又是Curtis Huttenhower實(shí)驗(yàn)室開(kāi)發(fā)的軟件~

MaAsLin2是全面的R軟件包呜达，用于有效確定臨床data和微生物組學(xué)特征之間的多變量關(guān)聯(lián)甲抖。 MaAsLin2依靠通用的線性模型來(lái)適應(yīng)大多數(shù)現(xiàn)代流行病學(xué)研究設(shè)計(jì)，包括橫斷面和縱斷面，并提供了多種數(shù)據(jù)探索，標(biāo)準(zhǔn)化和轉(zhuǎn)換方法笆搓。 MaAsLin2是MaAsLin的下一代。

MaAsLin2需要兩個(gè)輸入文件纬傲，一個(gè)是物種豐度表，一個(gè)臨床信息表：

The data file can contain samples not included in the metadata file (along with the reverse case). For both cases, those samples not included in both files will be removed from the analysis. Also the samples do not need to be in the same order in the two files.

• Data (or features) file
  制表符分隔肤频；樣本作為行叹括，feature作為列（也可以轉(zhuǎn)置）；可能的特征包括微生物宵荒、基因汁雷、途徑等
• Metadata file
  制表符分隔；樣本作為行报咳，feature作為列（也可以轉(zhuǎn)置）侠讯；可以是分類型變量，也可以是連續(xù)型

安裝

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("Maaslin2")

使用

library(Maaslin2)
##input data
input_data = system.file(
    "extdata", "HMP2_taxonomy.tsv", package="Maaslin2") # The abundance table file
input_data
input_metadata = system.file(
    "extdata", "HMP2_metadata.tsv", package="Maaslin2") # The metadata table file
input_metadata

##讀入示例數(shù)據(jù)
df_input_data = read.table(file = input_data, header = TRUE, sep = "\t",
                            row.names = 1,
                            stringsAsFactors = FALSE)
df_input_data[1:5, 1:5]
df_input_metadata = read.table(file = input_metadata, header = TRUE, sep = "\t",
                                row.names = 1,
                                stringsAsFactors = FALSE)
df_input_metadata[1:5, ]

##開(kāi)始運(yùn)行Maaslin2
fit_data = Maaslin2(
    input_data = input_data, 
    input_metadata = input_metadata, 
    output = "demo_output", 
    fixed_effects = c("diagnosis", "dysbiosis"))

output 文件

1. Significant associations

• metadata: the variable name being associated with a microbial feature.
• feature: the microbial feature (taxon, gene, pathway, etc.).
• value: for categorical features, the specific feature level for which the coefficient and significance of association is being reported.
• coef: the model coefficient value (effect size).
  • Coefficients for categorical variables indicate the contrast between the category specified in value versus the reference category.
  • MaAsLin2 by default sets the first category in alphabetical order as the reference. See 4.1 Setting Reference Levels on how to change this behavior.
• stderr: the standard error from the model.
• N: the total number of samples used in the model for this association (since e.g. missing values can be excluded).
• N.not.0: the total of number of these samples in which the feature is non-zero.
• pval: the nominal significance of this association.
• qval: the corrected significance is computed with p.adjust with the correction method (BH, etc.)

參考：http://huttenhower.sph.harvard.edu/maaslin