Editing Biostatistics (section)

== Tools ==

There are a lot of tools that can be used to do statistical analysis in biological data. Most of them are useful in other areas of knowledge, covering a large number of applications (alphabetical). Here are brief descriptions of some of them:
* [[ASReml]]: Another software developed by VSNi<ref name="vsni">{{cite web|url=https://www.vsni.co.uk/|title=Home - VSN International|website=www.vsni.co.uk}}</ref> that can be used also in R environment as a package. It is developed to estimate variance components under a general linear mixed model using [[restricted maximum likelihood]] (REML). Models with fixed effects and random effects and nested or crossed ones are allowed. Gives the possibility to investigate different [[Covariance matrix|variance-covariance]] matrix structures.
* CycDesigN:<ref>{{cite web|url=https://www.vsni.co.uk/software/cycdesign/|title=CycDesigN - VSN International|website=www.vsni.co.uk}}</ref> A computer package developed by VSNi<ref name="vsni" /> that helps the researchers create experimental designs and analyze data coming from a design present in one of three classes handled by CycDesigN. These classes are resolvable, non-resolvable, partially replicated and [[Crossover study|crossover designs]]. It includes less used designs the Latinized ones, as t-Latinized design.<ref>{{cite journal|last1=Piepho|first1=Hans-Peter|last2=Williams|first2=Emlyn R|last3=Michel|first3=Volker|year=2015|title=Beyond Latin Squares: A Brief Tour of Row-Column Designs|journal=Agronomy Journal|volume=107|issue=6|pages=2263|doi=10.2134/agronj15.0144|bibcode=2015AgrJ..107.2263P }}</ref>
* [[Orange (software)|Orange]]: A programming interface for high-level data processing, data mining and data visualization. Include tools for gene expression and genomics.<ref name=":4" />
* [[R (programming language)|R]]: An [[open source]] environment and programming language dedicated to statistical computing and graphics. It is an implementation of [[S (programming language)|S]] language maintained by CRAN.<ref>{{cite web|url=https://cran.r-project.org/|title=The Comprehensive R Archive Network|website=cran.r-project.org}}</ref> In addition to its functions to read data tables, take descriptive statistics, develop and evaluate models, its repository contains packages developed by researchers around the world. This allows the development of functions written to deal with the statistical analysis of data that comes from specific applications.<ref>{{cite book|title=Biostatistics explored through R software: An overview|author=Renganathan V|year=2021|publisher=Vinaitheerthan Renganathan |isbn=9789354936586}}</ref> In the case of Bioinformatics, for example, there are packages located in the main repository (CRAN) and in others, as [[Bioconductor]]. It is also possible to use packages under development that are shared in hosting-services as [[GitHub]].
* [[SAS (software)|SAS]]: A data analysis software widely used, going through universities, services and industry. Developed by a company with the same name ([[SAS Institute]]), it uses [[SAS language]] for programming.
* PLA 3.0:<ref>{{Cite web|url=https://www.bioassay.de/products/pla-30/|title=PLA 3.0|last=Stegmann|first=Dr Ralf|date=2019-07-01|website=PLA 3.0 – Software for Biostatistical Analysis|language=en|access-date=2019-07-02}}</ref> Is a biostatistical analysis software for regulated environments (e.g. drug testing) which supports Quantitative Response Assays (Parallel-Line, Parallel-Logistics, Slope-Ratio) and Dichotomous Assays (Quantal Response, Binary Assays). It also supports weighting methods for combination calculations and the automatic data aggregation of independent assay data.
* [[Weka (machine learning)|Weka]]: A [[Java (programming language)|Java]] software for [[machine learning]] and [[data mining]], including tools and methods for visualization, clustering, regression, association rule, and classification. There are tools for cross-validation, bootstrapping and a module of algorithm comparison. Weka also can be run in other programming languages as Perl or R.<ref name=":4" />
* [[Python (programming language)]] image analysis, deep-learning, machine-learning
* [[SQL]] databases
* [[NoSQL]]
* [[NumPy]] numerical python
* [[SciPy]]
* [[SageMath]]
* [[LAPACK]] linear algebra
* [[MATLAB]]
* [[Apache Hadoop]]
* [[Apache Spark]]
* [[Amazon Web Services]]