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whittlebaggett8 · 6 years ago

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China and Russia Pose Different Problems for the US. They Need Different Solutions.

U.S. Director of Countrywide Intelligence Dan Coats noticed in the intelligence community’s most modern risk assessment that “China and Russia are additional aligned than at any place since the mid-1950s.” Despite the fact that U.S. observers have feared these kinds of an alignment for a long time, there is enough evidence that relations amongst the two are indeed nearer than they have been since the Sino-Soviet split in the early 1960s.

In July 2017, the two countries’ navies conducted a joint work out in the Baltic Sea for the 1st time. In September 2018, China participated in Russia’s once-a-year Vostok army physical exercise — an additional initial. Russia has also offered China innovative navy tools, together with an S-400 air defense process and 24 SU-35 fighter aircraft.

In accordance to Chinese federal government information, bilateral trade grew from $69.6 billion in 2016 to $84.2 billion in 2017 to $107.1 billion very last 12 months, marking the initial time that that figure surpassed $100 billion. Moreover, regardless of facing setbacks in diversifying away from the U.S. dollar, Beijing and Moscow are conducting far more of that trade, albeit nonetheless in small amounts, in their own currencies.

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Russia grew to become China’s largest supplier of crude oil in 2016, displacing Saudi Arabia, and it is contracted to offer China 1.3 trillion toes of cubic gasoline on a yearly basis for three decades, commencing this year, by means of its Energy of Siberia pipeline.

Finally, Chinese President Xi Jinping has frequented Moscow more than any other capital metropolis due to the fact he assumed power. As of August 2018, he and his Russian counterpart Vladimir Putin had fulfilled 26 moments. In June 2018, moreover, Xi gave Putin China’s initial-at any time friendship medal, calling him “my ideal, most intimate buddy.��

It is not surprising, then, that U.S. analysts are progressively worried by the multifaceted momentum in Sino-Russian relations. In a speech that he delivered at the Nobel Peace Prize Discussion board in Oslo in December 2016, previous U.S. Countrywide Protection Advisor Zbigniew Brzezinski (who passed absent in 2017) warned that Washington “must be wary of the good hazard that China and Russia could sort a strategic alliance, generated in part by their own inside, political, and ideological momentum, and in aspect by the improperly considered out guidelines of the United States.”

“Nothing,” he concluded, would be “more dangerous” to U.S. countrywide interests than such an result.

In the confront of strengthening ties between Beijing and Moscow, the White House’s National Stability Tactic and the Pentagon’s National Defense Technique would seem to address them as very similar strategic challenges. Sadly, nevertheless, acting on that depiction could hasten the really end result Brzezinski warned about.

The NSS, for example, asserts that both equally countries “challenge American electrical power, impact, and interests, trying to erode American security and prosperity. They are determined to make economies significantly less free of charge and considerably less good, to expand their militaries, and to management data and to repress their societies and grow their affect.” The NDS, in the meantime, contends that “[t]he central problem to U.S. prosperity and safety is the reemergence of very long-phrase, strategic level of competition by…revisionist powers. It is ever more clear that China and Russia want to condition a world constant with their authoritarian model—gaining veto authority over other nations’ economic, diplomatic, and protection conclusions.”

Although each countries unquestionably contest U.S. national interests, they do so in distinct means. It is noteworthy that Coats distinguished concerning the troubles that the two nations around the world pose when he testified prior to the Senate Pick Committee on Intelligence at the end of January: “Whereas with China, we must be concerned about the methodical and prolonged-term attempts to … match, or overtake our excellent international capabilities, Russia’s method depends on misdirection and obfuscation as it seeks to destabilize and diminish our standing in the planet.”

There are a number of causes to consider about China and Russia individually. First, while their relationship is certainly growing throughout military, economic, and political proportions, it is continue to far more anchored in shared grievances than in typical visions. Beijing and Moscow have prolonged criticized America’s support for common values, the centrality of the U.S. dollar in worldwide economical markets, and the U.S. presumption that countries with small to no involvement in planning the article-war order would in the end integrate themselves into it of their possess enlightened volition. It is a lot more difficult, nevertheless, to recognize what the contours of a shared Sino-Russian conception of globe purchase would be though they equally avow the want for a much more multipolar system, soon after all, couple of other nations would categorical a various wish, even longstanding U.S. allies in Europe and Asia. In addition, as Andrea Kendall-Taylor and David Shullman observed in Oct 2018, China and Russia are acting upon their grievances in techniques that, although “synergistic,” remain “different and seemingly uncoordinated.”

Second, the financial hole in between China and Russia is considerable and growing rapidly. In accordance to the World Financial institution, China’s nominal gross domestic item in 1992 was somewhat more compact than Russia’s ($427 billion compared to $460 billion). Just a quarter-century afterwards, in 2017, it was just about eight situations as big ($12.2 trillion vs . $1.6 trillion). Even nevertheless its economic climate is cooling, in addition, China’s development level stays over four moments that of Moscow’s — a divergence that makes sure that the imbalance amongst their electrical power capabilities and the consequent hole in between their talents to fulfill world-wide ambitions will expand apace.

While China holds the current postwar purchase to be obsolescent, it has been the chief beneficiary of that process, possibly excepting the United States. It presently seeks a gradual modification of that procedure, not a wholesale dissolution. In addition, as witnessed with the development of the Belt and Street Initiative, China has the ability to develop its industrial footprint globally, and it can credibly imagine a Sinocentric trading and financial commitment zone in Eurasia. With “Made in China 2025,” Beijing aspires to no more time be just an imitator of world-class know-how, but a creator, and the developing achieve of corporations such as Huawei indicates that aim is plausible.

Russia, by distinction, does not have the financial wherewithal to pose a gradualist problem, only the tactical savvy to be an opportunistic disruptor. A weak demographic outlook declining and now largely flat oil selling prices (the price tag of a barrel of crude oil is about 50 % of what it was five many years in the past) and many years of sanctions following its invasion of Ukraine and annexation of Crimea have all taken their toll. Exactly where Moscow at the time hoped to provide as a flourishing economic middleman in between Western Europe and the Asia-Pacific, it is now centered on the substantially additional modest intention of growing the Eurasian Economic Union, which presently comprises Armenia, Belarus, Kazakhstan, Kyrgyzstan, and Russia. Its principal lines of hard work — hiving off territory in its so-termed in close proximity to overseas, focusing on democratic nations around the world with disinformation functions, and leveraging and compounding Syria’s bloodshed to consolidate its foothold in the Middle East — mirror the truth that Russia has minor hope — or intention, it would seem — of reintegrating into the write-up-war buy. As an alternative, Moscow appears to be to have concluded that it can display its impact additional by destabilizing that procedure than by offering a coherent option.

Though both international locations request to change the status quo, then, only Russia has attacked neighboring nations around the world, annexed conquered territory, and supported insurgent forces trying to find to detach nonetheless extra. It also interferes in foreign elections and works to undermine European and Atlantic establishments. Though China is no harmless abroad — it proceeds to militarize the South China Sea and has engaged in the forced repatriation of Chinese citizens from Hong Kong and many Asian nations around the world — its growing impact derives generally from a lot more constructive measures this sort of as trade, expenditure, and improvement assistance.

The aforementioned discrepancies propose that the United States really should respond otherwise to a resurgent electricity centered on reaching economic and technological preeminence than to a declining electrical power centered on fomenting armed forces and ideological chaos. A single could argue that China seeks to speed up time Russia, to reverse it. That is, exactly where Beijing hopes to take its location as “the Middle Kingdom” in world affairs, Moscow waxes nostalgic for its previous imperium. While this formulation may perhaps appear to be overly reductionist, it captures the disparity in between China and Russia’s respective capacities and ambitions: the relationship concerning the two international locations is growing in worth as well as asymmetry.

