cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.7928660
title: gVCF_HG02253

description: 1000 Genomes gVCF mapped to hs37d5 for HG02253. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928666.v1
title: gVCF_NA19359

description: 1000 Genomes gVCF mapped to hs37d5 for NA19359. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928669.v1
title: gVCF_HG03868

description: 1000 Genomes gVCF mapped to hs37d5 for HG03868. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928648
title: gVCF_HG02252

description: 1000 Genomes gVCF mapped to hs37d5 for HG02252. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928651
title: gVCF_HG03867

description: 1000 Genomes gVCF mapped to hs37d5 for HG03867. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928654
title: gVCF_NA19355

description: 1000 Genomes gVCF mapped to hs37d5 for NA19355. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928660.v1
title: gVCF_HG02253

description: 1000 Genomes gVCF mapped to hs37d5 for HG02253. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928642
title: gVCF_HG03866

description: 1000 Genomes gVCF mapped to hs37d5 for HG03866. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928651.v1
title: gVCF_HG03867

description: 1000 Genomes gVCF mapped to hs37d5 for HG03867. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928630
title: gVCF_HG02250

description: 1000 Genomes gVCF mapped to hs37d5 for HG02250. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928633
title: gVCF_NA19351

description: 1000 Genomes gVCF mapped to hs37d5 for NA19351. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928648.v1
title: gVCF_HG02252

description: 1000 Genomes gVCF mapped to hs37d5 for HG02252. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928654.v1
title: gVCF_NA19355

description: 1000 Genomes gVCF mapped to hs37d5 for NA19355. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928624
title: Systematic evaluation of the microRNAome through miR-CATCHv2.0 identifies positive and negative regulators of <i>BRAF</i>-X1 mRNA

description: Here we present miR-CATCHv2.0, an implemented experimental method that allows the identification of the microRNA species directly bound to an RNA of interest. After cross-linking of microRNA::RNA::Ago2 complexes using formaldehyde, the RNA is fragmented using sonication and then subjected to affinity purification using two sets of biotinylated tiling probes (ODD and EVEN). Finally, enriched microRNA species are retrieved by means of small RNA sequencing coupled with an <i>ad hoc</i> analytical workflow. In BRAFV600E mutant A375 melanoma cells, miR-CATCHv2.0 allowed us to identify 20 microRNAs that target X1, the most abundant isoform of <i>BRAF</i> mRNA. These microRNAs fall into different functional classes, according to the effect that they exert (decrease/increase in BRAFV600E mRNA and protein levels) and to the mechanism they use to achieve it (destabilization/stabilization of X1 mRNA or decrease/increase in its translation). microRNA-induced variations in BRAFV600E protein levels are most of the times coupled to consistent variations in pMEK levels, in melanoma cell proliferation <i>in vitro</i> and in sensitivity to the BRAF inhibitor vemurafenib in a xenograft model in zebrafish. However, microRNAs exist that uncouple the degree of activation of the ERK pathway from the levels of BRAFV600E protein. Our study proposes miR-CATCHv2.0 as an effective tool for the identification of direct microRNA-target interactions and, by using such a tool, unveils the complexity of the post-transcriptional regulation to which BRAFV600E and the ERK pathway are subjected in melanoma cells.
DOI: 10.6084/m9.figshare.7928630.v1
title: gVCF_HG02250

description: 1000 Genomes gVCF mapped to hs37d5 for HG02250. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928615
title: gVCF_HG03864

description: 1000 Genomes gVCF mapped to hs37d5 for HG03864. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928624.v1
title: Systematic evaluation of the microRNAome through miR-CATCHv2.0 identifies positive and negative regulators of <i>BRAF</i>-X1 mRNA

