cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17044/scilifelab.22303531
title: Multimodal classification of molecular subtypes in pediatric acute lymphoblastic leukemia

description: This dataset contains genome-wide DNA methylation data generated from 384 pediatric acute lymphoblastic leukemia (ALL) samples originating from bone marrow or peripheral blood samples taken at ALL diagnosis (n = 384). Further details regarding the samples are available in Supplementary Table S2 from Krali et al., 2023 (https://doi.org/10.1038/s41698-023-00479-5).Genome-wide DNA methylation was analyzed at the SNP&SEQ Technology Platform, SciLifeLab, National Genomics Infrastructure Uppsala, Sweden. 250 ng of bisulfite converted DNA was amplified, fragmented and hybridised to Illumina Infinium Human Methylation450k Beadchip using the standard protocol from Illumina (iScan SQ instrument).This metadata record contains information about the raw idat files generated from the Infinium DNA methylation arrays. The raw idat files were processed with Methylation Module (1.8.5) software in Genome Studio (V2010.3). Peak-based correction was used to normalize the beta-value matrix.The raw idat files along with a samplesheet, processed beta-value matrix, annotation file for CpG annotation will be made available upon request. Limited phenotype information is available in the Supplemental Table S2 of the manuscript. All scripts that give a walk-through to our project, including the modelling process with Machine Learning can be found in our GitHub repository.Terms for accessThe DNA methylation dataset is only to be used for research that is seeking to advance the understanding of the influence of epigenetic factors on leukemia etiology and biology.The data should not be used for other purposes, i.e. investigating the epigenetic signatures that may lead to identification of a person.<br>For retrieving the data used for the scope of this publication, please contact datacentre@scilifelab.se.
DOI: 10.7483/opendata.cms.bp1z.txkt
title: /TprimeBToTH_TLep_Hbb_LH_MT3000_MH450_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.17044/scilifelab.22303531.v1
title: Multimodal classification of molecular subtypes in pediatric acute lymphoblastic leukemia

description: This dataset contains genome-wide DNA methylation data generated from 384 pediatric acute lymphoblastic leukemia (ALL) samples originating from bone marrow or peripheral blood samples taken at ALL diagnosis (n = 384). Further details regarding the samples are available in Supplementary Table S2 from Krali et al., 2023 (DOI to publication when available). 
Genome-wide DNA methylation was analyzed at the SNP&SEQ Technology Platform, SciLifeLab, National Genomics Infrastructure Uppsala, Sweden. 250 ng of bisulfite converted DNA was amplified, fragmented and hybridised to Illumina Infinium Human Methylation450k Beadchip using the standard protocol from Illumina (iScan SQ instrument). 
This metadata record contains information about the raw idat files generated from the Infinium DNA methylation arrays. The raw idat files were processed with Methylation Module (1.8.5) software in Genome Studio (V2010.3). Peak-based correction was used to normalize the beta-value matrix.
The raw idat files along with a samplesheet, processed beta-value matrix, annotation file for CpG annotation will be made available upon request. Limited phenotype information is available in the Supplemental Table S2 of the manuscript. All scripts that give a walk-through to our project, including the modelling process with Machine Learning can be found in our GitHub repository.
Terms for access
The DNA methylation dataset is only to be used for research that is seeking to advance the understanding of the influence of epigenetic factors on leukemia etiology and biology.
The data should not be used for other purposes, i.e. investigating the epigenetic signatures that may lead to identification of a person.
<br>
For retrieving the data used for the scope of this publication, please contact datacentre@scilifelab.se.
DOI: 10.17044/scilifelab.22303531.v3
title: Multimodal classification of molecular subtypes in pediatric acute lymphoblastic leukemia

