Introduction

Resequencing 重测序

[NIBI] Resequencing
https://www.ncbi.nlm.nih.gov/probe/docs/techresequencing/

Resequencing of candidate genes or other genomic regions of interest in patients and controls is a key step in detection of mutations associated with various congenital diseases. Resequencing techniques can be divided into those which test for known mutations (genotyping) and those which scan for any mutation in a given target region (variation analysis). Typical mutations being tested are substitution (SNP), insertion and deletion mutations.

对象
候选基因（candidate genes）和其他基因区域（ interest in patients and controls ？）

用途
检测与多种先天疾病（congenital diseases）相关突变。突变侧重于检测替换（snp），插入（insertion）， 删除（deletion）

分类

1. 检测已知的突变（基因型， genotype）
2. 扫描给定目标区域的所有突变（variation analysis）

步骤
-TODO

Sequence Aligment 序列对比

[WIKIBOOK] Next Generation Sequencing (NGS)/Alignment
https://en.wikibooks.org/wiki/Next_Generation_Sequencing_(NGS)/Alignment

Alignment, also called mapping,[1]
of reads is an essential step in re-sequencing. Having sequenced an organism of a species before, and having constructed a reference sequence, re-sequencing more organisms of the same species allows us to see the genetic differences to the reference sequence, and, by extension, to each other. Alignments of data from these re-sequenced organisms is a relatively simple method of detecting variation in samples. There are certain instances (such as new genes in the sequenced sample that are not found in the existing reference sequence) that can not be detected by alignment alone; however, while other approaches, such as de novo assembly, are potentially more powerful, they are also much harder or, for some organisms, impossible to achieve with current sequencing methods.

序列对比（sequence alignment ）， 也叫序列匹配（sequence mapping）。
是 resequencing 的重要的一个步骤

用途
在已有某物种的测序结果的前提下（已经有的叫参照序列， refrerence sequence）， 再检测同物种下更多的个体（organisms）。 用于对法发现个体之间基因的不同

基本思想
检测序列之间的相似性， 发现生物序列中的功能，结构和进化的信息

分类

• 双序列对比
• 多序列对比
• 局部对比
• 全局对比

算法

• 取代矩阵
• 空位罚分

局限性
-TODO

de-novo assembly

de novo assembly

存储格式

SAM

相关软件

Paste_Image.png

这篇文章是介绍BWA的 前半部分是分析

Bowtie 2

Bowertie 2 Home
http://bowtie-bio.sourceforge.net/bowtie2/index.shtml

Bowertie 2手册
http://bowtie-bio.sourceforge.net/bowtie2/manual.shtml#what-is-bowtie-2

Bowtie 2 is an ultrafast and memory-efficient tool for aligning sequencing reads to long reference sequences. It is particularly good at aligning reads of about 50 up to 100s or 1,000s of characters to relatively long (e.g. mammalian) genomes. Bowtie 2 indexes the genome with an FM Index (based on the Burrows-Wheeler Transform or BWT) to keep its memory footprint small: for the human genome, its memory footprint is typically around 3.2 gigabytes of RAM. Bowtie 2 supports gapped, local, and paired-end alignment modes. Multiple processors can be used simultaneously to achieve greater alignment speed. Bowtie 2 outputs alignments in SAM format, enabling interoperation with a large number of other tools (e.g. SAMtools, GATK) that use SAM. Bowtie 2 is distributed under the GPLv3 license, and it runs on the command line under Windows, Mac OS X and Linux.
Bowtie 2 is often the first step in pipelines for comparative genomics, including for variation calling, ChIP-seq, RNA-seq, BS-seq. Bowtie 2 and Bowtie (also called "Bowtie 1" here) are also tightly integrated into some tools, including TopHat: a fast splice junction mapper for RNA-seq reads, Cufflinks: a tool for transcriptome assembly and isoform quantitiation from RNA-seq reads, Crossbow: a cloud-enabled software tool for analyzing resequencing data, and Myrna: a cloud-enabled software tool for aligning RNA-seq reads and measuring differential gene expression.

SOAP 2

BWA

Overview

Based on FM-index (Burrows-Wheeler Transform plus auxillary data
structures) which enables fast exact matching.
Short-read algorithm: alter the read sequence such that it matches
the reference exactly.
Long-read algorithm (BWA-SW): sample reference subsequences and
perform Smith-Waterman alignment between the subsequences and
the read.
Work for Illumina and SOLiD single-end (SE) and paired-end (PE)
reads; new component BWA-SW for 454/Sanger SE reads.

Key Features

Fast and moderate memory footprint (<4GB)
SAM output by default
Gapped alignment for both SE and PE reads
Effective pairing to achieve high alignment accuracy; suboptimal hits
considered in pairing.
Non-unique read is placed randomly with a mapping quality 0; all hits
can be outputted in a concise format.
Guarantee to find k-difference in the seed (first 32bp by default).
The default configuration works for most typical input.
Automatically adjust parameters based on read lengths and error rates.
Estimate the insert size distribution on the fly