Dataset

Simulated microbial sequencing data (WGS/HiC), 3C-contig graphs and clustering results.

University of Technology, Sydney
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.4225/59/57b0f832e013c&rft.title=Simulated microbial sequencing data (WGS/HiC), 3C-contig graphs and clustering results.&rft.identifier=10.4225/59/57b0f832e013c&rft.publisher=University of Technology, Sydney&rft.description=Raw data associated with the manuscript: DeMaere, Matthew Z., and Aaron E. Darling. Deconvoluting simulated metagenomes: the performance of hard-and soft-clustering algorithms applied to metagenomic chromosome conformation capture (3C). No. e1974v1. PeerJ Preprints, 2016. Contains a structured folder of raw data generated in simulation sweep as well as derivative analysis results. Folders: Data and derivative data and results ref_data - initial basis data for community generation comm_data - generated communities hic_data - raw simulated HiC readsets wgs_data - raw simulated WGS readsets and assembly contigs (A5 assembler) map_data - associated LAST alignment, BWA-MEM BAM files and golden standards (truth) graph_data - 3C-contig graphs in various formats for cluster analysis cluster_data - clustering results and external index scorings (weighted Bcubed) Final result tables mcl.csv louvain_hard.csv oclustr.csv srmcl.csv louvain_soft.csv &rft.creator=Anonymous&rft.date=2016&rft.relation=https://peerj.com/articles/2676/&rft_rights=Copyright, University of Technology Sydney, 2016&rft_rights=CC BY-NC-SA: Attribution-Noncommercial-Share Alike 3.0 AU http://creativecommons.org/licenses/by-nc-sa/3.0/au&rft_subject=Simulation&rft_subject=Microbial Genomics&rft_subject=Metagenomics&rft_subject=Hic Sequencing&rft_subject=Clustering&rft_subject=Microbial Community Analysis&rft_subject=Microbial Ecology&rft_subject=Biological Sciences&rft_subject=Microbiology&rft_subject=Bioinformatics Software&rft_subject=Information and Computing Sciences&rft_subject=Computer Software&rft_subject=Pattern Recognition and Data Mining&rft_subject=Artificial Intelligence and Image Processing&rft_subject=Expanding Knowledge in the Biological Sciences&rft_subject=Expanding Knowledge&rft_subject=Expanding Knowledge&rft_subject=Expanding Knowledge in the Information and Computing Sciences&rft_subject=Applied Research&rft.type=dataset&rft.language=English Go to Data Provider

Licence & Rights:

Non-Commercial Licence view details
CC-BY-NC-SA

CC BY-NC-SA: Attribution-Noncommercial-Share Alike 3.0 AU
http://creativecommons.org/licenses/by-nc-sa/3.0/au

Copyright, University of Technology Sydney, 2016

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Full description

Raw data associated with the manuscript:

DeMaere, Matthew Z., and Aaron E. Darling. Deconvoluting simulated metagenomes: the performance of hard-and soft-clustering algorithms applied to metagenomic chromosome conformation capture (3C). No. e1974v1. PeerJ Preprints, 2016.

Contains a structured folder of raw data generated in simulation sweep as well as derivative analysis results.

Folders:

Data and derivative data and results
ref_data - initial basis data for community generation
comm_data - generated communities
hic_data - raw simulated HiC readsets
wgs_data - raw simulated WGS readsets and assembly contigs (A5 assembler)
map_data - associated LAST alignment, BWA-MEM BAM files and golden standards (truth)
graph_data - 3C-contig graphs in various formats for cluster analysis
cluster_data - clustering results and external index scorings (weighted Bcubed)

Final result tables
mcl.csv
louvain_hard.csv
oclustr.csv
srmcl.csv
louvain_soft.csv
Identifiers