cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.v85uu2
title: Occurrence Download

description: A dataset containing 1858063 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-132.09945 49.806,-130.82336 6.33777,-70.84753 5.70325,-71.69826 49.94306,-132.09945 49.806))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Month is one of (August, September, October)",
 "Year 2022-2022"
 ]
}

 The dataset includes 1858063 records from 108 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0188917-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.voetch
title: Occurrence Download

description: A dataset containing 8256 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is El género Bursera en México. Parte II",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 8256 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007496-190415153152247/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pjzdsx
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Parthenocissus quinquefolia (L.) Planch.",
 "HasCoordinate is true",
 "Country is Japan",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0192761-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v5vgjp
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lotononis serpentinicola Wild"
 ]
}

 The dataset includes 18 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013554-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jctf4f
title: Occurrence Download

description: A dataset containing 3279 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 {
 "or" : [
 "TaxonKey is Hypnum densirameum Ando",
 "TaxonKey is Hypnum plicatulum (Lindb.) A.Jaeger",
 "TaxonKey is Hypnum recurvatum (Lindb. & Arnell) Kindb.",
 "TaxonKey is Hypnum sikkimense Ando",
 "TaxonKey is Hypnum tristoviride (Broth.) Paris",
 "TaxonKey is Hypnum leptothallum Paris"
 ]
 }
 ]
}

 The dataset includes 3279 records from 90 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060530-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g47g95
title: Occurrence Download

description: A dataset containing 39792987 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Asteraceae"
 ]
}

 The dataset includes 39792987 records from 6768 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054683-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17044/scilifelab.19375172
title: Modelling of Large Protein Complexes

description: AlphaFold and AlphaFold-multimer can predict the structure of single- and multiple chain proteins with very high accuracy. However, predicting protein complexes with more than a handful of chains is still unfeasible, as the accuracy rapidly decreases with the number of chains and the protein size is limited by the memory on a GPU. Nevertheless, it might be possible to predict the structure of large complexes starting from predictions of subcomponents. Here, we take a graph traversal approach to assemble 175 protein complexes with 10-30 chains using predictions of subcomponents. We compute paths through a complex graph constructed of subcomponents using Monte Carlo Tree Search and assemble these in a stepwise fashion. Using subcomponents predicted from all possible trimeric interactions, 91 complexes (52%) are assembled to completion. We create a scoring function, mpDockQ, that can distinguish if assemblies are complete and predict their accuracy. Selecting complete complexes with TM-score ≥0.9 at FPR 10% using mpDockQ results in 20 complete complexes with a median TM-score of 0.92. The complete assembly protocol, starting from the sequences, is freely available at: https://gitlab.com/patrickbryant1/molpc <br>The repository here contains MSAs and predicted subcomponents to reproduce the assembly for the "all-trimer" approach.<br><br><br>
DOI: 10.17044/scilifelab.19380116
title: Duplex sequencing uncovers recurrent low-frequency cancer-associated mutations in KMT2A-rearranged infant acute leukemia

description: This dataset includes Duplex sequencing and targeted next generation sequencing (NGS) of 20 Infants and 7 Children with acute lymphoblastic leukmia.
All patients had an underlying rearrangement of the KMT2A gene, either KMT2A::MLLT3 (n=5), KMT2A::AFF1 (n=12), KMT2A::MLLT1 (n=8) or KMT2A::MLLT10 (n=2). The median age of the cohort was 7 months. 
Diagnostic sample from peripheral blod (n=11) or bone marrow (n=16) underwent the duplex sequencing library preparation as described in https://doi.org/10.1073/pnas.1208715109 and sequenced on the NextSeq 500 (Illumina, San Diego, CA, USA).
A subset of variants were validated by targeted multiplex-PCR followed by NGS. In six patients with available relapse samples, a screening of diagnostic variants was performed by multiplex-PCR and NGS. All targeted sequencing libraries were prepared with Nextera XT DNA Sample Preparation Kit (Illumina) and sequenced on the Illumina MiSeq.
DOI: 10.7483/opendata.cms.2lnr.oeow
title: /TprimeBToTH_TLep_Hbb_LH_MT2700_MH125_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.17044/scilifelab.19380116.v1
title: Duplex sequencing uncovers recurrent low-frequency cancer-associated mutations in KMT2A-rearranged infant acute leukemia

