archaeal cell membrane components were a mixture of phytol,intact polar lipid–glycerol-dialkyl-glycerol tetraethers and core lipid– glycerol-dialkyl-glycerol tetraethers (each at a final concentration 50 ng ml −1). We used the archaeal membrane components as these have a positive effect on the growth of some archaeal species:(i) archaeal cell extract including membrane lipids stimulates the growth of the extremely thermophilic archaeon Thermocaldium modestius 96, and (ii) the hyperthermophilic archaeon Thermofilum pendes requires the polar lipids for growth,which was obtained from the archaeal species Thermoproteus tenax 97.

mOTUs 1.1 taxonomic profiling of the CAMI 2 Mouse Gut Toy data set, samples 0-63

Software: mOTUs SoftwareVersion: 1.1 DataURL: https://data.cami-challenge.org/participate SoftwareURL: http://www.bork.embl.de/software/mOTUs1/ DockerImage: stefanjanssen/docker_profiling_tools:motu IsBiobox: True BioboxYAMLFile: https://zenodo.org/record/3629567/files/biobox.yaml?download=1 ReferenceDatabase: mOTU.v1.padded ShortReadsUsed: True LongReadsUsed: False CommandsUsed: docker run \ --volume="/path/to/19122017_mousegut_scaffolds_yaml:/bbx/mnt/yaml:ro" \ --volume="/path/to/19122017_mousegut_scaffolds:/bbx/mnt/input:ro" \ --volume="/path/to/output:/bbx/mnt/output:rw" \ --volume="/path/to/output/metadata:/bbx/metadata:rw" \ --volume="/path/to/output/cache:/cache:rw" \ stefanjanssen/docker_profiling_tools:motu

FOCUS 0.31 taxonomic profiling of the CAMI 2 Mouse Gut Toy data set, samples 0-63

Software: FOCUS SoftwareVersion: 0.31 DataURL: https://data.cami-challenge.org/participate SoftwareURL: https://github.com/metageni/FOCUS DockerImage: stefanjanssen/docker_profiling_tools:focus IsBiobox: True BioboxYAMLFile: https://zenodo.org/record/3629567/files/biobox.yaml?download=1 ReferenceDatabase: k8_bacterial_and_draft ShortReadsUsed: True LongReadsUsed: False CommandsUsed: docker run \ --volume="/path/to/19122017_mousegut_scaffolds_yaml:/bbx/mnt/yaml:ro" \ --volume="/path/to/19122017_mousegut_scaffolds:/bbx/mnt/input:ro" \ --volume="/path/to/output:/bbx/mnt/output:rw" \ --volume="/path/to/output/metadata:/bbx/metadata:rw" \ --volume="/path/to/output/cache:/cache:rw" \ stefanjanssen/docker_profiling_tools:focus

MetaPhlAn 2.9.21 taxonomic profiling of the CAMI 2 Mouse Gut Toy data set, samples 0-63

Software: MetaPhlAn SoftwareVersion: 2.9.21 DataURL: https://data.cami-challenge.org/participate SoftwareURL: https://bitbucket.org/biobakery/metaphlan2 DockerImage: cami/metaphlan:2.9.21 IsBiobox: True BioboxYAMLFile: https://zenodo.org/record/3629567/files/biobox.yaml?download=1 ReferenceDatabase: mpa_v29_CHOCOPhlAn_201901 ShortReadsUsed: True LongReadsUsed: False CommandsUsed: docker run \ --volume="/path/to/19122017_mousegut_scaffolds_yaml:/bbx/mnt/yaml:ro" \ --volume="/path/to/19122017_mousegut_scaffolds:/bbx/mnt/input:ro" \ --volume="/path/to/output:/bbx/mnt/output:rw" \ --volume="/path/to/output/metadata:/bbx/metadata:rw" \ --volume="/path/to/output/cache:/cache:rw" \ --volume="/path/to/reference_database:/exchange/db:rw" \ cami/metaphlan:2.9.21

MetaPhlAn 2.2.0 taxonomic profiling of the CAMI 2 Mouse Gut Toy data set, samples 0-63

Software: MetaPhlAn SoftwareVersion: 2.2.0 DataURL: https://data.cami-challenge.org/participate SoftwareURL: https://bitbucket.org/biobakery/metaphlan2 DockerImage: stefanjanssen/docker_profiling_tools:metaphlan2 IsBiobox: True BioboxYAMLFile: https://zenodo.org/record/3629567/files/biobox.yaml?download=1 ReferenceDatabase: mpa_v20_m200 ShortReadsUsed: True LongReadsUsed: False CommandsUsed: docker run \ --volume="/path/to/19122017_mousegut_scaffolds_yaml:/bbx/mnt/yaml:ro" \ --volume="/path/to/19122017_mousegut_scaffolds:/bbx/mnt/input:ro" \ --volume="/path/to/output:/bbx/mnt/output:rw" \ --volume="/path/to/output/metadata:/bbx/metadata:rw" \ --volume="/path/to/output/cache:/cache:rw" \ stefanjanssen/docker_profiling_tools:metaphlan2