If the United States carries on to lump China and Russia alongside one another in undifferentiated hostility, it may well effectively persuade them to operate much more assiduously and concertedly to undermine U.S. nationwide passions. Nor is it probably to succeed in driving a wedge among them. Beijing has tiny incentive to sign up for any hard work by Washington to counterbalance Moscow, which is a reputable supplier of energy and military devices. Nor does Russia pose a apparent challenge to any of China’s very important national pursuits. Russia, by distinction, has two immediate good reasons to be apprehensive: China has displaced it as the principal financial drive in Central Asia, and China appears to be increasingly intent on populating Russia’s Much East with Chinese laborers. Above the extended run, also, as Moscow grows additional dependent on China’s economic climate, Beijing could increasingly impede Russian makes an attempt to court docket China’s neighbors as portion of its “look east” effort and hard work. Still, unless Russia concludes that its route to extensive-phrase resuscitation is extra most likely to lie in rejoining the West than in bolstering its partnership with China, it may have to accept the indignity of at any time-greater supplication.

The United States can maintain Russia at bay by adapting current variations of protection, deterrence, and alliance relationships that it and its Western allies utilized from the Soviet Union through the Cold War, suggesting the relevance of strengthening the U.S. alliance system. Washington simply cannot, nonetheless, consist of China. It is in the realm of geoeconomics, alternatively than geopolitics, that the contest for environment leadership is possible to be established. America’s good results in this competitors will be determined in huge measure by how adeptly it operates in foreign markets and is effective with other folks to modernize an open, guidelines-dependent world financial buy.

James Dobbins is a senior fellow, Howard J. Shatz is a senior economist, and Ali Wyne is a policy analyst at the nonprofit, nonpartisan RAND Company. They are the authors of the new report “Russia Is a Rogue, Not a Peer China Is a Peer, Not a Rogue.”

The post China and Russia Pose Different Problems for the US. They Need Different Solutions. appeared first on Defence Online.

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alegendarystudentwonderland-blog · 7 years ago

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Bogalusa Louisiana Cheap car insurance quotes zip 70429

"Bogalusa Louisiana Cheap car insurance quotes zip 70429

Bogalusa Louisiana Cheap car insurance quotes zip 70429

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No proof of insurance ticket LOS ANGELES CA ?

I got pulled over for speeding. Got a ticket for no proof of insurance. but now i have insurance .. i am 17 and i just wanna know whats gonna happen tomorrow in court ? and on the ticket it says (((People of the state or California Vs. me))) whats going to happened in the court?, are there going to be people watching me ? and ima take my grandma ? also if i cant pay the fine can do community service ? how many hrs ?""

Do insurance companies raise rates if they know you are dyslexic?

If you're had an evaluation and it comes out as positive. Would insurance companies be likely to charge you higher rates?

Ideas for quick car with cheap insurance?

I'm 21 and looking to get a new car that's both fast and cheapish to insure. I have 2 years NCB, with a clean license and I've never crashed. I have looked at some hot hatches and fast saloons. I was surprised to find that insurance for a Golf GTi was more than for a C32 AMG, a 180mph car with 150bhp more! I'm tempted by the AMG, but servicing might suck my wallet dry... Are there any other options? Looking for 0-60 around 5 - 6s, good mid range power, 5 seats, and economy at least in the 20s""

Could switching to Geico really save you 15 percent or more on car insurance?

Does the early bird catch the worm? Geico. 15 minutes could save you 15 percent or more on car insurance.

What is the cost of insurance for a bugatti?

Why is everyone whining about being required to buy heath insurance?

you probably don't realize it, but you practically are required to buy car insurance. if you wreck and you have no insurance, it's not very pretty, especially for your money. Same thing with heath. if you get sick and don't have insurance, it's not very good! i don't understand why people so strongly oppose requirement to buy heath insurance, but don't even stop to think about car insurance, the same principle.""

Bogalusa Louisiana Cheap car insurance quotes zip 70429

Do you have to have insurance for...?

I was wondering, when renting an apartment are you suppose to have insurance?""

What is the best low cost health insurance for a small business owner with no employees?

I have two daughters, one fifteen years old in high school and the other is 21 and a college student. I am a 49 year old woman and in fair health. My husband is a Vietnam vet in fair health as well and will be eligible for medicare this year, so he will not need this insurance.""

How do i use my insurance ?

i get insurance through my job but i dont know how to use it. Feel dumb asking but i've never had to go to the doctors before and now i do. Can someone tell me a a little bit about it. Do i call the doctors office first and tell them what insurance i have and they figure it out. or do i call my insurance first and tell them i need to make an appointment? i did call and they sent me a list of all the doctors my insurance cover.

Car insurance and CVT?

What is insurancegroup 13? how much would insurance be for a 16yr old first time driver on Mazda MX-5 2.0i 2dr Powershift Convertible. And cvt means the gears change by them self? good/bad? thanks

Am I eligible for unemployment insurance in Alaska if I am a full-time student?

How to get insurance when pregnant?

whats the fastest way to get insurance when pregnant im already about 14 weeks

Where can i get less expensive car insurance for an 18 year old student with a 2000 mustang?

Well this may sound like a long shot, but I just recently bought my son a 2000 Ford Mustang, Now its insurance time, hes 18, gets A's in school and has had drivers ed. Why do the quotes from Progressive and esurance estimate its going to cost nearly $500 a month, even with a 1990 honda junker it still cost nearly $400 do these prices seem reasonable, i can't recall them being that high, when i first got insurance, thanks.""

How much does it cost for insurance on a scooter in europe?

I don't need an exact number, just give me a range.""

Insurance as a 17 year old on a 1973 Volkswagen Beetle?

I am 17, I am currently insured under my mums name on a BMW 320D. However I have my own car, which is a 1200 Beetle 2 Door Saloon, petrol and manual transmission. I live in Northern Ireland, UK. I was looking to get insured in it after I get it MOT'd and taxed. I know nothing about insurance on vintage cars, so anyone who has more experience in this field could you please tell me how to go around doing in. Who should I get insured with? I dont want to be spending more than 100 a month.""

Quoted insurance price?

I purchased insurance on the online weekend for my car. I paid the first monthly installment. Only to have a phone call telling me this price was wrong it was a computer error and the policy will cost a lot more. Do I have any rights here? Or must I simply front the rest of the cash to keep my car insured?

What is the relationship between the MOT & car insurance?

My daughter had an accident whilst without an MOT. She has fully comp insurance but as her car was stationary and she was hit from behind and she has an independent witness. The other driver's insurance will have to pay. But does her not having an MOT present any problems? Thanks.

Can you cancel your car insurance for a month and the get it back?

I'm going out of state for like 3-4 weeks and I was wondering if there's anyway to stop your car insurance for just that month and then Get it back when I come back without having to pay for it since that's kind of a waste. I have allstate

What is the cost of insurance for children and teens?

How much does insurance cost for a child from age 2 to 12? What about for a teen (from age 12 to 18)? Please list these costs separately. Thanks so very much. I really appreciate this. It's for a school project in case you are wondering. =)

17 year old car insurance?

Ive got a car and should (hopefully!) be passing my test soon but for reasons to complicated to list here lol I will only be able to drive it 2 weeks in easter time, 2 weeks in christmas time, 5 weeks around august and 4 days every 5 weeks, so by my bad maths thats just over 100 days. Are there any insurance companies for a 17 year old that you can get a fixed amount of days insurance, it seems such a waste to pay for 365 days if im only going to be able to use it for just under a third of the time. I read about some companies doing 60 or 90 days for young drivers but that might have been me mis-reading it, anyone hear about anything like that? Ive tried lowering the amount of miles on quotes but that hasnt reduced the price by much at all. I was hoping for quite a substantial saving. Any help would be greatly appreciated, Thanks.""

How can I put my girlfriend (8 1/2 years and still going strong) on my health/dental insurance?