description: This dataset includes Duplex sequencing and targeted next generation sequencing (NGS) of 20 Infants and 7 Children with acute lymphoblastic leukmia.
All patients had an underlying rearrangement of the KMT2A gene, either KMT2A::MLLT3 (n=5), KMT2A::AFF1 (n=12), KMT2A::MLLT1 (n=8) or KMT2A::MLLT10 (n=2). The median age of the cohort was 7 months. 
Diagnostic sample from peripheral blod (n=11) or bone marrow (n=16) underwent the duplex sequencing library preparation as described in https://doi.org/10.1073/pnas.1208715109 and sequenced on the NextSeq 500 (Illumina, San Diego, CA, USA).
A subset of variants were validated by targeted multiplex-PCR followed by NGS. In six patients with available relapse samples, a screening of diagnostic variants was performed by multiplex-PCR and NGS. All targeted sequencing libraries were prepared with Nextera XT DNA Sample Preparation Kit (Illumina) and sequenced on the Illumina MiSeq.
DOI: 10.7483/opendata.cms.b3vt.s94d
title: /TprimeBToTH_TLep_Hbb_LH_MT2700_MH125_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.a3v7.uo31
title: /TprimeBToTH_TLep_Hbb_LH_MT2700_MH150_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.15156/bio/1280127
title: UNITE general FASTA release for eukaryotes

description: This release consists of a single FASTA file: the RepS/RefS of all SHs, adopting the dynamically use of clustering thresholds whenever available.
DOI: 10.15156/bio/786368
title: UNITE general FASTA release for Fungi

description: This release consists of a single FASTA file: the RepS/RefS of all SHs, adopting the dynamically use of clustering thresholds whenever available.
DOI: 10.15156/bio/786370
title: UNITE general FASTA release for eukaryotes

description: This release consists of a single FASTA file: the RepS/RefS of all SHs, adopting the dynamically use of clustering thresholds whenever available.
DOI: 10.17044/scilifelab.19411403.v1
title: SH information from UNITE databases

description: The data is the result of querying the PlutoF API (https://plutof.docs.apiary.io, Abarenkov et al 2010) with all sequence names in the UNITE general FASTA release (https://doi.org/10.15156/BIO/786368; Abarenkov et al. 2020, https://doi.org/10.15156/BIO/1280049; Abarenkov et al. 2021), in order to find the sequence hypothesis (SH) at level 1.5, version 8, for each sequence, resulting in a sequence-to-SH matching file (*.seq2SH.tsv). For each SH, the complete taxonomy is extracted from PlutoF by querying the PlutoF API, and stored in the *.SH.tax files.<br>
<br>
Files are available for UNITE version 8.2; sh_general_release_dynamic_04.02.2020.seq2sh.tsv.bz2 containing sequence to SH matchings, and sh_general_release_dynamic_04.02.2020.SHs.tax.bz2 containing SH taxonomies, and for UNITE version 8.3; sh_general_release_dynamic_10.05.2021.seq2sh.tsv.bz2 and sh_general_release_dynamic_10.05.2021.SHs.tax.bz2. All files are tab separated text files compressed with bzip2.<br>
<br>
Corresponding files are also available for the all eukaryotes version if the UNITE database (https://doi.org/10.15156/BIO/786370; Abarenkov et al 2020b, https://doi.org/10.15156/BIO/1280127; Abarenkov et al 2021b)<br>

Assignment of species hypothesis to ITS amplicons using this data and the UNITE general FASTA release is available as an optional argument to the nf-core/ampliseq Nextflow workflow from version 2.3.2: `--addsh` together with `--dada_ref_taxonomy unite-fungi` (https://nf-co.re/ampliseq; Straub et al. 2020).
<br>
<strong>Generation of files</strong><br>
After download and file extraction of the UNITE general FASTA release, each sequence name in the fasta file was used as query to PlutoF to find which SH at level 1.5 in release 8 the sequence belongs to, in order to generate the *.seq2sh.tsv files with sequence to SH matchings. Each SH was subsequently used as query to PlutoF to extract the complete taxonomy for the SH, stored in the *.SHs.tax files.<br>
Two python scripts for automatic querying and generation of the files can be found in the `scripts` folder in the GitHub repo: https://github.com/biodiversitydata-se/unite-shinfo. See the accompanying README file for usage information.<br>
DOI: 10.17044/scilifelab.19411403.v2
title: SH information from UNITE databases