description: This dataset contains genome-wide DNA methylation data generated from 384 pediatric acute lymphoblastic leukemia (ALL) samples originating from bone marrow or peripheral blood samples taken at ALL diagnosis (n = 384). Further details regarding the samples are available in Supplementary Table S2 from Krali et al., 2023 (https://doi.org/10.1038/s41698-023-00479-5).Genome-wide DNA methylation was analyzed at the SNP&SEQ Technology Platform, SciLifeLab, National Genomics Infrastructure Uppsala, Sweden. 250 ng of bisulfite converted DNA was amplified, fragmented and hybridised to Illumina Infinium Human Methylation450k Beadchip using the standard protocol from Illumina (iScan SQ instrument).This metadata record contains information about the raw idat files generated from the Infinium DNA methylation arrays. The raw idat files were processed with Methylation Module (1.8.5) software in Genome Studio (V2010.3). Peak-based correction was used to normalize the beta-value matrix.The raw idat files along with a samplesheet, processed beta-value matrix, annotation file for CpG annotation will be made available upon request. Limited phenotype information is available in the Supplemental Table S2 of the manuscript. All scripts that give a walk-through to our project, including the modelling process with Machine Learning can be found in our GitHub repository.Terms for accessThe DNA methylation dataset is only to be used for research that is seeking to advance the understanding of the influence of epigenetic factors on leukemia etiology and biology.The data should not be used for other purposes, i.e. investigating the epigenetic signatures that may lead to identification of a person.<br>For retrieving the data used for the scope of this publication, please contact datacentre@scilifelab.se.
DOI: 10.7483/opendata.cms.bxn4.yw0p
title: /TprimeBToTH_TLep_Hbb_LH_MT3000_MH450_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.17044/scilifelab.22270225.v1
title: Metagenomic dataset from Swedish urban lakes

description: We release metagenomic data of seven urban, eutrophic Swedish lakes that have been extensively studied and characterized in terms of biogeochemistry. Here we provide the supplementary tables and the full set of metagenome-assembled genomes of 17 metagenomic samples.
<br>
- We have 10 metagenomic samples from Lake Mälaren which is the third largest lake in Sweden and serves as the main drinking water supply to ~1.5 million residents in Stockholm and neighboring cities. This dataset is the first insight into the bacterial dynamics of Lake Mälaren during the summer seasonal gradient (early July – late August 2021). 
-  We sampled two additional lakes (Trehoringen and Langsjön) in Uppsala to compare summer microbial communities in lakes in Central Sweden. 
- Additionally, we sequenced, assembled and binned microbial communities in five Swedish lakes in the urban Stockholm-Uppsala region from 2002 that were previously characterized using older techniques (Eiler and Bertilsson, 2004). These five highly eutrophic lakes have a long history of seasonal cyanobacterial blooms in the summer (Eiler and Bertilsson, 2004). 
 
Our goal was to collect and sequence data that could be used to generate hypothesis and preliminary view of micrbial community or urban lakes around Stockholm with special emphasis on Lake Mälaren which proved drinking water to millions of people. In these data we release 17 shot-gun metagenomes in the  European Nucleotide Archive (ENA) and are accessible under project number PRJEB54817.  Moreover, in this repository we provide the 2378 MAGs that include the 514 species representative genomes (SRG, calculated &lt;95% average nucleotide identity - ANI). 
<br>
Finally, here you also can find the 4 supplementary tables that include the following information.
<br>
· Table S1. Sample metadata
· Table S2. Metagenomic assembly statistics (QUAST)
· Table S3. List of metagenome assembled genomes (MAGs), checkM statistics and GTDB taxonomic classification. Dereplicated species representative genomes are marked with x
· Table S4. Species representative genomes (SRGs) abundance in copies per million reads
DOI: 10.7483/opendata.cms.5ijy.ey4a
title: /TprimeBToTH_TLep_Hbb_LH_MT3000_MH500_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.17044/scilifelab.22270225.v3
title: Metagenomic dataset from Swedish urban lakes