CAMIARKQuikr 1.0.0 taxonomic profiling of the CAMI 2 Mouse Gut Toy data set, samples 0-63

Software: CAMIARKQuikr SoftwareVersion: 1.0.0 DataURL: https://data.cami-challenge.org/participate SoftwareURL: https://doi.org/10.5281/zenodo.1730572 DockerImage: stefanjanssen/docker_profiling_tools:quickr IsBiobox: True BioboxYAMLFile: https://zenodo.org/record/3629567/files/biobox.yaml?download=1 ReferenceDatabase: https://doi.org/10.5281/zenodo.1730572 ShortReadsUsed: True LongReadsUsed: False CommandsUsed: docker run \ --volume="/path/to/19122017_mousegut_scaffolds_yaml:/bbx/mnt/yaml:ro" \ --volume="/path/to/19122017_mousegut_scaffolds:/bbx/mnt/input:ro" \ --volume="/path/to/output:/bbx/mnt/output:rw" \ --volume="/path/to/output/metadata:/bbx/metadata:rw" \ --volume="/path/to/output/cache:/cache:rw" \ stefanjanssen/docker_profiling_tools:quickr

DAS Tool 1.1.2 genome binning of the CAMI 2 Mouse Gut Toy data set, samples 0-63, gold standard pooled assembly

Genome binning of the gold standard pooled assembly. Refinement of the binning output of MaxBin 2.2.7, MetaBAT 2.12.1, CONCOCT 1.0.0, and DAS Tool 1.1.2. Software: DAS Tool SoftwareVersion: 1.1.2 DataURL: https://data.cami-challenge.org/participate SoftwareURL: https://github.com/cmks/DAS_Tool DockerImage: cami/das_tool:1.1.2 IsBiobox: No ShortReadsUsed: True LongReadsUsed: False CommandUsed: DAS_Tool -i binning_concoct1.0.0,binning_maxbin2.2.7,binning_metabat2.12.1 -c anonymous_gsa_pooled.fasta -o output --search_engine diamond

CONCOCT 1.0.0 genome binning of the CAMI 2 Mouse Gut Toy data set, samples 0-63, gold standard pooled assembly

Genome binning of the gold standard pooled assembly Software: CONCOCT SoftwareVersion: 1.0.0 DataURL: https://data.cami-challenge.org/participate SoftwareURL: https://github.com/BinPro/CONCOCT DockerImage: quay.io/biocontainers/concoct:1.0.0--py37h88e4a8a_5 IsBiobox: No ShortReadsUsed: True LongReadsUsed: False CommandUsed: for i in {0..63}; do bowtie2 -q --threads 30 --fr -x anonymous_gsa_pooled.fasta --interleaved sample_${i}/anonymous_reads.fq -S anonymous_reads_sample_${i}.sam ; done for i in {0..63}; do samtools view -b sample_${i}.sam -o anonymous_reads_sample_${i}.bam & done for i in {0..63}; do samtools sort anonymous_reads_sample_${i}.bam -o anonymous_reads_sample_${i}.sorted.bam ; done for i in {0..63}; do samtools index anonymous_reads_sample_${i}.sorted.bam ; done cut_up_fasta.py anonymous_gsa_pooled.fasta -c 10000 -o 0 --merge_last -b contigs_10K.bed > contigs_10K.fa concoct_coverage_table.py contigs_10K.bed /host/benchmarking/fmeyer/output/bowtie2/mouse_gut/sorted_bam/anonymous_reads_sample_*.sorted.bam > coverage_table.tsv concoct --composition_file contigs_10K.fa --coverage_file coverage_table.tsv -b merge_cutup_clustering.py clustering_gt1000.csv > clustering_merged.csv

MetaPhyler 1.25 taxonomic profiling of the CAMI 2 Mouse Gut Toy data set, samples 0-63

Software: MetaPhyler SoftwareVersion: 1.25 DataURL: https://data.cami-challenge.org/participate SoftwareURL: http://metaphyler.cbcb.umd.edu/ DockerImage: stefanjanssen/docker_profiling_tools:metaphyler IsBiobox: True BioboxYAMLFile: https://zenodo.org/record/3629567/files/biobox.yaml?download=1 ReferenceDatabase: 2012 ShortReadsUsed: True LongReadsUsed: False CommandsUsed: docker run \ --volume="/path/to/19122017_mousegut_scaffolds_yaml:/bbx/mnt/yaml:ro" \ --volume="/path/to/19122017_mousegut_scaffolds:/bbx/mnt/input:ro" \ --volume="/path/to/output:/bbx/mnt/output:rw" \ --volume="/path/to/output/metadata:/bbx/metadata:rw" \ --volume="/path/to/output/cache:/cache:rw" \ stefanjanssen/docker_profiling_tools:metaphyler

mOTUs 2.5.1 taxonomic profiling of the CAMI 2 Mouse Gut Toy data set, samples 0-63

