今天给大家介绍一个快速绘制火山图(volcano map) 拓展工具包-ggVolcano,绘图结果为ggplot2对象,也就可以灵活进行相关主题的设置。详细介绍如下:
前面的帖子(CellChat学习笔记【一】——通讯网络构建)中我们已经成功地进行了细胞间通讯网络的构建,总的来看借助下面简易的分析流程即可完成:
In order to install Splinter, make sure Python is installed. Note: only Python 2.7+ is supported. 目前splinter支持Python2.7以上的版本,请在对应官网下载 http://www.python.org. Linux 和 Mac OS X有可能已经安装了对应的python
一篇旧文,解决一个困扰已经的小技术问题,权当是学习ggplot2以来的整理回顾与查漏补缺。 ---- 今天这一篇是昨天推送的基础上进行了进一步的深化,主要讲如何在离散颜色填充的地图上进行气泡图图层叠加。 为了使得案例前后一致,仍然使用昨天的数据集。 加载包: library("ggplot2") library("plyr") library("maptools") library("sp") library("ggthemes") 导入中国省界地图: china_map<-readShapePoly("
今天看到一个看着挺养眼的经济学人图表案例,于是职业病爆发了,用ggplot2按照自己的思路写了一遍。现在把代码思路分享给大家! 加载包: library("ggplot2") library("tid
今天这一篇是昨天推送的基础上进行了进一步的深化,主要讲如何在离散颜色填充的地图上进行气泡图图层叠加。 为了使得案例前后一致,仍然使用昨天的数据集。 加载包: library(ggplot2) library(plyr) library(maptools) library(sp) 导入中国省界地图: china_map<-readShapePoly("c:/rstudy/bou2_4p.shp") data1<- china_map@data data2<- data.frame(id=row.n
在图形上显示文本,或者标签(与文本的区别是在文本外有一个矩阵边框)是常规需求。用 ggplot2 画图时,有一个默认的几何对象 geom_text 在图上添加文本,但有时候表现得并不好,比如文本与点重叠在一起,文本与文本之间重叠在一起。
今天,我们利用健明老师推荐的批量运行多个R脚本代码,见证一下该代码的优势。首先,下载《Preoperative immune landscape predisposes adverse outcomes in hepatocellular carcinoma patients with liver transplantation》的 GitHub (https://github.com/sangho1130/KOR_HCC) ,我们发现其共包含19个R脚本。然后,我们一个一个打开脚本检查了一下其所用到的R包,下载好所要用到的所有R包。但是在下载R包过程中我们发现RGtk2和rsgcc这两个包一直报错,没有解决掉这个问题。所以,我们把包含这两个包的5个脚本剔除,把剩下的14个R脚本进行批量运行。
在BBC数据团队开发了一个R包,以ggplot2内部风格创建可发布出版物的图形,并且使新手更容易到R创建图形。 例如:
前些天被TCGA的终结新闻刷屏,但是一直比较忙,还没来得及仔细研读,但是笔记本躺着的一些TCGA教程快发霉了,借此契机好好整理一下吧,预计二十篇左右的笔记
之前课题组一个师妹有需要绘制一个带相关性又能展示生存分析显著性的极坐标图,所以造了ggpolar这个包,今天分享给大家,感兴趣的读者不妨使用自己的数据模仿下,应用到自己的分析项目中去。
早晨看到知乎上一篇介绍Go1.9X版本部分功能,特产关注了一下;把源码想给大家呈现下,实际测试请看下一篇文章:Go语言sync.map 实际测试 package sync import ( "sync/atomic" "unsafe" ) // Map is a concurrent map with amortized-constant-time loads, stores, and deletes. // It is safe for multiple
本文实例讲述了Android列表控件Spinner简单用法。分享给大家供大家参考,具体如下:
热图展示不同国家历届足球世界杯的成绩,非常有意思,时间跨度是1982年到2018年,入选国家的标准是最少参加过四次世界杯,我们今天来重复一下这个图,自己这个伪球迷也来了解一下足球世界杯的相关知识。
这张图的每一个点都是一个细胞,同一个颜色的点被认为时一类细胞,那末到底是什么细胞呢,可以通过marker基因进行分析。
上一次推文已经给大家介绍了常见的富集分析类型以及如何使用全能的R包clusterprofiler实现,详情请见:富集分析常见类型
It’s annoying to receive PDFs which are with much extra information or less information than they should have. A large PDF document could make sharing difficult. So, for electric file editors, it’s important to provide the function of editing PDFs like adding and deleting PDF pages.