description: We release metagenomic data of seven urban, eutrophic Swedish lakes that have been extensively studied and characterized in terms of biogeochemistry. Here we provide the supplementary tables and the full set of metagenome-assembled genomes of 17 metagenomic samples.
- We have 10 metagenomic samples from Lake Mälaren which is the third largest lake in Sweden and serves as the main drinking water supply to ~1.5 million residents in Stockholm and neighboring cities. This dataset is the first insight into the bacterial dynamics of Lake Mälaren during the summer seasonal gradient (early July – late August 2021).
- We sampled two additional lakes (Trehoringen and Langsjön) in Uppsala to compare summer microbial communities in lakes in Central Sweden.
- Additionally, we sequenced, assembled and binned microbial communities in five Swedish lakes in the urban Stockholm-Uppsala region from 2002 that were previously characterized using older techniques (Eiler and Bertilsson, 2004). These five highly eutrophic lakes have a long history of seasonal cyanobacterial blooms in the summer (Eiler and Bertilsson, 2004).
Our goal was to collect and sequence data that could be used to generate hypothesis and preliminary view of microbial community or urban lakes around Stockholm with special emphasis on Lake Mälaren which proved drinking water to millions of people. In these data we release 17 shot-gun metagenomes in the European Nucleotide Archive (ENA) and are accessible under project number PRJEB54817. Moreover, in this repository we provide the 2378 MAGs that include the 514 species representative genomes (SRG, calculated &lt;95% average nucleotide identity - ANI).
Finally, here you also can find the 4 supplementary tables that include the following information.
· Table S1. Sample metadata
· Table S2. Metagenomic assembly statistics (QUAST)
· Table S3. List of metagenome assembled genomes (MAGs), checkM statistics and GTDB taxonomic classification. Dereplicated species representative genomes are marked with x
· Table S4. Species representative genomes (SRGs) abundance in copies per million reads
DOI: 10.17044/scilifelab.22305991
title: 5'P metadegradome coverage for vaginal microbiome datasets

description: Coverage traks for  5´ monophosphorylated mRNA decay intermediates (5´P) in bacterial species from vaginal swabs.
Bedgraph files provide information for the 5'P coverage for the forward and reverse strand. Datasets are provided for 8 samples (r1 to r8).
<br>
DOI: 10.17044/scilifelab.22305991.v1
title: 5'P metadegradome coverage for vaginal microbiome datasets

description: Coverage traks for  5´ monophosphorylated mRNA decay intermediates (5´P) in bacterial species from vaginal swabs.
Bedgraph files provide information for the 5'P coverage for the forward and reverse strand. Datasets are provided for 8 samples (r1 to r8).
<br>
DOI: 10.6084/m9.figshare.28194794.v1
title: Enterobacter aerogenes wgMLST scheme.

description: Backup of the BioNumerics Enterobacter aerogenes wgMLST scheme.
DOI: 10.7483/opendata.cms.bewl.ad6v
title: /TprimeBToTH_TLep_Hbb_LH_MT3000_MH500_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.17044/scilifelab.22348714
title: Can we use molecular dynamics to simulate biomolecular recognition?

description: This Dataset contains starting structures, inout files and scripts to prepare and run normal and biased simulations on the LacI Transcriptionfactor and DNA (with different sequences). The starting structures (based on the crystal structure with PDB ID 1EFA), input files for GROMACS and PLUMED and scripts for prepartion and analysis are also available on GitHub. In this dataset, one can additionally find the trajetories of the simulations that were run to produce the linked publication.
The trajectories include the follwing sets:
<br>
<strong>Unbiased simulations </strong>
5 replica of 50 ns each
<br>
<strong>NMR restraint simulations </strong>
2 DNA sequences: specific, OSymL and non-specific NOD
3 replica of 250 ns each
<br>
<strong>Metadynamics simulations</strong>
OSymL (specific DNA sequence)
bias on selected contacts between the protein and the DNA
bias on selected contacts between the protein and the DNA and between the two hinge helices
bias on selected contacts between the protein and the DNA and between the two hinge helices and the hinge helixity
<br>
NOD (non-specific DNA sequence)
bias on selected contacts between the protein and the DNA and between the two hinge helices and the hinge helixity
<br>
Code contains the scripts used for preparing, running and analysing the simulations. It is also available on GitHub (https://github.com/mallu2/Transcriptionfactor_unbinding).
DOI: 10.17044/scilifelab.22348714.v1
title: Can we use molecular dynamics to simulate biomolecular recognition?

description: This Dataset contains starting structures, inout files and scripts to prepare and run normal and biased simulations on the LacI Transcriptionfactor and DNA (with different sequences). The starting structures (based on the crystal structure with PDB ID 1EFA), input files for GROMACS and PLUMED and scripts for prepartion and analysis are also available on GitHub. In this dataset, one can additionally find the trajetories of the simulations that were run to produce the linked publication.
The trajectories include the follwing sets:
<br>
<strong>Unbiased simulations </strong>
5 replica of 50 ns each
<br>
<strong>NMR restraint simulations </strong>
2 DNA sequences: specific, OSymL and non-specific NOD
3 replica of 250 ns each
<br>
<strong>Metadynamics simulations</strong>
OSymL (specific DNA sequence)
bias on selected contacts between the protein and the DNA
bias on selected contacts between the protein and the DNA and between the two hinge helices
bias on selected contacts between the protein and the DNA and between the two hinge helices and the hinge helixity
<br>
NOD (non-specific DNA sequence)
bias on selected contacts between the protein and the DNA and between the two hinge helices and the hinge helixity
<br>
Code contains the scripts used for preparing, running and analysing the simulations. It is also available on GitHub (https://github.com/mallu2/Transcriptionfactor_unbinding).
DOI: 10.7483/opendata.cms.fgcd.j3t4
title: /TprimeBToTH_TLep_Hbb_LH_MT3000_MH50_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.17044/scilifelab.22361761
title: Genotypes and population allele frequencies in Atlantic and Pacific herring samples

