使用Mutant-allele tumor heterogeneity(MATH)算法评估肿瘤异质性

MATH算法背景

MATH算法最早可追溯到发表于2013年Oral Oncol期刊的MATH, a novel measure of intratumor genetic heterogeneity, is high in poor-outcome classes of head and neck squamous cell carcinoma文章。后来该作者在Cancer上发表了一篇关于头颈部鳞状细胞癌的文章High intratumor genetic heterogeneity is related to worse outcome in patients with head and neck squamous cell carcinoma，并再次说明了MATH的有效性，高MATH的病人与低整体存活率有关等等

MATH算法原文描述

The MATH value for each tumor was based on the distribution of mutant-allele fractions among tumor-specific mutated loci, calculated as the percentage ratio of the width (median absolute deviation, MAD, scaled by a constant factor so that the expected MAD of a sample from a normal distribution equals the standard deviation) to the center (median) of its distribution:MATH=100 * MAD/median

the steps to determine the MATH value can be summarized as follows: (1) calculating the mutant-allele fraction (MAF) for each locus as the ratio of mutant reads to total reads; (2) obtaining the absolute differences of each MAF from the median MAF value, multiplying the median of these absolute differences by a factor of 1.4826, thus the median absolute deviation (MAD) was generated; (3) calculating MATH as the percentage ratio of the MAD to the median of the MAFs among the tumor’s mutated genomic loci, presented as MATH = 100 * MAD/median.

Each tumor’s MATH value was calculated from the median absolute deviation (MAD) and the median of its mutant-allele fractions at tumor-specific mutated loci:MATH=100 * MAD/median. Calculation of MAD followed the default in R, with values scaled by a constant factor (1.4826) so that the expected MAD of a sample from a normal distribution equals the standard deviation.

MATH算法个人理解

1. 首先通过测序数据计算每个样本的MAF（mutant-allele fractions）值，一般软件结果都会给出这个数据

MATH的意义，作者认为MATH能有效的代表肿瘤特异性特变位点的MAF值的分布的偏差，相当于说明MAF偏离该样本的MAF整体分布的程度（有点标准差的意思），当然是MATH值越大，说明肿瘤异质性越高！

重磅推荐

https://bioconductor.org/packages/devel/bioc/vignettes/maftools/inst/doc/maftools.html

0 条评论

• MATH值代表的肿瘤异质性在乳腺癌与生存关系不显著

但是今天要分享的文章Breast Cancer Research and Treatment February 2017 ， 题目是：Clinical and ...

• WashU EpiGenome Browser使用教程

WashU EpiGenome Browser 是我用过最赞的浏览器，没有之一。希望大伙跟着教程好好学习下！ 还有更多教程见：http://epigenomeg...

• 芯片探针ID的基因注释以前很麻烦

而且学生特别的好学，已经懂得去搜索我们已有的1.3万篇教程，找到了芯片探针序列重新注释的流程，但是我昨天就说到过：芯片探针序列的基因注释已经无需你自己亲自做了,...

• Rancher无法启动healthcheck和lb

一个新产品临近上线，全部采购了腾讯云ECS服务器，安装了Rancher 1.6.17做容器编排。在添加主机到服务器集群时，rancher的 healthchec...

• 交互语义学理论（CS）

本文的思想是通过一种依赖于信息交换的机制来描述。在离散系统间的交互中，使用协议对交换的字符冠以相同的命名。用交互形式（GIF）的游戏决策来补充不确定性协议，使其...

• hdu 3853LOOPS (概率DP)

LOOPS Time Limit: 15000/5000 MS (Java/Others)    Memory Limit: 125536/65536 K (J...

• 杭电60题--part 1 HDU1003 Max Sum（DP 动态规划）

Given a sequence a[1],a[2],a[3]......a[n], your job is to calculate the max sum ...

• 卷积神经网络 第三周作业 Keras+-+Tutorial+-+Happy+House+v1

Welcome to the first assignment of week 2. In this assignment, you will:

• 本质空间的张量网络的等级(CS)

阶-d张量的层次（多线性）等级是决定将张量表示为（树）张量网络（TN）的成本的关键。一般来说，众所周知，对于一个固定的精度，一个具有随机条目的张量不能被期望在没...