description: The data in this repository is the result of querying the PlutoF API (https://plutof.docs.apiary.io, Abarenkov et al 2010) with all sequence names in the UNITE general FASTA release (https://doi.org/10.15156/BIO/2483911; Abarenkov et al. 2022), in order to find the sequence hypothesis (SH) at level 1.5, version 9, for each sequence, resulting in a sequence-to-SH matching file (*.seq2SH.tsv). For each SH, the complete taxonomy is extracted from PlutoF by querying the PlutoF API, and stored in the *.SH.tax files.
<br>
Files are available for UNITE version 9.0; sh_general_release_dynamic_29.11.2022.seq2sh.tsv.bz2 containing sequence to SH matchings, and sh_general_release_dynamic_29.11.2022.SHs.tax.bz2 containing SH taxonomies. Corresponding files are also available for the all eukaryotes version of the UNITE database (https://doi.org/10.15156/BIO/2483913; Abarenkov et al 2022b). All files are tab separated text files compressed with bzip2.
<br>
Assignment of species hypothesis to ITS amplicons using this data and the UNITE general FASTA release is available as an optional argument to the nf-core/ampliseq Nextflow workflow from version 2.3.2: `--addsh` together with `--dada_ref_taxonomy unite-fungi` or `--dada_ref_taxonomy unite-alleuk` (https://nf-co.re/ampliseq; Straub et al. 2020).
<br>
<strong>Generation of files</strong><br>
After download and file extraction of the UNITE general FASTA release, each sequence name in the fasta file was used as query to PlutoF to find which SH at level 1.5 in release 9 the sequence belongs to, in order to generate the *.seq2sh.tsv files with sequence to SH matchings. Each SH was subsequently used as query to PlutoF to extract the complete taxonomy for the SH, stored in the *.SHs.tax files.<br>
Two python scripts for automatic querying and generation of the files can be found in the `scripts` folder in the GitHub repo: https://github.com/biodiversitydata-se/unite-shinfo. See the accompanying README file for usage information.<br>
DOI: 10.7483/opendata.cms.9vtv.mkey
title: /TprimeBToTH_TLep_Hbb_LH_MT2700_MH150_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.15156/bio/2483913
title: UNITE general FASTA release for eukaryotes

description: This release consists of a single FASTA file: the RepS/RefS of all SHs, adopting the dynamically use of clustering thresholds whenever available.
DOI: 10.7483/opendata.cms.ytuo.m8by
title: /TprimeBToTH_TLep_Hbb_LH_MT2700_MH175_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.17044/scilifelab.19678620
title: WGS for patient specific MRD in pediatric ALL

description: Data from a study of six children with acute lymphoblastic leukemia (four patients with precursor B-cell ALL (Acute lymphoblastic leukemia) and two patients with T-cell ALL). None had stratifying genetics or central nervous system involvement. The study was approved by the Ethical Review Board at Stockholm County and written informed consent was obtained from the patients’ guardians.
<br>
The data consits of BAM-files from whole-genome sequencing (WGS) of diagnostic bone marrow samples (30X coverage on an Illumina HiSeqX Ten platform). The Human GRCh37 (hg19) RefSeq was used for annotation and SV detection was performed using CNVnator V0.3.2 with 1kb bins, Delly, TIDDIT V2.0.0 and Manta. Filtering was performed using a list of recurrent aberrations in ALL. Assays for measurable residual disease (MRD) monitoring were designed from SV sequences and used for ddPCR analysis of gDNA and cfDNA from bone marrow, plasma and cerebrospinal fluid samples from diagnosis and follow-up.
<br>
Data Access Statement
<br>
The WGS datasets are only to be used for research aimed at advancing the understanding of genetic factors in the development of pediatric acute lymphoblastic leukemia. Applications, including those aimed at method development and bioinformatics, would only be considered as acceptable if proof of approved ethical consent is provided. Access requests should be sent to the email adress below.
DOI: 10.17044/scilifelab.19678620.v1
title: WGS for patient specific MRD in pediatric ALL