description: Individual genotypes, sample IDs and pool-wise allele freqeuncies used in "A long-standing hybrid population between Pacific and Atlantic herring in a subarctic fjord of Norway" (GBE-230119). The data are stored as tab-separated, gzipped textfiles. For the pool frequencies, sample names are in the header. For the individuals, the genotypes for each snp are stored as a single string with out spaces or tabs. The order is the indicated in the sample file, and each individual is represente by two characters (ie haplotype 1 and haplotype 2). Thus, the first and second character represents the first individual, the third and fourth cahncater the second individual et c.
DOI: 10.17044/scilifelab.22361761.v1
title: Genotypes and population allele frequencies in Atlantic and Pacific herring samples

description: Individual genotypes, sample IDs and pool-wise allele freqeuncies used in "A long-standing hybrid population between Pacific and Atlantic herring in a subarctic fjord of Norway" (GBE-230119). The data are stored as tab-separated, gzipped textfiles. For the pool frequencies, sample names are in the header. For the individuals, the genotypes for each snp are stored as a single string with out spaces or tabs. The order is the indicated in the sample file, and each individual is represente by two characters (ie haplotype 1 and haplotype 2). Thus, the first and second character represents the first individual, the third and fourth cahncater the second individual et c.
DOI: 10.7483/opendata.cms.0ztj.2imf
title: /TprimeBToTH_TLep_Hbb_LH_MT3000_MH50_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.15468/dl.mzcc6g
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pseudohydrosme ebo Cheek"
 ]
}

 The dataset includes 5 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071211-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15472/fmlbsd
title: Fauna y flora asociada al Plan de Ordenación y Manejo Ambiental de la cuenca del río Pauto

description: Bajo los lineamientos técnicos previstos en el decreto 1729 de 2002 y la Guía Técnico Científica formulada por el IDEAM en el 2003, la Corporación Autónoma Regional de la Orinoquia – CORPORINOQUIA, decidió llevar a cabo la elaboración del Plan de Ordenación y Manejo de la Cuenca del río Pauto. Para el fin, se convino integrar la comisión conjunta determinada por las áreas de jurisdicción de cada autoridad ambiental, para el caso del río Pauto, compuesta por CORPORINOQUIA, Corpoboyacá y la UAESPNN.
description: Este conjunto de datos cuenta con 241 registros biológicos correspondientes a los reinos Plantae (220) y Animalia (21). Estos fueron tomados en el año 2007, a lo largo de la cuenca del río Pauto en jurisdicción del departamento de Casanare, algunos de los municipios con más registros son Támara, Trinidad y Chita. Para la caracterización faunística se realizó recorridos de campo para cada tipo de formación vegetal en los que se registró las especies encontradas y para la caracterización de flora se realizó un levantamiento en campo siguiendo el Manual de Métodos para el Desarrollo de Inventarios de Biodiversidad, publicado por el Instituto de Investigación Alexander von Humboldt en el año 2004.
DOI: 10.6084/m9.figshare.28212140
title: Kidney Panel-ACTN4

description: The dataset contains all the variants identified after WES and filtering by a kidney panel.
DOI: 10.7483/opendata.cms.fnrj.4evw
title: /TprimeBToTH_TLep_Hbb_LH_MT3000_MH75_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.15468/dl.vfm4zk
title: Occurrence Download

description: A dataset containing 30787 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-75.43473 8.42455,-75.78335 8.39416,-75.9228 8.32086,-75.91565 8.12063,-75.86202 8.00442,-75.3078 7.95794,-75.14689 8.1975,-75.43473 8.42455))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 30787 records from 67 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071209-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17044/scilifelab.22670290
title: Population allele frequencies, environmental data, and individual genotypes of Atlantic horse mackerel (<em>Trachurus trachurus</em>) collected across the east Atlantic ocean

