SaDA: From Sampling to Data Analysis-An Extensible Open Source Infrastructure for Rapid, Robust and Automated Management and Analysis of Modern Ecological High-Throughput Microarray Data

被引:4
|
作者
Singh, Kumar Saurabh [1 ]
Thual, Dominique [2 ]
Spurio, Roberto [1 ]
Cannata, Nicola [3 ]
机构
[1] Univ Camerino, Sch Biosci & Vet Med, I-62032 Varano Camerino, Italy
[2] Next Generat Bioinformat Srl, I-62032 Camerino, Italy
[3] Univ Camerino, Sch Sci & Technol, I-62032 Camerino, Italy
关键词
software; data management; microarrays; ecological assessment; environmental studies; LIMS; open source system; SYSTEM; INFORMATION; GALAXY;
D O I
10.3390/ijerph120606352
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
One of the most crucial characteristics of day-to-day laboratory information management is the collection, storage and retrieval of information about research subjects and environmental or biomedical samples. An efficient link between sample data and experimental results is absolutely important for the successful outcome of a collaborative project. Currently available software solutions are largely limited to large scale, expensive commercial Laboratory Information Management Systems (LIMS). Acquiring such LIMS indeed can bring laboratory information management to a higher level, but most of the times this requires a sufficient investment of money, time and technical efforts. There is a clear need for a light weighted open source system which can easily be managed on local servers and handled by individual researchers. Here we present a software named SaDA for storing, retrieving and analyzing data originated from microorganism monitoring experiments. SaDA is fully integrated in the management of environmental samples, oligonucleotide sequences, microarray data and the subsequent downstream analysis procedures. It is simple and generic software, and can be extended and customized for various environmental and biomedical studies.
引用
收藏
页码:6352 / 6366
页数:15
相关论文
共 50 条
  • [41] Identification and analysis of the regulatory network of Myc and microRNAs from high-throughput experimental data
    Xiong, Lili
    Jiang, Wei
    Zhou, Rui
    Mao, Canquan
    Guo, Zhiyun
    COMPUTERS IN BIOLOGY AND MEDICINE, 2013, 43 (09) : 1252 - 1260
  • [42] SPEEDING UP THE ANALYSIS OF READ-COUNT DATA FROM HIGH-THROUGHPUT SEQUENCING
    Wang, Weibo
    Sun, Wei
    Wang, Wei
    Szatkiewicz, Jin
    EUROPEAN NEUROPSYCHOPHARMACOLOGY, 2017, 27 : S225 - S225
  • [43] Rapid nuclear magnetic resonance data acquisition with improved resolution and sensitivity for high-throughput metabolomic analysis
    Joseph, David
    Sukumaran, Sujeesh
    Chandra, Kousik
    Pudakalakatti, Shivanand M.
    Dubey, Abhinav
    Singh, Amrinder
    Atreya, Hanudatta S.
    MAGNETIC RESONANCE IN CHEMISTRY, 2021, 59 (03) : 300 - 314
  • [44] NucTools: analysis of chromatin feature occupancy profiles from high-throughput sequencing data
    Vainshtein, Yevhen
    Rippe, Karsten
    Teif, Vladimir B.
    BMC GENOMICS, 2017, 18
  • [45] Construction and Analysis of an Integrated Regulatory Network Derived from High-Throughput Sequencing Data
    Cheng, Chao
    Yan, Koon-Kiu
    Hwang, Woochang
    Qian, Jiang
    Bhardwaj, Nitin
    Rozowsky, Joel
    Lu, Zhi John
    Niu, Wei
    Alves, Pedro
    Kato, Masaomi
    Snyder, Michael
    Gerstein, Mark
    PLOS COMPUTATIONAL BIOLOGY, 2011, 7 (11)
  • [46] ExpoSeq: simplified analysis of high-throughput sequencing data from antibody discovery campaigns
    Sorensen, Christoffer, V
    Hofmann, Nils
    Rawat, Puneet
    Sorensen, Frederik, V
    Ljungars, Anne
    Greiff, Victor
    Laustsen, Andreas H.
    Jenkins, Timothy P.
    BIOINFORMATICS ADVANCES, 2024, 4 (01):
  • [47] Editorial: Advancement in Gene Set Analysis: Gaining Insight From High-Throughput Data
    Maleki, Farhad
    Draghici, Sorin
    Menezes, Renee
    Kusalik, Anthony
    FRONTIERS IN GENETICS, 2022, 13
  • [48] NucTools: analysis of chromatin feature occupancy profiles from high-throughput sequencing data
    Yevhen Vainshtein
    Karsten Rippe
    Vladimir B. Teif
    BMC Genomics, 18
  • [49] Empowering High-Throughput High-Content Analysis of Microphysiological Models: Open-Source Software for Automated Image Analysis of Microvessel Formation and Cell Invasion
    Wiggin, Noah
    Cook, Carson
    Black, Mitchell
    Cadena, Ines
    Rahal-Arabi, Salam
    Asnes, Chandler L.
    Ivanova, Yoanna
    Hettiaratchi, Marian H.
    Hind, Laurel E.
    Fogg, Kaitlin C.
    CELLULAR AND MOLECULAR BIOENGINEERING, 2024, : 369 - 383
  • [50] High-throughput data analysis for rapid ranking of high-concentration monoclonal antibody formulations using manufacturability indices
    Yang, Yang
    Velayudhan, Ajoy
    Farid, Suzanne
    Thornhill, Nina
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2017, 253