Hi guys, so I have asked my job and it seems the only way I can add her to my health/dental insurance is if 1) we are married or 2) if i provide proof of living with her for a certain amount of years. There has to be some loophole because I really think it is ridiculous that we have been to together since we were 16 and I cant add her or help her in such a way. There is no possible way, in timeline, for us to qualify for such rules. 16-18 years old (in high school and lived with parents), 18-23 years old (Attended separate universities and lived in different cities), 23- 24 1/2 years old, (both living with parents back home, we alternate and stay at each others place, so have no set home or bills in our name, such as direct tv, electricity, internet, you name it. we are blessed with awesome parents) and yes we have though about just getting married, but no way... we are waiting until we are established and can fend for ourselves to make a decision like that, but yes we do want to get married some day, but not over screwing the government or other reasons. Also we live in california if that helps, since i know every state varies, thank s guys!! ^_^""

19 year old female just passed driving test. need cheap insurance quotes. is anyone else in the same situation?

i am a 19 year old female and have just passed my driving test. i know the insurance quotes i get are going to be expensive but does anyone know who is best to go with (cheapest) and is anyone else in the same situation? Thanks

Legal questions regarding my car insurance and getting my car painted?

My girlfriend recently put her car in the shop to get painted. Damage was done to the car and she had to put a $500 deductable to get the car painted and the insurance company paid $1500. she chose a shop to use and the check was made out to her and the shop was under her name on the check. The paint shop said she has to sign the check over for them to do the work. It has now been a month and they still have not completed any of the work. She keeps getting the run around with them. They are saying the have to bring the adjuster backout cause they found a dent they want to get fixed and then they found another dent. Basically we want the car out of there but how can we accomplish this and can we take legal action if needed, and what action can be done? Also on a side note we live in florida. As well she supposedly only has the check stub and no paperwork cause they never gave her any.""

How much does your motorcycle insurance cost?

Also say your gender, state, age, etc. P.S how much would it cost for a 18 year old male in NYC with a 600cc engine? ninja..""

Who Is The Best Car Insurance Company For A 17year old?

What medical insurance is cheap in California? ?

Is there medicaid n Cali ? Or just Oklahoma

Will my insurance go up?

I got a failure to obey a traffic control device ticket because I cut through a parking lot to go on a road. I paid the ticket today, wondering if this gets turned into insurance? I am hearing mixed reviews on this from looking online. I would hate to see my insurance go up at all for something so petty. I'm with state farm. Im 25 and just had my insurance go down a few months ago. Never had an accident and havnt had any other tickets since I was 18.""

I want to by a nissan s-cargo does anyone know anything about them or what the insurance cost is?

http://www.carfolio.com/specifications/models/car/?car=131516&Nissan-quote Nissan s-cargo this is the site for my car and I love it just curious what the insurance will before I make a offer and would like to hear opinions and stories about them.

What car modifications dont affect insurance price?

... if anyone knows any car modifications that dont affect insurance...

Will the check from the auto insurance company be in my name or my mom's?

under name of insured it has my mom's name and my name. the car is in my name. I hit a car and the insurance company is sending a check for the repair costs after the deductible. will the check be in my name or my mom's name??

Why are car insurance quotes on comparison sites so high?

I'm almost 17 and I'm hoping to learn to drive and buy a car, I was looking on some comparison sites to see what the insurance might be on some possible cars (ford KA, fiat sciento, nothing too fancy) but the quotes were ridiculously high? I know being 17 will mean expensive insurance but this was really expensive, they said the cheapest was around 6000 for third party. This is really high because I know loads of people who drive at 17 and their insurance ranges from 1800-3000. So, why is it so high and will it actually be this price when I come to pay the insurance?""

Bogalusa Louisiana Cheap car insurance quotes zip 70429

https://www.linkedin.com/pulse/virginia-unitedhealthcare-insurance-company-ryan-holmes/"

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oditile · 8 years ago

Text

Programming in R

From: http://manuals.bioinformatics.ucr.edu/home/programming-in-r

Author:

Thomas Girke

UC Riverside

Contents

1 Introduction

2 R Basics

3 Code Editors for R

4 Integrating R with Vim and Tmux

5 Finding Help

6 Control Structures

7 Functions

8 Useful Utilities

9 Running R Programs

10 Object-Oriented Programming (OOP)

11 Building R Packages

12 Reproducible Research by Integrating R with Latex or Markdown

13 R Programming Exercises

14 Translation of this Page

6.1 Conditional Executions

6.2 Loops

6.1.1 Comparison Operators

6.1.2 Logical Operators

6.1.3 If Statements

6.1.4 Ifelse Statements

6.2.1 For Loop

6.2.2 While Loop

6.2.3 Apply Loop Family

6.2.4 Other Loops

6.2.5 Improving Speed Performance of Loops

6.2.3.1 For Two-Dimensional Data Sets: apply

6.2.3.2 For Ragged Arrays: tapply

6.2.3.3 For Vectors and Lists: lapply and sapply

8.1 Debugging Utilities

8.2 Regular Expressions

8.3 Interpreting Character String as Expression

8.4 Time, Date and Sleep

8.5 Calling External Software with System Command

8.6 Miscellaneous Utilities

10.1 Define S4 Classes

10.2 Assign Generics and Methods

13.1 Exercise Slides

13.2 Sample Scripts

13.2.1 Batch Operations on Many Files

13.2.2 Large-scale Array Analysis

13.2.3 Graphical Procedures: Feature Map Example

13.2.4 Sequence Analysis Utilities

13.2.5 Pattern Matching and Positional Parsing of Sequences

13.2.6 Identify Over-Represented Strings in Sequence Sets

13.2.7 Translate DNA into Protein

13.2.8 Subsetting of Structure Definition Files (SDF)

13.2.9 Managing Latex BibTeX Databases

13.2.10 Loan Payments and Amortization Tables

13.2.11 Course Assignment: GC Content, Reverse & Complement

Introduction

[

Slides

] [

R Code

]

General Overview

One of the main attractions of using the

R (http://cran.at.r-project.org)

environment is the ease with which users can write their own programs and custom functions. The R programming syntax is extremely easy to learn, even for users with no previous programming experience. Once the basic R programming control structures are understood, users can use the R language as a powerful environment to perform complex custom analyses of almost any type of data.

Format of this Manual

In this manual all commands are given in code boxes, where the R code is printed in black, the comment text in blue and the output generated by R in green. All comments/explanations start with the standard comment sign '#' to prevent them from being interpreted by R as commands. This way the content in the code boxes can be pasted with their comment text into the R console to evaluate their utility. Occasionally, several commands are printed on one line and separated by a semicolon ';'. Commands starting with a '$' sign need to be executed from a Unix or Linux shell. Windows users can simply ignore them.

R Basics

The

R & BioConductor

manual provides a general introduction to the usage of the R environment and its basic command syntax.

Code Editors for R

Several excellent code editors are available that provide functionalities like R syntax highlighting, auto code indenting and utilities to send code/functions to the R console.

Basic code editors provided by Rguis

RStudio: GUI-based IDE for R

Vim-R-Tmux: R working environment based on vim and tmux

Emacs (ESS add-on package)

gedit and Rgedit

RKWard

Eclipse

Tinn-R

Notepad++ (NppToR)

Programming in R using Vim or Emacs Programming in R using RStudio

Integrating R with Vim and Tmux

Users interested in integrating R with vim and tmux may want to consult the Vim-R-Tmux configuration page.

Finding Help

Reference list on R programming (selection)

R Programming for Bioinformatics, by Robert Gentleman

Advanced R, by Hadley Wickham

S Programming, by W. N. Venables and B. D. Ripley

Programming with Data, by John M. Chambers

R Help & R Coding Conventions, Henrik Bengtsson, Lund University

Programming in R (Vincent Zoonekynd)

Peter's R Programming Pages, University of Warwick

Rtips, Paul Johnsson, University of Kansas

R for Programmers, Norm Matloff, UC Davis

High-Performance R, Dirk Eddelbuettel tutorial presented at useR-2008

C/C++ level programming for R, Gopi Goswami

Control Structures

Conditional Executions

Comparison Operators

equal: ==

not equal: !=

greater/less than: > <

greater/less than or equal: >= <=

Logical Operators

and: &

or: |

not: !

If StatementsIf statements operate on length-one logical vectors.