description: Here we present miR-CATCHv2.0, an implemented experimental method that allows the identification of the microRNA species directly bound to an RNA of interest. After cross-linking of microRNA::RNA::Ago2 complexes using formaldehyde, the RNA is fragmented using sonication and then subjected to affinity purification using two sets of biotinylated tiling probes (ODD and EVEN). Finally, enriched microRNA species are retrieved by means of small RNA sequencing coupled with an <i>ad hoc</i> analytical workflow. In BRAFV600E mutant A375 melanoma cells, miR-CATCHv2.0 allowed us to identify 20 microRNAs that target X1, the most abundant isoform of <i>BRAF</i> mRNA. These microRNAs fall into different functional classes, according to the effect that they exert (decrease/increase in BRAFV600E mRNA and protein levels) and to the mechanism they use to achieve it (destabilization/stabilization of X1 mRNA or decrease/increase in its translation). microRNA-induced variations in BRAFV600E protein levels are most of the times coupled to consistent variations in pMEK levels, in melanoma cell proliferation <i>in vitro</i> and in sensitivity to the BRAF inhibitor vemurafenib in a xenograft model in zebrafish. However, microRNAs exist that uncouple the degree of activation of the ERK pathway from the levels of BRAFV600E protein. Our study proposes miR-CATCHv2.0 as an effective tool for the identification of direct microRNA-target interactions and, by using such a tool, unveils the complexity of the post-transcriptional regulation to which BRAFV600E and the ERK pathway are subjected in melanoma cells.
DOI: 10.6084/m9.figshare.7928612
title: gVCF_HG02239

description: 1000 Genomes gVCF mapped to hs37d5 for HG02239. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928615.v1
title: gVCF_HG03864

description: 1000 Genomes gVCF mapped to hs37d5 for HG03864. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928606
title: GCA links TRAF6-ULK1-dependent autophagy activation in resistant chronic myeloid leukemia

description: Imatinib is the first molecularly targeted compound for chronic myeloid leukemia (CML) capable to inhibit BCR-ABL kinase activity. However, recent clinical evidence indicates that a substantial proportion of CML patients exhibit BCR-ABL-dependent or independent resistance to imatinib. Despite the importance of imatinib resistance in CML, the underlying molecular mechanisms of this resistance are largely unknown. Here, we identified GCA (grancalcin) as a critical regulator of imatinib resistance in chronic phase CML via activation of autophagy. Mechanistically, we demonstrated that GCA activates TRAF6 ubiquitin ligase activity to induce Lys63 ubiquitination of ULK1, a crucial regulator of autophagy, resulting in its stabilization and activation. We also highlighted the role of GCA-TRAF6-ULK1 autophagy regulatory axis in imatinib resistance. Our findings represent the basis for novel therapeutic strategies against CML. <b>Abbreviation:</b> ACTB/β-actin: actin beta; ADM: adrenomedullin; AMBRA1: autophagy and beclin 1 regulator 1; AMPK: AMP-activated protein kinase; ANXA5: annexin A5; CP: cytogenetic response; CML: chronic myeloid leukemia; CUL3: cullin 3; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; GCA: grancalcin; Dx: at diagnosis; E-64-d: (2S,3S)-trans-Epoxysuccinyl-L-leucylamido-3-methylbutane ethyl ester; IMres: Imatinib resistance; KLHL20: Kelch-like protein 20; LRMP: lymphoid-restricted membrane protein; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MMR: major molecular response; NH<sub>4</sub>Cl: ammonium chloride; PBMCs: peripheral blood mononuclear cells; PTPRC: protein tyrosine phosphatase, receptor type, C; SQSTM1/p62: sequestosome 1; SYK: spleen associated tyrosine kinase; TAP1: transporter 1, ATP binding cassette subfamily B member; TKIs: ABL-specific tyrosine kinase inhibitors; TLR9: toll- like receptor 9; TRAF6: TNF receptor associated factor 6; ULK1: unc-51 like autophagy activating kinase 1
DOI: 10.6084/m9.figshare.7928609
title: gVCF_NA19350

description: 1000 Genomes gVCF mapped to hs37d5 for NA19350. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928606.v1
title: GCA links TRAF6-ULK1-dependent autophagy activation in resistant chronic myeloid leukemia