本文实例讲述了Android开发之开关按钮控件ToggleButton简单用法。分享给大家供大家参考,具体如下:
今天介绍一下基因型数据清洗的一般步骤,我们知道很多分析之前,都要做基因型数据清洗,包括:
我已经下载整理好了,下载本书的电子版pdf+数据+代码,链接:书籍及配套代码领取--统计遗传分析导论
此教程展示了如何应用 CellChat 来识别主要的信号变化,以及通过多个细胞通信网络的联合多重学习和定量对比保守和环境特异的信号。我们通过将其应用于来自两种生物条件:(NL,正常) 和(LS, 损伤) 人类皮肤的细胞的 scRNA-seq 数据,来展示 CellChat 的多重分析功能。这两个数据集具有相同的细胞群组成。如果不同数据集之间的细胞群组成略有或差异较大,请查看另一个相关的教程。
@ConditionalOnClass(KafkaTemplate.class)就是说只有在classpath下能找到KafkaTemplate类才会构建这个bean。
这是对比损失函数的一种变体,不再是使用绝对距离,还要考虑batch中其他样本对的整体距离分布来对损失进行加权,大家可以试试。
下拉列表—Spinner用于显示列表项,类似于一组单选按钮RadioButton。Spinner的使用,可以极大的提升用户的体验性。当需要用户选择的时候,可以提供一个下拉列表项给用户选择。
Sensory, a Silicon Valley company enhancing user experience and security for consumer electronics, announced today its collaboration with Philips, a provider of advanced speech enhancement technologies, to offer a combined technology suite. This would package Sensory’s best-in-class speech recognition technologies TrulyHandsfree™ and TrulyNatural™ with Philips BeClear Speech Enhancement™ algorithms, resulting in significant accuracy improvement in noisy environments. By processing an audio signal with Philips’ echo cancellation, noise suppression and/or beam-forming processors before passing it to Sensory’s speech recognition engine, much of the unwanted ambient noise in a signal can be filtered out, leaving the critical speech portion of the signal largely untouched. This process allows Sensory’s already noise robust speech recognizer to decipher near- and far-field speech more accurately in conditions where very high ambient noise is present.
GLanCE 培训数据集向公众开放,专为区域到全球土地覆被和土地覆被变化分析而设计。该数据集的中等空间分辨率为 30 米,时间跨度为 1984 年至 2020 年,在地理和光谱上代表了全球所有生态区域。每个训练单元提供多达 23 种土地覆被特征,提供了一个统一、标准化和全面的数据库,其中包括有关土地覆被突变和渐变过程的信息,特别是在选定区域的长达 36 年的时间跨度。该数据集具有适应性强的特点,用户可根据自己的研究区域、分类算法和所需的分类图例对其进行子取样和定制,使其成为深入土地覆被调查的多功能资源。前言 – 人工智能教程
Substrate 环境安装提速文档(Mike版,仅限Debian/Ubuntu Linux 和 Mac brew)
CVer 有几天没更新论文速递了,主要是这段时间的论文太多,而且质量较高的论文也不少,所以为了方便大家阅读,我已经将其中的目标检测(Object Detection)论文整理出来。本文分享的目标检测论文将同步推送到 github上,欢迎大家 star/fork(点击阅读原文,也可直接访问):
Class条件注解有一对语义相反的注解,@ConditionalOnClass和@ConditionalOnMissClass分别表达"当指定类存在时"和"当指定类不存在时"的语义。
自从周运来写了一篇cellchat的中文介绍教程《CellChat:细胞间相互作用分析利器》,然后R包作者也在B站做了直播介绍,cellchat作为一个细胞通讯分析的新兴R包,受到了广泛关注。教程也如雨后春笋般涌现。
The NCEP/NCAR Reanalysis Project is a joint project between the National Centers for Environmental Prediction (NCEP, formerly "NMC") and the National Center for Atmospheric Research (NCAR). The goal of this joint effort is to produce new atmospheric analyses using historical data as well as to produce analyses of the current atmospheric state (Climate Data Assimilation System, CDAS). The NCEP/NCAR Reanalysis 1 project is using a state-of-the-art analysis/forecast system to perform data assimilation using past data from 1948 to the present. The data have 6-hour temporal resolution (0000, 0600, 1200, and 1800 UTC) and 2.5 degree spatial resolution.