Syntax

if(cond1=true) { cmd1 } else { cmd2 }

Example

if(1==0) { print(1) } else { print(2) } [1] 2

Table of Contents

Avoid inserting newlines between '} else'.

Ifelse StatementsIfelse statements operate on vectors of variable length.

Syntax

ifelse(test, true_value, false_value)

Example

x <- 1:10 # Creates sample data ifelse(x<5 | x>8, x, 0) [1] 1 2 3 4 0 0 0 0 9 10

Table of Contents

Loops

The most commonly used loop structures in R are for, while and apply loops. Less common are repeat loops. The break function is used to break out of loops, and next halts the processing of the current iteration and advances the looping index.

For LoopFor loops are controlled by a looping vector. In every iteration of the loop one value in the looping vector is assigned to a variable that can be used in the statements of the body of the loop. Usually, the number of loop iterations is defined by the number of values stored in the looping vector and they are processed in the same order as they are stored in the looping vector.

Syntax

for(variable in sequence) { statements }

Example

mydf <- iris myve <- NULL # Creates empty storage container for(i in seq(along=mydf[,1])) { myve <- c(myve, mean(as.numeric(mydf[i, 1:3]))) # Note: inject approach is much faster than append with 'c'. See below for details. } myve [1] 3.333333 3.100000 3.066667 3.066667 3.333333 3.666667 3.133333 3.300000 [9] 2.900000 3.166667 3.533333 3.266667 3.066667 2.800000 3.666667 3.866667

Table of Contents

Example:

condition*

x <- 1:10 z <- NULL for(i in seq(along=x)) { if(x[i] < 5) { z <- c(z, x[i] - 1) } else { z <- c(z, x[i] / x[i]) } } z [1] 0 1 2 3 1 1 1 1 1 1

Table of Contents

Example:

stop on condition and print error message

x <- 1:10 z <- NULL for(i in seq(along=x)) { if (x[i]<5) { z <- c(z,x[i]-1) } else { stop("values need to be <5") } } Error: values need to be <5 z [1] 0 1 2 3

Table of Contents

While LoopSimilar to for loop, but the iterations are controlled by a conditional statement.

Syntax

while(condition) statements

Example

z <- 0 while(z < 5) { z <- z + 2 print(z) } [1] 2 [1] 4 [1] 6

Table of Contents

Apply Loop Family

For T

wo-Dimensional Data Sets: apply

Syntax

apply(X, MARGIN, FUN, ARGs)

X: array, matrix or data.frame; MARGIN: 1 for rows, 2 for columns, c(1,2) for both; FUN: one or more functions; ARGs: possible arguments for function

Example

## Example for applying predefined mean function apply(iris[,1:3], 1, mean) [1] 3.333333 3.100000 3.066667 3.066667 3.333333 3.666667 3.133333 3.300000 ... ## With custom function x <- 1:10 test <- function(x) {

# Defines some custom function if(x < 5) { x-1 } else { x / x } } apply(as.matrix(x), 1, test) #

Returns same result as previous for loop* [1] 0 1 2 3 1 1 1 1 1 1 ## Same as above but with a single line of code apply(as.matrix(x), 1, function(x) { if (x<5) { x-1 } else { x/x } })

[1] 0 1 2 3 1 1 1 1 1 1

Table of Contents

For Ragged Arrays: tapply

Applies a function to array categories of variable lengths (ragged array). Grouping is defined by factor.

Syntax

tapply(vector, factor, FUN)

Example

## Computes mean values of vector agregates defined by factor tapply(as.vector(iris[,4]), factor(iris[,5]), mean) setosa versicolor virginica 0.246 1.326 2.026 ## The aggregate function provides related utilities aggregate(iris[,1:4], list(iris$Species), mean) Group.1 Sepal.Length Sepal.Width Petal.Length Petal.Width 1 setosa 5.006 3.428 1.462 0.246 2 versicolor 5.936 2.770 4.260 1.326 3 virginica 6.588 2.974 5.552 2.026

Table of Contents

For Vectors and Lists: lapply and sapply

Both apply a function to vector or list objects. The function lapply returns a list, while sapply attempts to return the simplest data object, such as vector or matrix instead of list.

Syntax

lapply(X, FUN) sapply(X, FUN)

Example

## Creates a sample list mylist <- as.list(iris[1:3,1:3]) mylist $Sepal.Length [1] 5.1 4.9 4.7 $Sepal.Width [1] 3.5 3.0 3.2 $Petal.Length [1] 1.4 1.4 1.3 ## Compute sum of each list component and return result as list lapply(mylist, sum) $Sepal.Length [1] 14.7 $Sepal.Width [1] 9.7 $Petal.Length [1] 4.1 ##

Compute sum of each list component and return result as vector sapply(mylist, sum) Sepal.Length Sepal.Width Petal.Length 14.7 9.7 4.1

Table of Contents

Other Loops

Repeat Loop Syntax

repeat statement

Loop is repeated until a break is specified. This means there needs to be a second statement to test whether or not to break from the loop.

Example

z <- 0 repeat { z <- z + 1 print(z) if(z > 100) break() }

Table of Contents

Improving Speed Performance of LoopsLooping over very large data sets can become slow in R. However, this limitation can be overcome by eliminating certain operations in loops or avoiding loops over the data intensive dimension in an object altogether. The latter can be achieved by performing mainly vector-to-vecor or matrix-to-matrix computations which run often over 100 times faster than the corresponding for() or apply() loops in R. For this purpose, one can make use of the existing speed-optimized R functions (

e.g.:

rowSums, rowMeans, table, tabulate) or one can design custom functions that avoid expensive R loops by using vector- or matrix-based approaches. Alternatively, one can write programs that will perform all time consuming computations on the C-level.

(1)

Speed comparison of for loops with an append versus an inject step:

myMA <- matrix(rnorm(1000000), 100000, 10, dimnames=list(1:100000, paste("C", 1:10, sep=""))) results <- NULL system.time(for(i in seq(along=myMA[,1])) results <- c(results, mean(myMA[i,]))) user system elapsed 39.156 6.369 45.559 results <- numeric(length(myMA[,1])) system.time(for(i in seq(along=myMA[,1])) results[i] <- mean(myMA[i,])) user system elapsed 1.550 0.005 1.556

Table of Contents

The inject approach is 20-50 times faster than the append version.

(2)

Speed comparison of apply loop versus rowMeans for computing the mean for each row in a large matrix:

system.time(myMAmean <- apply(myMA, 1, mean)) user system elapsed 1.452 0.005 1.456 system.time(myMAmean <- rowMeans(myMA)) user system elapsed 0.005 0.001 0.006

Table of Contents

The rowMeans approach is over 200 times faster than the apply loop.

(3)

Speed comparison of apply loop versus vectorized approach for computing the standard deviation of each row:

system.time(myMAsd <- apply(myMA, 1, sd)) user system elapsed 3.707 0.014 3.721 myMAsd[1:4] 1 2 3 4 0.8505795 1.3419460 1.3768646 1.3005428 system.time(myMAsd <- sqrt((rowSums((myMA-rowMeans(myMA))^2)) / (length(myMA[1,])-1))) user system elapsed 0.020 0.009 0.028 myMAsd[1:4] 1 2 3 4 0.8505795 1.3419460 1.3768646 1.3005428

Table of Contents

The vector-based approach in the last step is over 200 times faster than the apply loop.

