Gene set /Pathway 基因集 通路分析 进行通路分析时,magma首先将上一步所得到的每个基因的p值通过probit方程转化为z值, 这里的zg整体上近似服从正态分布,zg反映了该基因关联的强度。 Self-contained gene-set analysis检验一个通路上的基因的整体上是否与表型相关联。使用通路里基因的z值,可以构建一个只有截距项的...
# Gene analysis - SNP p-values ../magma--bfile g1000_eur/g1000_eur--pval sumstats/SESA_neuro_clus_sumstats.txt N=449484 --gene-annottest.genes.annot --outtest.gene # cat msigdb.v7.2.entrez.gmt | cut -f1,3- > formated.msigdb.v7.2.entrez.gmt # Gene-set analysis ../magma--gene-...
(2)gene-set analysis方法gene analysis的基础上,将个体基因数据根据生物过程、功能或其它特征进行分类聚合成基因群,利用上一步中得到的基因p值和基因相关矩阵进行实际的基因集分析。Gene-set analysis方法可以被分为self-contained和competitive analysis两种类别。其中self-contained会关注被分到同一个gene set的gene之间...
Gene-set analysis的结果 以pathway为对象的sumstats结果 # TOTAL_GENES = 18152# TEST_DIRECTION = one-sided, positive (set), two-sided (covar)# CONDITIONED_INTERNAL = gene size, gene density, inverse mac, log(gene size), log(gene density), log(inverse mac)VARIABLE TYPE NGENES BETA BETA_ST...
Here, we present a quick-start protocol to perform generalized gene-set analysis of GWAS data on a metaset of gene lists generated by upstream pipelines, such as differential expression analysis, using the Multi-marker Analysis of GenoMic Annotation (MAGMA) software package and Hi-C coupled H-...
when analysing SNP p-value input with variable sample size by SNP (due to missingness or differences in coverage in meta-analysis) • ZSTAT: the Z-value for the gene, based on its (permutation) p-value; this is what is used as the measure of gene association in the gene-level ...
Nature用到的GWAS数据通路富集方法-MAGMA软件。这个软件的英文介绍是MAGMA is a tool for gene analysis and generalized gene-set analysis of GWAS data. It can be used to analyses both raw ge...
MAGMA: de Leeuw, C. A., Mooij, J. M., Heskes, T. & Posthuma, D. MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput. Biol. 11, e1004219 (2015). MAGMA update: de Leeuw, C. A., Sey, N.Y.A., Posthuma, D., Won, H. A response to Yurko et al: H-MAGMA, in...
对于Gene analysis on raw genotype data分析应用的模型默认是linreg,而对于使用--pval参数的分析,默认使用的模型是snp-wise=mean。 产出结果的解读 GENE:第一步注释完之后的基因ID; CHR:基因位于的染色体; START/STOP:染色体上基因的注释边界; NSNPS:注释到该基因的SNP数量; ...
set file:一行是一个set(可以是某个pathway的基因集等等),每行的第一列是set名称,后面的列都是基因ID(entrez ID),tab分割。 4. Meta-analysis on gene level blabla... 可选的model image.png 流程 # 首先需要准备.snp.loc,.gene.loc,bfile(including.bed ,.bim,.fam and maybe sy),.pvalue和.gene...