import pandas as pd ###################################################### # config file ###################################################### configfile: "config.yaml" ###################################################### # read samples.txt to dict ###################################################### SAMPLES = pd.read_csv(config["SAMPLES_FILE"], header=None, sep="\t").set_index(1, drop=False)[0].to_dict() f = open(config['contrasts'], 'r') CONTRASTS = [i.strip().replace('\t', '_vs_') for i in f.readlines()] ###################################################### # Includes ###################################################### include: "Includes/Annotation.snake" include: "Includes/Mapping_Ref.snake" include: "Includes/Quantification_Ref.snake" include: "Includes/ExprAnalysis.snake" ###################################################### # result files ###################################################### rule all: input: config["Quantification_Dir"] + "/my.gene.counts.matrix", # gene counts matrix config["Quantification_Dir"] + "/my.gene.TMM.EXPR.matrix", # TMP and TMM normalized matrix #config["Quantification_Dir"] + "/my.gene.TMM.EXPR.matrix.stat.txt", config["ExprAnalysis_Dir"] + "/sample_cor/my.minRow10.sample_cor.dat", # sample correlation config["ExprAnalysis_Dir"] + "/sample_cor/my.minRow10.sample_cor_matrix.pdf", # sample correlation plot config["ExprAnalysis_Dir"] + "/pca/my.minRow10.PCA.prcomp.scores", # sample PCA config["ExprAnalysis_Dir"] + "/pca/my.minRow10.prcomp.principal_components.pdf", # sample PCA plot expand(config["ExprAnalysis_Dir"] + "/deg/my.gene.counts.matrix.{vs}.DESeq2.DE_results", vs=CONTRASTS) #expand(config["ExprAnalysis_Dir"] + "/deg/my.gene.counts.matrix.{vs}.DESeq2.DE_results.ekp_results.txt", vs = CONTRASTS)