github: https://github.com/SegataLab/lefse
install
conda create -n lefse
conda activate lefse
conda install -c bioconda lefse
format
python ~/huty/softwares/miniconda3/envs/lefse/bin/lefse_format_input.py \
input_layer.txt input_layer.in -c 1 -u 2
-c指定分组行
-s指定亚组行,若没有可以不指定
-u指定样本编号
-o指定归一化后范围; -o 1000000
usage: lefse_format_input.py INPUT_FILE OUTPUT_FILE
--output_table OUTPUT_TABLE the formatted table in txt format
-f {c,r} set whether the features are on rows (default) or on columns
-c [1..n_feats] set which feature use as class (default 1)
-s [1..n_feats] set which feature use as subclass (default -1 meaning no subclass)
-u [1..n_feats] set which feature use as subject (default -1 meaning no subject)
-o float set the normalization value (default -1.0 meaning no normalization)
analysis
python ~/huty/softwares/miniconda3/envs/lefse/bin/lefse_run.py \
input_layer.in input_layer.res
-a float set the alpha value for the Anova test (default 0.05)
-w float set the alpha value for the Wilcoxon test (default 0.05)
-l float set the threshold on the absolute value of the logarithmic LDA score (default 2.0)
过程
# layer
Number of significantly discriminative features: 6806 ( 6806 ) before internal wilcoxon
Number of discriminative features with abs LDA score > 2.0 : 1169
# site
Number of significantly discriminative features: 127 ( 737 ) before internal wilcoxon
Number of discriminative features with abs LDA score > 2.0 : 1
参考:
宏基因组数据分析:差异分析(LEfSe安装使用及LDA score计算)
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