(4)

Example for computing the mean for any custom selection of columns without compromising the speed performance:

## In the following the colums are named according to their selection in myList myList <- tapply(colnames(myMA), c(1,1,1,2,2,2,3,3,4,4), list) myMAmean <- sapply(myList, function(x) rowMeans(myMA[,x])) colnames(myMAmean) <- sapply(myList, paste, collapse="_") myMAmean[1:4,] C1_C2_C3 C4_C5_C6 C7_C8 C9_C10 1 0.0676799 -0.2860392 0.09651984 -0.7898946 2 -0.6120203 -0.7185961 0.91621371 1.1778427 3 0.2960446 -0.2454476 -1.18768621 0.9019590 4 0.9733695 -0.6242547 0.95078869 -0.7245792

## Alternative to achieve the same result with similar performance, but in a much less elegant way myselect <- c(1,1,1,2,2,2,3,3,4,4) # The colums are named according to the selection stored in myselect myList <- tapply(seq(along=myMA[1,]), myselect, function(x) paste("myMA[ ,", x, "]", sep="")) myList <- sapply(myList, function(x) paste("(", paste(x, collapse=" + "),")/", length(x))) myMAmean <- sapply(myList, function(x) eval(parse(text=x))) colnames(myMAmean) <- tapply(colnames(myMA), myselect, paste, collapse="_") myMAmean[1:4,] C1_C2_C3 C4_C5_C6 C7_C8 C9_C10 1 0.0676799 -0.2860392 0.09651984 -0.7898946 2 -0.6120203 -0.7185961 0.91621371 1.1778427 3 0.2960446 -0.2454476 -1.18768621 0.9019590 4 0.9733695 -0.6242547 0.95078869 -0.7245792

Table of Contents

Functions

A very useful feature of the R environment is the possibility to expand existing functions and to easily write custom functions. In fact, most of the R software can be viewed as a series of R functions.

Syntax to define functions

myfct <- function(arg1, arg2, ...) { function_body }

Table of Contents

The value returned by a function is the value of the function body, which is usually an unassigned final expression,

e.g.:

return()

Syntax to call functions

myfct(arg1=..., arg2=...)

Table of Contents

Syntax Rules for Functions

General

Functions are defined by (1) assignment with the keyword function, (2) the declaration of arguments/variables (arg1, arg2, ...) and (3) the definition of operations (function_body) that perform computations on the provided arguments. A function name needs to be assigned to call the function (see below).

Naming

Function names can be almost anything. However, the usage of names of existing functions should be avoided.

Arguments

It is often useful to provide default values for arguments (

e.g.

:arg1=1:10). This way they don't need to be provided in a function call. The argument list can also be left empty (myfct <- function() { fct_body }) when a function is expected to return always the same value(s). The argument '...' can be used to allow one function to pass on argument settings to another.

Function body

The actual expressions (commands/operations) are defined in the function body which should be enclosed by braces. The individual commands are separated by semicolons or new lines (preferred).

Calling functions

Functions are called by their name followed by parentheses containing possible argument names. Empty parenthesis after the function name will result in an error message when a function requires certain arguments to be provided by the user. The function name alone will print the definition of a function.

Scope

Variables created inside a function exist only for the life time of a function. Thus, they are not accessible outside of the function. To force variables in functions to exist globally, one can use this special assignment operator: '<<-'. If a global variable is used in a function, then the global variable will be masked only within the function.

Example:

Function basics

myfct <- function(x1, x2=5) { z1 <- x1/x1 z2 <- x2*x2 myvec <- c(z1, z2) return(myvec) } myfct # prints definition of function myfct(x1=2, x2=5) # applies function to values 2 and 5 [1] 1 25 myfct(2, 5) # the argument names are not necessary, but then the order of the specified values becomes important myfct(x1=2) # does the same as before, but the default value '5' is used in this case

Table of Contents

Example:

Function with optional arguments

myfct2 <- function(x1=5, opt_arg) { if(missing(opt_arg)) { # 'missing()' is used to test whether a value was specified as an argument z1 <- 1:10 } else { z1 <- opt_arg } cat("my function returns:", "\n") return(z1/x1) } myfct2(x1=5) # performs calculation on default vector (z1) that is defined in the function body my function returns: [1] 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 myfct2(x1=5, opt_arg=30:20) # a custom vector is used instead when the optional argument (opt_arg) is specified my function returns: [1] 6.0 5.8 5.6 5.4 5.2 5.0 4.8 4.6 4.4 4.2 4.0

Table of Contents

Control utilities for functions: return, warning and stop

Return

The evaluation flow of a function may be terminated at any stage with the return function. This is often used in combination with conditional evaluations.

Stop

To stop the action of a function and print an error message, one can use the stop function.

Warning

To print a warning message in unexpected situations without aborting the evaluation flow of a function, one can use the function warning("...").

myfct <- function(x1) { if (x1>=0) print(x1) else stop("This function did not finish, because x1 < 0") warning("Value needs to be > 0") } myfct(x1=2) [1] 2 Warning message: In myfct(x1 = 2) : Value needs to be > 0 myfct(x1=-2) Error in myfct(x1 = -2) : This function did not finish, because x1 < 0

Table of Contents

Useful Utilities

Debugging Utilities

Several debugging utilities are available for R. The most important utilities are: traceback(), browser(), options(error=recover), options(error=NULL) and debug(). The

Debugging in R

page provides an overview of the available resources.

Regular Expressions

R's regular expression utilities work similar as in other languages. To learn how to use them in R, one can consult the main help page on this topic with ?regexp. The following gives a few basic examples.

The grep function can be used for finding patterns in strings, here letter A in vector month.name.

month.name[grep("A", month.name)] [1] "April" "August"

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Example for using regular expressions to substitute a pattern by another one using the sub/gsub function with a back reference. Remember: single escapes '\' need to be double escaped '\\' in R.

gsub("(i.*a)", "xxx_\\1", "virginica", perl = TRUE) [1] "vxxx_irginica"

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Example for split and paste functions

x <- gsub("(a)", "\\1_", month.name[1], perl=TRUE) # performs substitution with back reference which inserts in this example a '_' character x [1] "Ja_nua_ry" strsplit(x, "_") # splits string on inserted character from above [[1]] [1] "Ja" "nua" "ry" paste(rev(unlist(strsplit(x, NULL))), collapse="") # reverses character string by splitting first all characters into vector fields and then collapsing them with paste [1] "yr_aun_aJ"

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Example for importing specific lines in a file with a regular expression. The following example demonstrates the retrieval of specific lines from an external file with a regular expression. First, an external file is created with the cat function, all lines of this file are imported into a vector with readLines, the specific elements (lines) are then retieved with the grep function, and the resulting lines are split into vector fields with strsplit.

cat(month.name, file="zzz.txt", sep="\n") x <- readLines("zzz.txt") x <- x[c(grep("^J", as.character(x), perl = TRUE))] t(as.data.frame(strsplit(x, "u"))) [,1] [,2] c..Jan....ary.. "Jan" "ary" c..J....ne.. "J" "ne" c..J....ly.. "J" "ly"

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Interpreting Character String as Expression

Example

mylist <- ls() # generates vector of object names in session mylist[1] # prints name of 1st entry in vector but does not execute it as expression that returns values of 10th object get(mylist[1]) # uses 1st entry name in vector and executes it as expression eval(parse(text=mylist[1])) # alternative approach to obtain similar result

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Time, Date and Sleep

Example

system.time(ls()) # returns CPU (and other) times that an expression used, here ls() user system elapsed 0 0 0 date() # returns the current system date and time [1] "Wed Dec 11 15:31:17 2012" Sys.sleep(1) # pause execution of R expressions for a given number of seconds (e.g. in loop)

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Calling External Software with System CommandThe system command allows to call any command-line software from within R on Linux, UNIX and OSX systems.

system("...") # provide under '...' command to run external software e.g. Perl, Python, C++ programs

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Related utilities on Windows operating systems

x <- shell("dir", intern=T) # reads current working directory and assigns to file shell.exec("C:/Documents and Settings/Administrator/Desktop/my_file.txt") # opens file with associated program

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Miscellaneous Utilities

(1)

Batch import and export of many files.

