beta_binom | Bayesian estimation for beta binomial distribution |
check_inverse | Can the matrix be inverted? |
color_hclust | Hclust in colour |
col_scale | Column normalization |
counts_to_cpm | Compute counts per million (CPM) |
counts_to_rle | Size Factor normalization as used by DESeq for differential... |
counts_to_tpm | Convert counts to transcripts per million (TPM). |
fancy_heatmap | Fancy Heatmap |
fastload_mat | Load a File as Matrix |
fastwrite_tab | Write a New File as Tab Delimited |
fetch_gc_content | Fetch GC content from gene IDs |
fetch_gene_length | Fetch gene lengths from gene IDs |
foo_tests | Hypothesis tests |
GO_analysis | Gene Ontology Analysis |
GWAS | GWAS |
logistic.model | Implementing binomial GLM (logistic regression) from scratch. |
ma_plot | MA plot |
min_max_scale | Minimum maximum scaling of vector |
mix.beta | Bayesian estimation for a mixture of betas. |
mle_gaussian_dist | Gaussian MLE parameters and Model selection |
mle_weibull_dist | Weibull MLE parameters and Model selection |
plot_mds | Multi-Dimensional Scaling 2D plot |
plot_pca | Principal Component Analysis 2D plot |
plot_svd | Singular Value Decomposition |
read_genome | Read the genome of a given organism |
read_proteome | Read the proteome of a given organism |
row_scale | Row normalization |
smooth_hist | Smooth Histogram |
test_lda | Learns and classifies using a Linear Discriminant Analysis... |
test_limma_lm | Automatic differential gene expression using limma |
test_nb | Learns and classifies using a Naive Bayes Classifier |
test_rf | Learns and classifies using a Random Forest Classifier |
test_svm | Learns and classifies using an SVM |
uq_scale | Upper Quartile Normalization |
write_genome | Save a genome in fasta format This function writes to a file.... |
write_proteome | Save a proteome in fasta format This function writes to a... |
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