Software: mOTUs SoftwareVersion: 2.5.1 DataURL: https://data.cami-challenge.org/participate SoftwareURL: https://motu-tool.org/ DockerImage: cami/motus:2.5.1 IsBiobox: False ReferenceDatabase: mOTUs database version 2.5.0 ShortReadsUsed: True LongReadsUsed: False CommandsUsed: for i in {0..63}; do motus profile -f sample_$((i))/reads/anonymous_reads_r1.fq -r sample_$((i))/reads/anonymous_reads_r2.fq -n $((i)) -C precision > sample$((i)).profile ; done cat sample*.profile > cami2_mouse_gut_motus2.5.1.profile

MaxBin 2.2.7 genome binning of the CAMI 2 Mouse Gut Toy data set, samples 0-63, gold standard pooled assembly

Genome binning of the gold standard pooled assembly Software: MaxBin SoftwareVersion: 2.2.7 DataURL: https://data.cami-challenge.org/participate SoftwareURL: https://sourceforge.net/projects/maxbin/ DockerImage: cami/maxbin:2.2.7 IsBiobox: No ShortReadsUsed: True LongReadsUsed: False CommandUsed: run_MaxBin.pl -thread 16 -contig anonymous_gsa_pooled.fasta -out output -reads sample_0/reads/anonymous_reads.fq -reads2 sample_1/reads/anonymous_reads.fq -reads3 sample_2/reads/anonymous_reads.fq -reads4 sample_3/reads/anonymous_reads.fq -reads5 sample_4/reads/anonymous_reads.fq -reads6 sample_5/reads/anonymous_reads.fq -reads7 sample_6/reads/anonymous_reads.fq -reads8 sample_7/reads/anonymous_reads.fq -reads9 sample_8/reads/anonymous_reads.fq -reads10 sample_9/reads/anonymous_reads.fq -reads11 sample_10/reads/anonymous_reads.fq -reads12 sample_11/reads/anonymous_reads.fq -reads13 sample_12/reads/anonymous_reads.fq -reads14 sample_13/reads/anonymous_reads.fq -reads15 sample_14/reads/anonymous_reads.fq -reads16 sample_15/reads/anonymous_reads.fq -reads17 sample_16/reads/anonymous_reads.fq -reads18 sample_17/reads/anonymous_reads.fq -reads19 sample_18/reads/anonymous_reads.fq -reads20 sample_19/reads/anonymous_reads.fq -reads21 sample_20/reads/anonymous_reads.fq -reads22 sample_21/reads/anonymous_reads.fq -reads23 sample_22/reads/anonymous_reads.fq -reads24 sample_23/reads/anonymous_reads.fq -reads25 sample_24/reads/anonymous_reads.fq -reads26 sample_25/reads/anonymous_reads.fq -reads27 sample_26/reads/anonymous_reads.fq -reads28 sample_27/reads/anonymous_reads.fq -reads29 sample_28/reads/anonymous_reads.fq -reads30 sample_29/reads/anonymous_reads.fq -reads31 sample_30/reads/anonymous_reads.fq -reads32 sample_31/reads/anonymous_reads.fq -reads33 sample_32/reads/anonymous_reads.fq -reads34 sample_33/reads/anonymous_reads.fq -reads35 sample_34/reads/anonymous_reads.fq -reads36 sample_35/reads/anonymous_reads.fq -reads37 sample_36/reads/anonymous_reads.fq -reads38 sample_37/reads/anonymous_reads.fq -reads39 sample_38/reads/anonymous_reads.fq -reads40 sample_39/reads/anonymous_reads.fq -reads41 sample_40/reads/anonymous_reads.fq -reads42 sample_41/reads/anonymous_reads.fq -reads43 sample_42/reads/anonymous_reads.fq -reads44 sample_43/reads/anonymous_reads.fq -reads45 sample_44/reads/anonymous_reads.fq -reads46 sample_45/reads/anonymous_reads.fq -reads47 sample_46/reads/anonymous_reads.fq -reads48 sample_47/reads/anonymous_reads.fq -reads49 sample_48/reads/anonymous_reads.fq -reads50 sample_49/reads/anonymous_reads.fq -reads51 sample_50/reads/anonymous_reads.fq -reads52 sample_51/reads/anonymous_reads.fq -reads53 sample_52/reads/anonymous_reads.fq -reads54 sample_53/reads/anonymous_reads.fq -reads55 sample_54/reads/anonymous_reads.fq -reads56 sample_55/reads/anonymous_reads.fq -reads57 sample_56/reads/anonymous_reads.fq -reads58 sample_57/reads/anonymous_reads.fq -reads59 sample_58/reads/anonymous_reads.fq -reads60 sample_59/reads/anonymous_reads.fq -reads61 sample_60/reads/anonymous_reads.fq -reads62 sample_61/reads/anonymous_reads.fq -reads63 sample_62/reads/anonymous_reads.fq -reads64 sample_63/reads/anonymous_reads.fq