In the following example all file names ending with *.txt in the current directory are first assigned to a list (the '$' sign is used to anchor the match to the end of a string). Second, the files are imported one-by-one using a for loop where the original names are assigned to the generated data frames with the assign function. Consult help with ?read.table to understand arguments row.names=1 and comment.char = "A". Third, the data frames are exported using their names for file naming and appending the extension *.out.

files <- list.files(pattern=".txt$") for(i in files) { x <- read.table(i, header=TRUE, comment.char = "A", sep="\t") assign(i, x) print(i) write.table(x, paste(i, c(".out"), sep=""), quote=FALSE, sep="\t", col.names = NA) }

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(2)

Running Web Applications (basics on designing web client/crawling/scraping scripts in R)

Example for obtaining MW values for peptide sequences from the

EXPASY's pI/MW Tool

web page.

myentries <- c("MKWVTFISLLFLFSSAYS", "MWVTFISLL", "MFISLLFLFSSAYS") myresult <- NULL for(i in myentries) { myurl <- paste("http://ca.expasy.org/cgi-bin/pi_tool?protein=", i, "&resolution=monoisotopic", sep="") x <- url(myurl) res <- readLines(x) close(x) mylines <- res[grep("Theoretical pI/Mw:", res)] myresult <- c(myresult, as.numeric(gsub(".*/ ", "", mylines))) print(myresult) Sys.sleep(1) # halts process for one sec to give web service a break } final <- data.frame(Pep=myentries, MW=myresult) cat("\n The MW values for my peptides are:\n") final Pep MW 1 MKWVTFISLLFLFSSAYS 2139.11 2 MWVTFISLL 1108.60 3 MFISLLFLFSSAYS 1624.82

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Running R Programs

(1)

Executing an R script from the R console

source("my_script.R")

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(2.1)

Syntax for running R programs from the command-line. Requires in first line of my_script.R the following statement: #!/usr/bin/env Rscript

$ Rscript my_script.R # or just ./myscript.R after making file executable with 'chmod +x my_script.R'

All commands starting with a '$' sign need to be executed from a Unix or Linux shell.

(2.2)

Alternatively, one can use the following syntax to run R programs in BATCH mode from the command-line.

$ R CMD BATCH [options] my_script.R [outfile]

The output file lists the commands from the script file and their outputs. If no outfile is specified, the name used is that of infile and .Rout is appended to outfile. To stop all the usual R command line information from being written to the outfile, add this as first line to my_script.R file: options(echo=FALSE). If the command is run like this R CMD BATCH --no-save my_script.R, then nothing will be saved in the .Rdata file which can get often very large. More on this can be found on the help pages: $ R CMD BATCH --help or ?BATCH.

(2.3)

Another alternative for running R programs as silently as possible.

$ R --slave < my_infile > my_outfile

Argument --slave makes R run as 'quietly' as possible.

(3)

Passing Command-Line Arguments to R Programs

Create an R script, here named test.R, like this one:

######################

myarg <- commandArgs()

print(iris[1:myarg[6], ])

######################

Then run it from the command-line like this:

$ Rscript test.R 10

In the given example the number 10 is passed on from the command-line as an argument to the R script which is used to return to STDOUT the first 10 rows of the iris sample data. If several arguments are provided, they will be interpreted as one string that needs to be split it in R with the strsplit function.

(4)

Submitting R script to a Linux cluster via Torque

Create the following shell script my_script.sh

#################################

#!/bin/bash

cd $PBS_O_WORKDIR

R CMD BATCH --no-save my_script.R

#################################

This script doesn't need to have executable permissions. Use the following qsub command to send this shell script to the Linux cluster from the directory where the R script my_script.R is located. To utilize several CPUs on the Linux cluster, one can divide the input data into several smaller subsets and execute for each subset a separate process from a dedicated directory.

$ qsub my_script.sh

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Here is a short R script that generates the required files and directories automatically and submits the jobs to the nodes:

submit2cluster.R

. For more details, see also this

'Tutorial on Parallel Programming in R' by Hanna Sevcikova

(5)

Submitting jobs to Torque or any other queuing/scheduling system via the

BatchJobs

package. This package provides one of the most advanced resources for submitting jobs to queuing systems from within R. A related package is

BiocParallel

from Bioconductor which extends many functionalities of BatchJobs to genome data analysis. Useful documentation for BatchJobs:

Technical Report

GitHub page

Slide Show

Config samples

library(BatchJobs) loadConfig(conffile = ".BatchJobs.R") ## Loads configuration file. Here .BatchJobs.R containing just this line: ## cluster.functions <- makeClusterFunctionsTorque("torque.tmpl") ## The template file torque.tmpl is expected to be in the current working ## director. It can be downloaded from here: ## https://github.com/tudo-r/BatchJobs/blob/master/examples/cfTorque/simple.tmpl getConfig() # Returns BatchJobs configuration settings reg <- makeRegistry(id="BatchJobTest", work.dir="results") ## Constructs a registry object. Output files from R will be stored under directory "results", ## while the

standard objects from BatchJobs will be stored in the directory "BatchJobTest-files". print(reg) ## Some test function f <- function(x) { system("ls -al >> test.txt") x } ## Adds jobs to registry object (here reg) ids <- batchMap(reg, fun=f, 1:10) print(ids) showStatus(reg) ## Submit jobs or chunks of jobs to batch system via cluster function done <- submitJobs(reg, resources=list(walltime=3600, nodes="1:ppn=4", memory="4gb")) ## Load results from BatchJobTest-files/jobs/01/1-result.RData loadResult(reg, 1)

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Object-Oriented Programming (OOP)

R supports two systems for object-oriented programming (OOP). An older S3 system and a more recently introduced S4 system. The latter is more formal, supports multiple inheritance, multiple dispatch and introspection. Many of these features are not available in the older S3 system. In general, the OOP approach taken by R is to separate the class specifications from the specifications of generic functions (function-centric system). The following introduction is restricted to the S4 system since it is nowadays the preferred OOP method for R. More information about OOP in R can be found in the following introductions:

Vincent Zoonekynd's introduction to S3 Classes

S4 Classes in 15 pages

Christophe Genolini's S4 Intro

The R.oo package

BioC Course: Advanced R for Bioinformatics

Programming with R by John Chambers

and

R Programming for Bioinformatics by Robert Gentleman

Define S4 Classes

(A)

Define S4 Classes with

setClass() and new()

y <- matrix(1:50, 10, 5) # Sample data set setClass(Class="myclass", representation=representation(a="ANY"), prototype=prototype(a=y[1:2,]), # Defines default value (optional) validity=function(object) { # Can be defined in a separate step using setValidity if(class(object@a)!="matrix") { return(paste("expected matrix, but obtained", class(object@a))) } else { return(TRUE) } } )

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The setClass function defines classes. Its most important arguments are

Class: the name of the class

representation: the slots that the new class should have and/or other classes that this class extends.

prototype: an object providing default data for the slots.

contains: the classes that this class extends.

validity, access, version: control arguments included for compatibility with S-Plus.

where: the environment to use to store or remove the definition as meta data.

(B)

The function new creates an instance of a class (here myclass)

myobj <- new("myclass", a=y) myobj An object of class "myclass" Slot "a": [,1] [,2] [,3] [,4] [,5] [1,] 1 11 21 31 41 [2,] 2 12 22 32 42 ... new("myclass", a=iris) # Returns an error message due to wrong input type (iris is data frame) Error in validObject(.Object) : invalid class “myclass” object: expected matrix, but obtained data.frame

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Its arguments are:

Class: the name of the class

...: Data to include in the new object with arguments according to slots in class definition.

(C)

A more generic way of creating class instances is to define an initialization method (details below)

setMethod("initialize", "myclass", function(.Object, a) { .Object@a <- a/a .Object }) new("myclass", a = y) [1] "initialize" new("myclass", a = y)> new("myclass", a = y) An object of class "myclass" Slot "a": [,1] [,2] [,3] [,4] [,5] [1,] 1 1 1 1 1 [2,] 1 1 1 1 1 ...

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(D)

Usage and helper functions

myobj@a # The '@' extracts the contents of a slot. Usage should be limited to internal functions! initialize(.Object=myobj, a=as.matrix(cars[1:3,])) # Creates a new S4 object from an old one. # removeClass("myclass") # Removes object from current session; does not apply to associated methods.