description: Imatinib is the first molecularly targeted compound for chronic myeloid leukemia (CML) capable to inhibit BCR-ABL kinase activity. However, recent clinical evidence indicates that a substantial proportion of CML patients exhibit BCR-ABL-dependent or independent resistance to imatinib. Despite the importance of imatinib resistance in CML, the underlying molecular mechanisms of this resistance are largely unknown. Here, we identified GCA (grancalcin) as a critical regulator of imatinib resistance in chronic phase CML via activation of autophagy. Mechanistically, we demonstrated that GCA activates TRAF6 ubiquitin ligase activity to induce Lys63 ubiquitination of ULK1, a crucial regulator of autophagy, resulting in its stabilization and activation. We also highlighted the role of GCA-TRAF6-ULK1 autophagy regulatory axis in imatinib resistance. Our findings represent the basis for novel therapeutic strategies against CML. <b>Abbreviation:</b> ACTB/β-actin: actin beta; ADM: adrenomedullin; AMBRA1: autophagy and beclin 1 regulator 1; AMPK: AMP-activated protein kinase; ANXA5: annexin A5; CP: cytogenetic response; CML: chronic myeloid leukemia; CUL3: cullin 3; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; GCA: grancalcin; Dx: at diagnosis; E-64-d: (2S,3S)-trans-Epoxysuccinyl-L-leucylamido-3-methylbutane ethyl ester; IMres: Imatinib resistance; KLHL20: Kelch-like protein 20; LRMP: lymphoid-restricted membrane protein; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MMR: major molecular response; NH<sub>4</sub>Cl: ammonium chloride; PBMCs: peripheral blood mononuclear cells; PTPRC: protein tyrosine phosphatase, receptor type, C; SQSTM1/p62: sequestosome 1; SYK: spleen associated tyrosine kinase; TAP1: transporter 1, ATP binding cassette subfamily B member; TKIs: ABL-specific tyrosine kinase inhibitors; TLR9: toll- like receptor 9; TRAF6: TNF receptor associated factor 6; ULK1: unc-51 like autophagy activating kinase 1
DOI: 10.6084/m9.figshare.7928609.v1
title: gVCF_NA19350

description: 1000 Genomes gVCF mapped to hs37d5 for NA19350. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928621.v1
title: Facile synthesis of porous Mo2C/C composites by using luffa sponge-derived carbon template in molten salt media

description: Herein, we report the synthesis of a new type of porous Mo<sub>2</sub>C/C composite by using luffa sponge-derived carbon template, and ammonium molybdate ((NH<sub>4</sub>)<sub>6</sub>Mo<sub>7</sub>O<sub>24</sub>•4H<sub>2</sub>O) in the molten NaCl-KCl salts media. The product exhibits a higher specific surface area and three-dimensional porous structure, including macrochannels, micropores, and mesopores. The desirable porous structure is resulted from the carbon template structure and formed Mo<sub>2</sub>C coating.
DOI: 10.6084/m9.figshare.7928600
title: gVCF_HG02238

description: 1000 Genomes gVCF mapped to hs37d5 for HG02238. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928603
title: gVCF_HG03863

description: 1000 Genomes gVCF mapped to hs37d5 for HG03863. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928612.v1
title: gVCF_HG02239

description: 1000 Genomes gVCF mapped to hs37d5 for HG02239. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928582
title: gVCF_HG02236

description: 1000 Genomes gVCF mapped to hs37d5 for HG02236. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928594
title: gVCF_NA19347

description: 1000 Genomes gVCF mapped to hs37d5 for NA19347. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928603.v1
title: gVCF_HG03863

description: 1000 Genomes gVCF mapped to hs37d5 for HG03863. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928579
title: gVCF_HG03862

description: 1000 Genomes gVCF mapped to hs37d5 for HG03862. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928582.v1
title: gVCF_HG02236