opencc-by-4.0Feb 2020View details →

MEGAHIT 1.0.3, 1.1.3, 1.2.9 assembly of the CAMI 2 Mouse Gut Toy data set, samples 0-9, short reads

Assembly of the first 10 short read samples with different MEGAHIT versions and parameters Software: MEGAHIT SoftwareVersion: 1.0.3, 1.1.3, 1.2.9 DataURL: https://data.cami-challenge.org/participate SoftwareURL: https://github.com/voutcn/megahit ShortReadsUsed: True LongReadsUsed: False CommandUsed: # install bioconda and run: conda create -n megahit103 megahit=1.0.3 conda create -n megahit113 megahit=1.1.3 conda create -n megahit129 megahit=1.2.9 Sample0=/path/to/19122017_mousegut_scaffolds/2017.12.29_11.37.26_sample_0/reads/anonymous_reads.fq.gz Sample1=/path/to/19122017_mousegut_scaffolds/2017.12.29_11.37.26_sample_1/reads/anonymous_reads.fq.gz Sample2=/path/to/19122017_mousegut_scaffolds/2017.12.29_11.37.26_sample_2/reads/anonymous_reads.fq.gz Sample3=/path/to/19122017_mousegut_scaffolds/2017.12.29_11.37.26_sample_3/reads/anonymous_reads.fq.gz Sample4=/path/to/19122017_mousegut_scaffolds/2017.12.29_11.37.26_sample_4/reads/anonymous_reads.fq.gz Sample5=/path/to/19122017_mousegut_scaffolds/2017.12.29_11.37.26_sample_5/reads/anonymous_reads.fq.gz Sample6=/path/to/19122017_mousegut_scaffolds/2017.12.29_11.37.26_sample_6/reads/anonymous_reads.fq.gz Sample7=/path/to/19122017_mousegut_scaffolds/2017.12.29_11.37.26_sample_7/reads/anonymous_reads.fq.gz Sample8=/path/to/19122017_mousegut_scaffolds/2017.12.29_11.37.26_sample_8/reads/anonymous_reads.fq.gz Sample9=/path/to/19122017_mousegut_scaffolds/2017.12.29_11.37.26_sample_9/reads/anonymous_reads.fq.gz conda activate megahit103 /usr/bin/time -v megahit -t 48 \ --12 $Sample0 --12 $Sample1 --12 $Sample2 --12 $Sample3 --12 $Sample4 --12 $Sample5 --12 $Sample6 --12 $Sample7 --12 $Sample8 --12 $Sample9 \ -o megahit103-Sample0-9-sLibs-default conda activate megahit113 /usr/bin/time -v megahit -t 48 \ --12 $Sample0 --12 $Sample1 --12 $Sample2 --12 $Sample3 --12 $Sample4 --12 $Sample5 --12 $Sample6 --12 $Sample7 --12 $Sample8 --12 $Sample9 \ -o megahit113-Sample0-9-sLibs-default /usr/bin/time -v megahit -t 48 --presets meta-sensitive \ --12 $Sample0 --12 $Sample1 --12 $Sample2 --12 $Sample3 --12 $Sample4 --12 $Sample5 --12 $Sample6 --12 $Sample7 --12 $Sample8 --12 $Sample9 \ -o megahit113-Sample0-9-sLibs-meta-sensitive /usr/bin/time -v megahit -t 48 --presets meta-large \ --12 $Sample0 --12 $Sample1 --12 $Sample2 --12 $Sample3 --12 $Sample4 --12 $Sample5 --12 $Sample6 --12 $Sample7 --12 $Sample8 --12 $Sample9 \ -o megahit113-Sample0-9-sLibs-meta-large conda activate megahit129 /usr/bin/time -v megahit -t 48 \ --12 $Sample0 --12 $Sample1 --12 $Sample2 --12 $Sample3 --12 $Sample4 --12 $Sample5 --12 $Sample6 --12 $Sample7 --12 $Sample8 --12 $Sample9 \ -o megahit129-Sample0-9-sLibs-default