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http://bioconductor.org/packages/devel/bioc/vignettes/DESeq2/inst/doc/DESeq2.html

https://www.gencodegenes.org/releases/current.html
https://www.gencodegenes.org/stats/current.html

http://www.sequenceontology.org

https://www.nature.com/articles/nrm.2017.104/tables/1

LincRNA   LncRNA not overlapping a protein-coding transcript

Interface to BioMart databases (e.g. Ensembl, COSMIC, Wormbase and Gramene)

https://bioconductor.org/packages/release/bioc/html/biomaRt.html

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library(biomaRt)
ensembl <- useMart("ensembl",dataset="hsapiens_gene_ensembl")
my.genes <- c("ENSG00000284190", "ENSG00000171658", "Something else")
out <- getBM(attributes=c("ensembl_gene_id", "gene_biotype"),
    filters="ensembl_gene_id", values=my.genes, mart=ensembl)
out <- out[match(my.genes, out$ensembl_gene_id),] # now in correct order/length.https://support.bioconductor.org/p/104800/

http://bioconductor.org/packages/devel/bioc/vignettes/GDCRNATools/inst/doc/GDCRNATools.html

GDCRNATools is an R package which provides a standard, easy-to-use and comprehensive pipeline for downloading, organizing, and integrative analyzing RNA expression data in the GDC portal with an emphasis on deciphering the lncRNA-mRNA related ceRNAs regulatory network in cancer.

R/Excel/SPSS/Matlab

T檢驗:
https://bioant.blogspot.tw/2009/12/excelstudent-t-testp-value.html
http://charngro.blogspot.tw/2016/01/t_86.html

(1)單一樣本(One-sample t-test)
one-sample t-test is used to compare the mean of one sample to a known standard (or theoretical/hypothetical) mean (μ).
假說檢定(Hypothesis Testing)
H0:m=μ
R      http://www.instantr.com/2012/12/29/performing-a-one-sample-t-test-in-r/
Excel http://charngro.blogspot.tw/2016/01/t.html
(2)成對樣本t檢定 (Paired samples t-test)

假說檢定(Hypothesis Testing)
H0:the true mean difference is zero
R    https://www.r-bloggers.com/paired-students-t-test/
(3) 獨立樣本t檢定 (Independent sample t-test)
假說檢定(Hypothesis Testing)
SPSShttps://www.yongxi-stat.com/independent-sample-t-test/
http://www.r-web.com.tw/stat/step1.php?method=two_sample_independent_t_test

(4) 單因子變異數分析(One-way ANOVA)
(H0)：u1 = u2 = u3 =……= uk
http://r97846001.blog.ntu.edu.tw/2010/05/03/sas-analysis-of-variance-anova/
https://www.yongxi-stat.com/one-way-anova-indenpedent/
(5) 二因子變異數分析(Two-way ANOVA)
https://www.yongxi-stat.com/two-way-anova/

benpolletta/HHT-Tutorial https://github.com/benpolletta/HHT-Tutorial/

https://ww2.mathworks.cn/help/matlab/matlab-engine-for-python.html
https://github.com/Calysto/matlab_kernel

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On Windows systems —
cd "C:\Program Files\MATLAB\R2017b\extern\engines\python"
python setup.py install

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$ pip install matlab_kernel

(1) 安裝R/R-Studio
https://cran.r-project.org/bin/windows/base/
https://www.rstudio.com/products/rstudio/download/
(2) 安裝Anaconda
https://www.anaconda.com/download/
(3) 更新Anaconda(命令列)

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conda update anaconda
conda install -c r r-essentials(4) 更新 jupyter_core jupyter_client(命令列)

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conda update jupyter_core jupyter_client(5) Install IRkernel (用R或RStudio)

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install.packages(c('repr', 'IRdisplay', 'evaluate', 'crayon', 'pbdZMQ', 'devtools', 'uuid', 'digest'))
devtools::install_github('IRkernel/IRkernel')
IRkernel::installspec(user = FALSE)

參考
https://stackoverflow.com/questions/48372019/importerror-cannot-import-name-ensure-dir-exists