description: 1000 Genomes gVCF mapped to hs37d5 for HG02236. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928594.v1
title: gVCF_NA19347

description: 1000 Genomes gVCF mapped to hs37d5 for NA19347. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928600.v1
title: gVCF_HG02238

description: 1000 Genomes gVCF mapped to hs37d5 for HG02238. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928573
title: gVCF_NA19346

description: 1000 Genomes gVCF mapped to hs37d5 for NA19346. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928576
title: gVCF_HG02235

description: 1000 Genomes gVCF mapped to hs37d5 for HG02235. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928555
title: gVCF_NA19338

description: 1000 Genomes gVCF mapped to hs37d5 for NA19338. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928558
title: gVCF_HG02233

description: 1000 Genomes gVCF mapped to hs37d5 for HG02233. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928561
title: A Systematic Review of Large Agriculture Vehicles Use and Crash Incidents on Public Roads

description: <b>Background</b>: Agricultural vehicles are a common sight on rural public roads. However, due to their larger mass (height, width, length, and weight), there are concerns about safety. The aim of this paper is to explore crash incidents on public roads of agricultural vehicles to determine the size of the problem, risk factors, and potential prevention strategies. <b>Methods</b>: A systematic review using the PRISMA guidelines was undertaken of peer-reviewed literature from Medline, Agricola, Scopus, PsycInfo, Science Direct, Web of Science, and SafetyLit. Crash incident rates, risk factors, and prevention strategies were extracted from the articles, and a review of quality was undertaken using McMasters guidelines. <b>Results</b>: Included in the review were 30 articles, with the majority from the United States. Crash risk rates, where reported, were low relative to agricultural vehicle use and when compared to overall road crash numbers. Crash risk factors included weather and visibility, age, personal and driving characteristics, road conditions, and event characteristics. Prevention strategies proposed were targeted at drivers and operators, vehicles, road design, driving behavior, and surveillance, policy, and technology. <b>Conclusions</b>: Overall, reported crash numbers involving large agricultural vehicles were low. Currently, there is limited capacity to calculate exposure rates compounded by the difficulties in identifying road incidents that involve agriculture vehicles. Better surveillance systems are required to improve our understanding of exposure and crash incident rates. Future research into the multiplicity of interrelated factors involved in agriculture vehicle crashes on roads, exposure rates, and evidence for the effectiveness of the prevention strategies is required.
DOI: 10.6084/m9.figshare.7928564
title: gVCF_HG03861

description: 1000 Genomes gVCF mapped to hs37d5 for HG03861. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928573.v1
title: gVCF_NA19346

description: 1000 Genomes gVCF mapped to hs37d5 for NA19346. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928558.v1
title: gVCF_HG02233

description: 1000 Genomes gVCF mapped to hs37d5 for HG02233. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928561.v1
title: A Systematic Review of Large Agriculture Vehicles Use and Crash Incidents on Public Roads

description: <b>Background</b>: Agricultural vehicles are a common sight on rural public roads. However, due to their larger mass (height, width, length, and weight), there are concerns about safety. The aim of this paper is to explore crash incidents on public roads of agricultural vehicles to determine the size of the problem, risk factors, and potential prevention strategies. <b>Methods</b>: A systematic review using the PRISMA guidelines was undertaken of peer-reviewed literature from Medline, Agricola, Scopus, PsycInfo, Science Direct, Web of Science, and SafetyLit. Crash incident rates, risk factors, and prevention strategies were extracted from the articles, and a review of quality was undertaken using McMasters guidelines. <b>Results</b>: Included in the review were 30 articles, with the majority from the United States. Crash risk rates, where reported, were low relative to agricultural vehicle use and when compared to overall road crash numbers. Crash risk factors included weather and visibility, age, personal and driving characteristics, road conditions, and event characteristics. Prevention strategies proposed were targeted at drivers and operators, vehicles, road design, driving behavior, and surveillance, policy, and technology. <b>Conclusions</b>: Overall, reported crash numbers involving large agricultural vehicles were low. Currently, there is limited capacity to calculate exposure rates compounded by the difficulties in identifying road incidents that involve agriculture vehicles. Better surveillance systems are required to improve our understanding of exposure and crash incident rates. Future research into the multiplicity of interrelated factors involved in agriculture vehicle crashes on roads, exposure rates, and evidence for the effectiveness of the prevention strategies is required.
DOI: 10.6084/m9.figshare.7928576.v1
title: gVCF_HG02235