description: Data from a study of six children with acute lymphoblastic leukemia (four patients with precursor B-cell ALL (Acute lymphoblastic leukemia) and two patients with T-cell ALL). None had stratifying genetics or central nervous system involvement. The study was approved by the Ethical Review Board at Stockholm County and written informed consent was obtained from the patients’ guardians.
<br>
The data consits of BAM-files from whole-genome sequencing (WGS) of diagnostic bone marrow samples (30X coverage on an Illumina HiSeqX Ten platform). The Human GRCh37 (hg19) RefSeq was used for annotation and SV detection was performed using CNVnator V0.3.2 with 1kb bins, Delly, TIDDIT V2.0.0 and Manta. Filtering was performed using a list of recurrent aberrations in ALL. Assays for measurable residual disease (MRD) monitoring were designed from SV sequences and used for ddPCR analysis of gDNA and cfDNA from bone marrow, plasma and cerebrospinal fluid samples from diagnosis and follow-up.
<br>
Data Access Statement
<br>
The WGS datasets are only to be used for research aimed at advancing the understanding of genetic factors in the development of pediatric acute lymphoblastic leukemia. Applications, including those aimed at method development and bioinformatics, would only be considered as acceptable if proof of approved ethical consent is provided. Access requests should be sent to the email adress below.
DOI: 10.7483/opendata.cms.9j76.6604
title: /TprimeBToTH_TLep_Hbb_LH_MT2700_MH175_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.17044/scilifelab.19721998
title: Targeted sequencing of 252 genes based on their relevance in lymphoid malignancies

description: <strong>Dataset description</strong>
Data consists of CRAM file from capture-based gene panel sequencing  (Twist Bioscience) of 252 genes selected based on their relevance in lymphoid malignancies. The panel also included genome-wide backbone probes for copy-number analysis. The preprared libraries were then subsequenlty equenced in paired-end mode (2x150bp) on the Illumina NovaSeq 6000 (Illumina Inc.).
BALSAMIC was used to analyze the FASTQ files and aligning them to reference genome. Trimmed reads were mapped to the reference genome hg19 using BWA MEM v0.7.15 4. The resulting SAM files were converted to BAM files and sorted using samtools v1.6. Duplicated reads were marked using Picard tools MarkDuplicate v2.17.0. And finally converted to CRAM files using samtools v1.6.
<br>
Note: CRAM is a sequencing read file format that is highly space efficient by using reference-based compression of sequence data and offers both lossless and lossy modes of compression: https://www.ebi.ac.uk/ena/cram/
<br>
<strong>Data Access Statement</strong>
The data is under restricted access and can be accessed upon request through the email-adress below.
The targeted sequence datasets are only to be used for research aimed at advancing the understanding of genetic factors in the chronic lymphocytic leukemia. Applications aimed at method development including bioinformatics would not be considered as acceptable for use of this dataset.
DOI: 10.17044/scilifelab.19721998.v1
title: Targeted sequencing of 252 genes based on their relevance in lymphoid malignancies

description: <strong>Dataset description</strong>
Data consists of CRAM file from capture-based gene panel sequencing  (Twist Bioscience) of 252 genes selected based on their relevance in lymphoid malignancies. The panel also included genome-wide backbone probes for copy-number analysis. The preprared libraries were then subsequenlty equenced in paired-end mode (2x150bp) on the Illumina NovaSeq 6000 (Illumina Inc.).
BALSAMIC was used to analyze the FASTQ files and aligning them to reference genome. Trimmed reads were mapped to the reference genome hg19 using BWA MEM v0.7.15 4. The resulting SAM files were converted to BAM files and sorted using samtools v1.6. Duplicated reads were marked using Picard tools MarkDuplicate v2.17.0. And finally converted to CRAM files using samtools v1.6.
<br>
Note: CRAM is a sequencing read file format that is highly space efficient by using reference-based compression of sequence data and offers both lossless and lossy modes of compression: https://www.ebi.ac.uk/ena/cram/
<br>
<strong>Data Access Statement</strong>
The data is under restricted access and can be accessed upon request through the email-adress below.
The targeted sequence datasets are only to be used for research aimed at advancing the understanding of genetic factors in the chronic lymphocytic leukemia. Applications aimed at method development including bioinformatics would not be considered as acceptable for use of this dataset.
DOI: 10.17044/scilifelab.19761307
title: Single-cell gene expression count data for trifluridine treated co-culture of tumor cell line with PBMC