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(E)

Inheritance: allows to define new classes that inherit all properties (

e.g.

data slots, methods) from their existing parent classes

setClass("myclass1", representation(a = "character", b = "character")) setClass("myclass2", representation(c = "numeric", d = "numeric")) setClass("myclass3", contains=c("myclass1", "myclass2")) new("myclass3", a=letters[1:4], b=letters[1:4], c=1:4, d=4:1) An object of class "myclass3" Slot "a": [1] "a" "b" "c" "d" Slot "b": [1] "a" "b" "c" "d" Slot "c": [1] 1 2 3 4 Slot "d": [1] 4 3 2 1 getClass("myclass1") Class "myclass1" [in ".GlobalEnv"] Slots: Name: a b Class: character character Known Subclasses: "myclass3" getClass("myclass2") Class "myclass2" [in ".GlobalEnv"] Slots: Name: c d Class: numeric numeric Known Subclasses: "myclass3" getClass("myclass3") Class "myclass3" [in ".GlobalEnv"] Slots: Name: a b c d Class: character character numeric numeric Extends: "myclass1", "myclass2"

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The argument contains allows to extend existing classes; this propagates all slots of parent classes.

(F)

Coerce objects to another class

setAs(from="myclass", to="character", def=function(from) as.character(as.matrix(from@a))) as(myobj, "character") [1] "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12" "13" "14" "15" ...

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(G)

Virtual classes are constructs for which no instances will be or can be created. They are used to link together classes which may have distinct representations (e.g. cannot inherit from each other) but for which one wants to provide similar functionality. Often it is desired to create a virtual class and to then have several other classes extend it. Virtual classes can be defined by leaving out the representation argument or including the class VIRTUAL:

setClass("myVclass") setClass("myVclass", representation(a = "character", "VIRTUAL"))

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(H)

Functions to introspect classes

getClass("myclass")

getSlots("myclass")

slotNames("myclass")

extends("myclass2")

Assign Generics and MethodsAssign generics and methods with setGeneric() and setMethod()

(A)

Accessor function (to avoid usage of '@')

setGeneric(name="acc", def=function(x) standardGeneric("acc")) setMethod(f="acc", signature="myclass", definition=function(x) { return(x@a) }) acc(myobj) [,1] [,2] [,3] [,4] [,5] [1,] 1 11 21 31 41 [2,] 2 12 22 32 42 ...

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(B.1)

Replacement method using custom accessor function (acc <-)

setGeneric(name="acc<-", def=function(x, value) standardGeneric("acc<-")) setReplaceMethod(f="acc", signature="myclass", definition=function(x, value) { x@a <- value return(x) }) ## After this the following replace operations with 'acc' work on new object class acc(myobj)[1,1] <- 999 # Replaces first value colnames(acc(myobj)) <- letters[1:5] # Assigns new column names rownames(acc(myobj)) <- letters[1:10] # Assigns new row names myobj An object of class "myclass" Slot "a": a b c d e a 999 11 21 31 41 b 2 12 22 32 42 ...

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(B.2)

Replacement method using "[" operator ([<-)

setReplaceMethod(f="[", signature="myclass", definition=function(x, i, j, value) { x@a[i,j] <- value return(x) }) myobj[1,2] <- 999 myobj An object of class "myclass" Slot "a": a b c d e a 999 999 21 31 41 b 2 12 22 32 42 ...

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(C)

Define behavior of "[" subsetting operator (no generic required!)

setMethod(f="[", signature="myclass", definition=function(x, i, j, ..., drop) { x@a <- x@a[i,j] return(x) }) myobj[1:2,] # Standard subsetting works now on new class An object of class "myclass" Slot "a": a b c d e a 999 999 21 31 41 b 2 12 22 32 42 ...

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(D)

Define print behavior

setMethod(f= show", signature="myclass", definition=function(object) { cat("An instance of ", "\"", class(object), "\"", " with ", length(acc(object)[,1]), " elements", "\n", sep="") if(length(acc(object)[,1])>=5) { print(as.data.frame(rbind(acc(object)[1:2,], ...=rep("...", length(acc(object)[1,])), acc(object)[(length(acc(object)[,1])-1):length(acc(object)[,1]),]))) } else { print(acc(object)) }}) myobj # Prints object with custom method An instance of "myclass" with 10 elements a b c d e a 999 999 21 31 41 b 2 12 22 32 42 ... ... ... ... ... ... i 9 19 29 39 49 j 10 20 30 40 50

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(E)

Define a data specific function (here randomize row order)

setGeneric(name="randomize", def=function(x) standardGeneric("randomize")) setMethod(f="randomize", signature="myclass", definition=function(x) { acc(x)[sample(1:length(acc(x)[,1]), length(acc(x)[,1])), ] }) randomize(myobj) a b c d e j 10 20 30 40 50 b 2 12 22 32 42 ...

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(F)

Define a graphical plotting function and allow user to access it with generic plot function

setMethod(f="plot", signature="myclass", definition=function(x, ...) { barplot(as.matrix(acc(x)), ...) }) plot(myobj)

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(G)

Functions to inspect methods

showMethods(class="myclass")

findMethods("randomize")

getMethod("randomize", signature="myclass")

existsMethod("randomize", signature="myclass")

Building R Packages

To get familiar with the structure, building and submission process of R packages, users should carefully read the documentation on this topic available on these sites:

Writing R Extensions, R web site

R Packages, by Hadley Wickham

R Package Primer, by Karl Broman

Package Guidelines, Bioconductor

Advanced R Programming Class, Bioconductor

Short Overview of Package Building Process

(A)

Automatic package building with the package.skeleton function:

package.skeleton(name="mypackage", code_files=c("script1.R", "script2.R"))

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Note: this is an optional but very convenient function to get started with a new package. The given example will create a directory named mypackage containing the skeleton of the package for all functions, methods and classes defined in the R script(s) passed on to the code_files argument. The basic structure of the package directory is

described here

. The package directory will also contain a file named 'Read-and-delete-me' with the following instructions for completing the package:

Edit the help file skeletons in man, possibly combining help files for multiple functions.

Edit the exports in NAMESPACE, and add necessary imports.

Put any C/C++/Fortran code in src.

If you have compiled code, add a useDynLib() directive to NAMESPACE.

Run R CMD build to build the package tarball.

Run R CMD check to check the package tarball.

Read Writing R Extensions for more information.

(B)

Once a package skeleton is available one can build the package from the command-line (Linux/OS X):

$ R CMD build mypackage

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This will create a tarball of the package with its version number encoded in the file name, e.g.: mypackage_1.0.tar.gz.

Subsequently, the package tarball needs to be checked for errors with:

$ R CMD check mypackage_1.0.tar.gz

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All issues in a package's source code and documentation should be addressed until R CMD check returns no error or warning messages anymore.

(C)

Install package from source:

Linux:

install.packages("mypackage_1.0.tar.gz", repos=NULL)

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OS X:

install.packages("mypackage_1.0.tar.gz", repos=NULL, type="source")

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Windows requires a zip archive for installing R packages, which can be most conveniently created from the command-line (Linux/OS X) by installing the package in a local directory (here tempdir) and then creating a zip archive from the installed package directory:

$ mkdir tempdir $ R CMD INSTALL -l tempdir mypackage_1.0.tar.gz $ cd tempdir $ zip -r mypackage mypackage ## The resulting mypackage.zip archive can be installed under Windows like this: install.packages("mypackage.zip", repos=NULL)

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This procedure only works for packages which do not rely on compiled code (C/C++). Instructions to fully build an R package under Windows can be

found here

and

here

(D)

Maintain/expand an existing package:

Add new functions, methods and classes to the script files in the ./R directory in your package

Add their names to the NAMESPACE file of the package

Additional *.Rd help templates can be generated with the prompt*() functions like this:

source("myscript.R") # imports functions, methods and classes from myscript.R prompt(myfct) # writes help file myfct.Rd promptClass("myclass") # writes file myclass-class.Rd promptMethods("mymeth") # writes help file mymeth.Rd

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The resulting *.Rd help files can be edited in a text editor and properly rendered and viewed from within R like this:

library(tools) Rd2txt("./mypackage/man/myfct.Rd") # renders *.Rd files as they look in final help pages checkRd("./mypackage/man/myfct.Rd") # checks *.Rd help file for problems

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(E)

Submit package to a public repository

The best way of sharing an R package with the community is to submit it to one of the main R package repositories, such as CRAN or Bioconductor. The details about the submission process are given on the corresponding repository submission pages:

Submitting to Bioconductor (guidelines, submission, svn control, build/checks release, build/checks devel)

Submitting to CRAN

Reproducible Research by Integrating R with Latex or Markdown

See Sweave/Stangle sections of Slide Show for this manual

Sweave Manual

R Markdown

knitr manual

RStudio's Rpubs page

R Programming Exercises

Exercise Slides[

Slides

] [

Exercises

] [

Additional Exercises

]

Download on of the above exercise files, then start editing this R source file with a programming text editor, such as Vim, Emacs or one of the R GUI text editors. Here is the

HTML version

of the code with syntax coloring.