description: 1000 Genomes gVCF mapped to hs37d5 for HG02235. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928540
title: gVCF_HG02231

description: 1000 Genomes gVCF mapped to hs37d5 for HG02231. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928543
title: gVCF_HG03858

description: 1000 Genomes gVCF mapped to hs37d5 for HG03858. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928555.v1
title: gVCF_NA19338

description: 1000 Genomes gVCF mapped to hs37d5 for NA19338. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928531
title: gVCF_HG02230

description: 1000 Genomes gVCF mapped to hs37d5 for HG02230. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928537
title: gVCF_NA19334

description: 1000 Genomes gVCF mapped to hs37d5 for NA19334. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928540.v1
title: gVCF_HG02231

description: 1000 Genomes gVCF mapped to hs37d5 for HG02231. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928543.v1
title: gVCF_HG03858

description: 1000 Genomes gVCF mapped to hs37d5 for HG03858. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928525
title: gVCF_NA19332

description: 1000 Genomes gVCF mapped to hs37d5 for NA19332. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928528
title: gVCF_HG03857

description: 1000 Genomes gVCF mapped to hs37d5 for HG03857. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928531.v1
title: gVCF_HG02230

description: 1000 Genomes gVCF mapped to hs37d5 for HG02230. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928519
title: gVCF_HG03856

description: 1000 Genomes gVCF mapped to hs37d5 for HG03856. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928522
title: gVCF_HG02224

description: 1000 Genomes gVCF mapped to hs37d5 for HG02224. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928528.v1
title: gVCF_HG03857

description: 1000 Genomes gVCF mapped to hs37d5 for HG03857. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928537.v1
title: gVCF_NA19334

description: 1000 Genomes gVCF mapped to hs37d5 for NA19334. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928507
title: gVCF_HG03854

description: 1000 Genomes gVCF mapped to hs37d5 for HG03854. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928513
title: gVCF_HG02223

description: 1000 Genomes gVCF mapped to hs37d5 for HG02223. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928522.v1
title: gVCF_HG02224

description: 1000 Genomes gVCF mapped to hs37d5 for HG02224. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928504
title: gVCF_HG02221

description: 1000 Genomes gVCF mapped to hs37d5 for HG02221. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928504.v1
title: gVCF_HG02221

description: 1000 Genomes gVCF mapped to hs37d5 for HG02221. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928507.v1
title: gVCF_HG03854

description: 1000 Genomes gVCF mapped to hs37d5 for HG03854. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928519.v1
title: gVCF_HG03856

description: 1000 Genomes gVCF mapped to hs37d5 for HG03856. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928483
title: gVCF_NA19327

description: 1000 Genomes gVCF mapped to hs37d5 for NA19327. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928492
title: gVCF_HG02220

description: 1000 Genomes gVCF mapped to hs37d5 for HG02220. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928495
title: gVCF_NA19328

description: 1000 Genomes gVCF mapped to hs37d5 for NA19328. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928498
title: gVCF_HG03851

description: 1000 Genomes gVCF mapped to hs37d5 for HG03851. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928501
title: gVCF_NA19331

description: 1000 Genomes gVCF mapped to hs37d5 for NA19331. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928483.v1
title: gVCF_NA19327

description: 1000 Genomes gVCF mapped to hs37d5 for NA19327. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.6084/m9.figshare.7928495.v1
title: gVCF_NA19328

description: 1000 Genomes gVCF mapped to hs37d5 for NA19328. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307