description: Gene expression (counts) scRNA-seq of co-cultured cancer- and immune cells treated with trifluridine and DMSO control assayed at two time-points (12h and 72h).
<br>
HCT116 were seeded in 6-well Nunc plates (50,000 cells/3mL/well) and precultured for 24 h before PBMCs were added at a 1:8 ratio. Co-cultures were treated with DMSO vehicle (0.1%) or FTD (3mM) for 12 h or 72 h. MACS Dead Cell Removal Kit (Miltenyi Biotec, Gladbach, DEU) was performed according to the manufacturer’s instructions on cells treated for 72 h to increase the viability of the samples before RNA-sequencing. The viability of the samples treated for 12 h was not subjected to Dead Cell Removal as the viability was already sufficient. All samples were washed in PBS with 0.04% BSA (2x1mL). Chromium Next GEM Single Cell 3’ library preparation and RNA-sequencing were performed by the SNP&SEQ Technology Platform (National Genomics Infrastructure (NGI), Science for Life Laboratory, Uppsala University, Sweden). 
<br>
This data set contains processed data using Cell Ranger toolkit version 5.0.1 provided by 10x Genomics,  for demultiplexing, aligning reads to the human reference genome GRCh38, and generating gene-cell unique molecular identifiers
DOI: 10.17044/scilifelab.19761307.v1
title: Single-cell gene expression count data for trifluridine treated co-culture of tumor cell line with PBMC

description: Gene expression (counts) scRNA-seq of co-cultured cancer- and immune cells treated with trifluridine and DMSO control assayed at two time-points (12h and 72h).
<br>
HCT116 were seeded in 6-well Nunc plates (50,000 cells/3mL/well) and precultured for 24 h before PBMCs were added at a 1:8 ratio. Co-cultures were treated with DMSO vehicle (0.1%) or FTD (3mM) for 12 h or 72 h. MACS Dead Cell Removal Kit (Miltenyi Biotec, Gladbach, DEU) was performed according to the manufacturer’s instructions on cells treated for 72 h to increase the viability of the samples before RNA-sequencing. The viability of the samples treated for 12 h was not subjected to Dead Cell Removal as the viability was already sufficient. All samples were washed in PBS with 0.04% BSA (2x1mL). Chromium Next GEM Single Cell 3’ library preparation and RNA-sequencing were performed by the SNP&SEQ Technology Platform (National Genomics Infrastructure (NGI), Science for Life Laboratory, Uppsala University, Sweden). 
<br>
This data set contains processed data using Cell Ranger toolkit version 5.0.1 provided by 10x Genomics,  for demultiplexing, aligning reads to the human reference genome GRCh38, and generating gene-cell unique molecular identifiers
DOI: 10.7483/opendata.cms.84jo.n6au
title: /TprimeBToTH_TLep_Hbb_LH_MT2700_MH200_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.17044/scilifelab.19761343
title: Chromium Next GEM Single Cell 3’ RNA-sequencing of tumor cell line co-cultured with PBMC and treated with trifluridine or DMSO control

description: <strong>Chromium Next GEM Single Cell 3’</strong> <strong>RNA-sequencing</strong>. 
<br>
HCT116 were seeded in 6-well Nunc plates (50,000 cells/3mL/well) and precultured for 24 h before PBMCs were added at a 1:8 ratio. Co-cultures were treated with DMSO vehicle (0.1%) or FTD (3mM) for 12 h or 72 h. MACS Dead Cell Removal Kit (Miltenyi Biotec, Gladbach, DEU) was performed according to the manufacturer’s instructions on cells treated for 72 h to increase the viability of the samples before RNA-sequencing. The viability of the samples treated for 12 h was not subjected to Dead Cell Removal as the viability was already sufficient. All samples were washed in PBS with 0.04% BSA (2x1mL). 
<br>
Chromium Next GEM Single Cell 3’ library preparation and RNA-sequencing were performed by the SNP&SEQ Technology Platform (National Genomics Infrastructure (NGI), Science for Life Laboratory, Uppsala University, Sweden).