wgs全基因组序列比对流程
用到的软件
过程步骤
一. 下载准备需要的文件
下载参考序列基因组文件
1.建立索引
bwa index ref.fasta
完成之后 会看到几个ref.fasta为前缀的文件
为参考序列生成dict文件
gatk CreateSequenceDictionary -R ref.fasta -O ref.dict
samtools 建索引
samtools faidx ref.fasta
下载测序文件
fastaq-dump --split-files SRR*****
下载的文件是双末端测序从两端读的read1和read2
>> 用bgzip压缩
bgzip seq1_.fasta
bgzip seq2_.fasta
二.处理文件
将read比对到参考基因组
bwa mem -t 4 -R '@RG\tID:foo\tPL:illumina\tSM:
2022-10-07 09:31:29
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The use of MATLAB is ubiquitous in the scientific and engineering communities today, and justifiably so. Simple programming, rich graphic facilities, built-in functions, and extensive toolboxes offer users the power and flexibility they need to solve the complex analytical problems inherent in modern technologies. The ability to use MATLAB effectively has become practically a prerequisite to success for engineering professionals. Like its best-selling predecessor, Electronics and Circuit Analysis Using MATLAB, Second Edition helps build that proficiency. It provides an easy, practical introduction to MATLAB and clearly demonstrates its use in solving a wide range of electronics and circuit analysis problems. This edition reflects recent MATLAB enhancements, includes new material, and provides even more examples and exercises. New in the Second Edition: · Thorough revisions to the first three chapters that incorporate additional MATLAB functions and bring the material up to date with recent changes to MATLAB · A new chapter on electronic data analysis · Many more exercises and solved examples · New sections added to the chapters on two-port networks, Fourier analysis, and semiconductor physics · MATLAB m-files available for download Whether you are a student or professional engineer or technician, Electronics and Circuit Analysis Using MATLAB, Second Edition will serve you well. It offers not only an outstanding introduction to MATLAB, but also forms a guide to using MATLAB for your specific purposes: to explore the characteristics of semiconductor devices and to design and analyze electrical and electronic circuits and systems
2022-10-03 20:23:41
1.68MB
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Product failure Reliability Analysis using Minitab
2022-09-27 20:24:47
21.99MB
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AndroPy工具
更新！ DroidBox图像是固定的。 动态分析现在正在工作。
这是一个用于从Android APK中提取静态和动态功能的工具。 它结合了各种著名的Android应用程序分析工具，例如DroidBox，FlowDroid，Strace，AndroGuard或VirusTotal分析。 提供了包含APK文件的源目录，AndroPyTool应用了所有这些工具来执行静态，静态和动态分析，并生成JSON和CSV格式的功能文件，还允许将所有数据保存在MongoDB数据库中。
要获取更多信息，您可以阅读以下两篇文章：
马丁·A，拉拉·卡布雷拉·R和卡马乔·D（2018）。 信息融合。 DOI：10.1016 / j.inffus.2018.12.006
马丁·A，拉拉·卡布雷拉·R和卡马乔·D（2018）。 数据科学和知识工程中的传感决策支持（第509-516页）。 世
2022-09-27 11:16:36
259.53MB
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应用统计学入门教程，非常详细易懂，英文原版，第七版，带英文书签目录
2022-09-25 19:49:10
42.91MB
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uboot方面的文档资料 包括源代码的一些分析。教你读懂如何分析uboot
2022-09-24 22:00:19
554KB
2021-域自适应-医学图像分析 综述译文
2022-09-22 09:08:26
38KB
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使用PyTorch在MURA数据集上的DenseNet
在MURA数据集上实现169层模型的PyTorch实现，灵感来自Pranav Rajpurkar等人的论文 。 MURA是肌肉骨骼X射线照片的大型数据集，其中放射医师手动将每项研究标记为正常或异常。
重要事项：
所实现的模型是169层DenseNet，其单节点输出层使用ImageNet数据集上预先训练的模型中的权重进行初始化。
在将图像馈送到网络之前，将每个图像标准化为具有与ImageNet训练集中的图像相同的均值和标准差，并缩放为224 x 224，并通过随机的横向反转和旋转进行增强。
该模型使用了本文提到的改进的二进制交叉熵损失函数。
每次经过一段时间后，验证损失达到稳定水平，学习率就会下降10倍。
优化算法是默认参数β1= 0.9和β2= 0.999的Adam。
根据MURA数据集文件：
该模型将一个或多个用于上
2022-09-21 22:28:28
194KB
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ALGLIB is a cross-platform numerical analysis and data processing library. It supports several programming languages (C++, C#, Delphi) and several operating systems (Windows and POSIX, including Linux). ALGLIB features include:
Data analysis (classification/regression, statistics)
Optimization and nonlinear solvers
Interpolation and linear/nonlinear least-squares fitting
Linear algebra (direct algorithms, EVD/SVD), direct and iterative linear solvers
Fast Fourier Transform and many other algorithms
2022-09-21 22:00:21
3.65MB