咱们书接上文,继续来说说Android数据读取,这回,我们要讲的是Sqlite数据库的相关操作。以一个实例开始吧:
在Android程序中,应用程序通过活动栈来管理Activity,活动栈中有多少个Activity对象,我们在退出程序的时候就要按多少下返回键(即要将活动栈中的所有Activity出栈),但是这样的话难免会有活动栈中存在相同的Activity对象,那么我们该如何解决这个问题呢。
The MOD17A2H V6 Gross Primary Productivity (GPP) product is a cumulative 8-day composite with a 500m resolution. The product is based on the radiation-use efficiency concept and can be potentially used as inputs to data models to calculate terrestrial energy, carbon, water cycle processes, and biogeochemistry of vegetation.
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IrrMapper is an annual classification of irrigation status in the 11 Western United States made at Landsat scale (i.e., 30 m) using the Random Forest algorithm, covering years 1986 - present. While the IrrMapper paper describes classification of four classes (i.e., irrigated, dryland, uncultivated, wetland), the dataset is converted to a binary classification of irrigated and non-irrigated. 'Irrigated' refers to the detection of any irrigation during the year. The IrrMapper random forest model was trained using an extensive geospatial database of land cover from each of four irrigated- and non-irrigated classes, including over 50,000 human-verified irrigated fields, 38,000 dryland fields, and over 500,000 square kilometers of uncultivated lands.
这里我们使用一个开源的库叫:PullToRefresh 开源地址:https://github.com/chenyoca/pull-to-refresh 下载地址:https://github.com
Quickstart Guide The Foreman installer is a collection of Puppet modules that installs everything required for a full working Foreman setup. It uses native OS packaging (e.g. RPM and .deb packages) and adds necessary configuration for the complete installation.
HashSet类继承AbstractSet,实现Set接口、实现了Cloneable接口以及序列化Serializable接口~如:
今天小编给大家介绍一个绘制图表时添加阴影(shadow) 的小技巧,R-ggshadow 可视化绘制。R-ggshadow包提供geom_shadowline()、geom_shadowpoint()和geom_shadowpath() 等多个绘制阴影的函数,同时还提供朋克风格绘图样式,接下来将通过几个小例子来了解一下这个包的魅力。
The MOD16A2 Version 6 Evapotranspiration/Latent Heat Flux product is an 8-day composite product produced at 500 meter pixel resolution. The algorithm used for the MOD16 data product collection is based on the logic of the Penman-Monteith equation, which includes inputs of daily meteorological reanalysis data along with MODIS remotely sensed data products such as vegetation property dynamics, albedo, and land cover.
Problem Description In the new year party, everybody will get a “special present”.Now it’s your turn to get your special present, a lot of presents now putting on the desk, and only one of them will be yours.Each present has a card number on it, and your present’s card number will be the one that different from all the others.For example, there are 5 present, and their card numbers are 1, 2, 3, 2, 1.so your present will be the one with the card number of 3, because 3 is the number that different from all the others.
The MYD17A2H V6 Gross Primary Productivity (GPP) product is a cumulative 8-day composite with a 500m resolution. The product is based on the radiation-use efficiency concept and can be potentially used as inputs to data models to calculate terrestrial energy, carbon, water cycle processes, and biogeochemistry of vegetation.
The MOD17A3H V6 product provides information about annual Net Primary Productivity (NPP) at 500m pixel resolution. Annual NPP is derived from the sum of the 45 8-day Net Photosynthesis (PSN) products (MOD17A2H) from the given year. The PSN value is the difference of the GPP and the Maintenance Respiration (MR) (GPP-MR).
下载链接:http://download.csdn.net/detail/a123demi/7511823
docker-compose非常适合开发、测试、快速验证原型,这个小工具让单机部署容器变得简洁、高效。正如我在《docker-compose,docker-stack前世今生》里讲,所有人都认为docker-compose是单机部署多容器的瑞士军刀,没有docker stack由deploy配置节体现的生产特性(多实例、滚动部署、故障重启、负载均衡)。
Design a data structure that supports all following operations in average O(1) time.
大家好,我是飞哥,本章节是理论+实操,干货满满,这里我将书中的数据用代码进行了实现,你可以下载相关的数据,用我整理好的代码进行操作,666!
本文将深入讨论HashSet实现原理的源码细节。在分析源码之前,首先我们需要对HashSet有一个基本的理解。
Problem Description In the new year party, everybody will get a “special present”.Now it’s your turn to get your special present, a lot of presents now putting on the desk, and only one of them will be yours.Each present has a card number on it, and your present’s card number will be the one that different from all the others, and you can assume that only one number appear odd times.For example, there are 5 present, and their card numbers are 1, 2, 3, 2, 1.so your present will be the one with the card number of 3, because 3 is the number that different from all the others.
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