description: Pool-wise allele frequencies, environmental data, and individual genotypes used in the manuscript entitled "The genomic basis and environmental correlates of local adaptation in the Atlantic horse mackerel (<em>Trachurus trachurus</em>)" (EVA-2023-003-OA). 
In the pool-wise allele frequencies file (tab-separated text gzipped file), pool sample names are indicated in the columns header and SNP markers are in rows (the first two columns indicate the chromosome, CHROM, and base pair position, POS). 
In the individual genotype data file (VCF format), rows 1-17 correspond to the general header of the file, row 18 shows the header indicating markers and sample information, genotype data starts in row 19 onwards. The header in row 18 indicates:
Col 1: chromosome (CHROM)
Col 2: position (POS)
Col 3: SNP ID (ID)
Col 4: reference allele (REF)
Col 5: alternative allele (ALT)
Col 6: marker quality (QUAL)
Col 7: filter (FILTER)
Col 8: information (INFO)
Col 9: genotype format (FORMAT)
Col 10-onwards: samples, one per column
In the environmental data file (tab-separated text file), each row corresponds to a pool sample and each column to environmental data such as depth, Longitude (Lon), Latitude (Lat), and eight environmental variables:
Mean depth mean current velocity (m/s) (BO21_curvelmean_bdmean)
Mean depth mean dissolved oxygen (umol/m3) (BO21_dissoxmean_bdmean)
Mean depth mean iron content (umol/m3) (BO21_ironmean_bdmean)
Mean depth mean nitrate (umol/m3) (BO21_nitratemean_bdmean)
Mean depth mean primary productivity (g/m3/day) (BO21_ppmean_bdmean)
Mean depth mean salinity (PSS) (BO21_salinitymean_bdmean)
Mean depth mean temperature (°C) (BO21_tempmean_bdmean)
Mean depth mean temperature range (°C) (BO21_temprange_bdmean)
DOI: 10.7483/opendata.cms.cq06.0c8p
title: /TprimeBToTH_TLep_Hbb_LH_MT3000_MH75_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.17044/scilifelab.22670290.v1
title: Population allele frequencies, environmental data, and individual genotypes of Atlantic horse mackerel (Trachurus trachurus) collected across the east Atlantic ocean

description: Pool-wise allele frequencies, environmental data, and individual genotypes used in the manuscript entitled "The genomic basis and environmental correlates of local adaptation in the Atlantic horse mackerel (Trachurus trachurus)" (EVA-2023-003-OA). 
In the pool-wise allele frequencies file (tab-separated text gzipped file), pool sample names are indicated in the columns header and SNP markers are in rows (the first two columns indicate the chromosome, CHROM, and base pair position, POS). 
In the individual genotype data file (VCF format), rows 1-17 correspond to the general header of the file, row 18 shows the header indicating markers and sample information, genotype data starts in row 19 onwards. The header in row 18 indicates:
Col 1: chromosome (CHROM)
Col 2: position (POS)
Col 3: SNP ID (ID)
Col 4: reference allele (REF)
Col 5: alternative allele (ALT)
Col 6: marker quality (QUAL)
Col 7: filter (FILTER)
Col 8: information (INFO)
Col 9: genotype format (FORMAT)
Col 10-onwards: samples, one per column
In the environmental data file (tab-separated text file), each row corresponds to a pool sample and each column to environmental data such as depth, Longitude (Lon), Latitude (Lat), and eight environmental variables:
Mean depth mean current velocity (m/s) (BO21_curvelmean_bdmean)
Mean depth mean dissolved oxygen (umol/m3) (BO21_dissoxmean_bdmean)
Mean depth mean iron content (umol/m3) (BO21_ironmean_bdmean)
Mean depth mean nitrate (umol/m3) (BO21_nitratemean_bdmean)
Mean depth mean primary productivity (g/m3/day) (BO21_ppmean_bdmean)
Mean depth mean salinity (PSS) (BO21_salinitymean_bdmean)
Mean depth mean temperature (°C) (BO21_tempmean_bdmean)
Mean depth mean temperature range (°C) (BO21_temprange_bdmean)