Sample Scripts

Batch Operations on Many Files

## (1) Start R from an empty test directory ## (2) Create some files as sample data for(i in month.name) { mydf <- data.frame(Month=month.name, Rain=runif(12, min=10, max=100), Evap=runif(12, min=1000, max=2000)) write.table(mydf, file=paste(i , ".infile", sep=""), quote=F, row.names=F, sep="\t") } ## (3) Import created files, perform calculations and export to renamed files files <- list.files(pattern=".infile$") for(i in seq(along=files)) { # start for loop with numeric or character vector; numeric vector is often more flexible x <- read.table(files[i], header=TRUE, row.names=1, comment.char = "A", sep="\t") x <- data.frame(x, sum=apply(x, 1, sum), mean=apply(x, 1, mean)) # calculates sum and mean for each data frame assign(files[i], x) # generates data frame object and names it after content in variable 'i' print(files[i], quote=F) # prints loop iteration to screen to check its status write.table(x, paste(files[i], c(".out"), sep=""), quote=FALSE, sep="\t", col.names = NA) } ## (4) Same as above, but file naming by index data frame. This way one can organize file names by external table. name_df <- data.frame(Old_name=sort(files), New_name=sort(month.abb)) for(i in seq(along=name_df[,1])) { x <- read.table(as.vector(name_df[i,1]), header=TRUE, row.names=1, comment.char = "A", sep="\t") x <- data.frame(x, sum=apply(x, 1, sum), mean=apply(x, 1, mean)) assign(as.vector(name_df[i,2]), x) # generates data frame object and names it after 'i' entry in column 2 print(as.vector(name_df[i,1]), quote=F) write.table(x, paste(as.vector(name_df[i,2]), c(".out"), sep=""), quote=FALSE, sep="\t", col.names = NA) } ## (5) Append content of all input files to one file. files <- list.files(pattern=".infile$") all_files <- data.frame(files=NULL, Month=NULL, Gain=NULL , Loss=NULL, sum=NULL, mean=NULL) # creates empty data frame container for(i in seq(along=files)) { x <- read.table(files[i], header=TRUE, row.names=1, comment.char = "A", sep="\t") x <- data.frame(x, sum=apply(x, 1, sum), mean=apply(x, 1, mean)) x <- data.frame(file=rep(files[i], length(x[,1])), x) # adds file tracking column to x all_files <- rbind(all_files, x) # appends data from all files to data frame 'all_files' write.table(all_files, file="all_files.xls", quote=FALSE, sep="\t", col.names = NA) } ## (6) Write the above code into a text file and execute it with the commands 'source' and 'BATCH'. source("my_script.R") # execute from R console $ R CMD BATCH my_script.R # execute from shell

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Large-scale Array Analysis

Sample script to perform large-scale expression array analysis with complex queries: lsArray.R. To demo what the script does, run it like this:

source("http://faculty.ucr.edu/~tgirke/Documents/R_BioCond/My_R_Scripts/lsArray.R")

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Graphical Procedures: Feature Map Example

Script to plot feature maps of genes or chromosomes: featureMap.R. To demo what the script does, run it like this:

source("http://faculty.ucr.edu/~tgirke/Documents/R_BioCond/My_R_Scripts/featureMap.txt")

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Sequence Analysis UtilitiesIncludes sequence batch import, sub-setting, pattern matching, AA Composition, NEEDLE, PHYLIP, etc. The script '

sequenceAnalysis.R

' demonstrates how R can be used as a powerful tool for managing and analyzing large sets of biological sequences. This example also shows how easy it is to integrate R with the

EMBOSS

project or other external programs. The script provides the following functionality:

Batch sequence import into R data frame

Motif searching with hit statistics

Analysis of sequence composition

All-against-all sequence comparisons

Generation of phylogenetic trees

To demonstrate the utilities of the script, users can simply execute it from R with the following source command:

source("http://faculty.ucr.edu/~tgirke/Documents/R_BioCond/My_R_Scripts/sequenceAnalysis.txt")

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Pattern Matching and Positional Parsing of Sequences

Functions for importing sequences into R, retrieving reverse and complement of nucleotide sequences, pattern searching, positional parsing and exporting search results in HTML format: patternSearch.R. To demo what the script does, run it like this:

source("http://faculty.ucr.edu/~tgirke/Documents/R_BioCond/My_R_Scripts/patternSearch.R")

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Identify Over-Represented Strings in Sequence Sets

Functions for finding over-represented words in sets of DNA, RNA or protein sequences: wordFinder.R. To demo what the script does, run it like this:

source("http://faculty.ucr.edu/~tgirke/Documents/R_BioCond/My_R_Scripts/wordFinder.R")

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Translate DNA into Protein

Script 'translateDNA.R' for translating NT sequences into AA sequences (required codon table). To demo what the script does, run it like this:

source("http://faculty.ucr.edu/~tgirke/Documents/R_BioCond/My_R_Scripts/translateDNA.R")

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Subsetting of Structure Definition Files (SDF)

Script for importing and subsetting SDF files: sdfSubset.R. To demo what the script does, run it like this:

source("http://faculty.ucr.edu/~tgirke/Documents/R_BioCond/My_R_Scripts/sdfSubset.R")

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Managing Latex BibTeX Databases

Script for importing BibTeX databases into R, retrieving the individual references with a full-text search function and viewing the results in R or in HubMed: BibTex.R. To demo what the script does, run it like this:

source("http://faculty.ucr.edu/~tgirke/Documents/R_BioCond/My_R_Scripts/BibTex.R")

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Loan Payments and Amortization Tables

This script calculates monthly and annual mortgage or loan payments, generates amortization tables and plots the results: mortgage.R. To demo what the script does, run it like this:

source("http://faculty.ucr.edu/~tgirke/Documents/R_BioCond/My_R_Scripts/mortgage.R")

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Course Assignment: GC Content, Reverse & Complement

Apply the above information to write a function that calculates for a set of DNA sequences their GC content and generates their reverse and complement. Here are some useful commands that can be incorporated in this function:

## Generate an example data frame with ID numbers and DNA sequences fx <- function(test) { x <- as.integer(runif(20, min=1, max=5)) x[x==1] <- "A"; x[x==2] <- "T"; x[x==3] <- "G"; x[x==4] <- "C" paste(x, sep = "", collapse ="") } z1 <- c() for(i in 1:50) { z1 <- c(fx(i), z1) } z1 <- data.frame(ID=seq(along=z1), Seq=z1) z1 ## Write each character of sequence into separate vector field and reverse its order my_split <- strsplit(as.character(z1[1,2]),"") my_rev <- rev(my_split[[1]]) paste(my_rev, collapse="") ## Generate the sequence complement by replacing G|C|A|T by C|G|T|A ## Use 'apply' or 'for loop' to apply the above operations to all sequences in sample data frame 'z1' ## Calculate in the same loop the GC content for each sequence using the following command table(my_split[[1]])/length(my_split[[1]])

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