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+# Intro to Computing
+
+*Slides that go with this lesson can be found [here](slides/lesson1_slides.html).*
+
+## Goals of the course
+
+-   Fundamental concepts in high-level programming languages (R, Python, Julia, WDL, etc.) that is transferable: *How do programs run, and how do we solve problems using functions and data structures?*
+
+-   Beginning of data science fundamentals: *How do you translate your scientific question to a data wrangling problem and answer it?*
+
+    ![Data science workflow](https://d33wubrfki0l68.cloudfront.net/571b056757d68e6df81a3e3853f54d3c76ad6efc/32d37/diagrams/data-science.png){width="450"}
+
+-   Find a nice balance between the two throughout the course: we will try to reproduce a figure from a scientific publication using new data.
+
+## What is a computer program?
+
+-   A sequence of instructions to manipulate data for the computer to execute.
+
+-   A series of translations: English \<-\> Programming Code for Interpreter \<-\> Machine Code for Central Processing Unit (CPU)
+
+We will focus on English \<-\> Programming Code for R Interpreter in this class.
+
+More importantly: **How we organize ideas \<-\> Instructing a computer to do something**.
+
+## A programming language has following elements: {#a-programming-language-has-following-elements}
+
+-   Grammar structure (simple building blocks)
+
+-   Means of combination to analyze and create content (examples around genomics provided, and your scientific creativity is strongly encouraged!)
+
+-   Means of abstraction for modular and reusable content (data structures, functions)
+
+-   Culture (emphasis on open-source, collaborative, reproducible code)
+
+Requires a lot of practice to be fluent!
+
+## What is R and why should I use it?
+
+It is a:
+
+-   Dynamic programming interpreter
+
+-   Highly used for data science, visualization, statistics, bioinformatics
+
+-   Open-source and free; easy to create and distribute your content; quirky culture
+
+## R vs. Python as a first language
+
+In terms of our goals, recall:
+
+-   Fundamental concepts in high-level programming languages
+
+-   Beginning of data science fundamentals
+
+There are a lot of nuances and debates, but I argue that Python is a better learning environment for the former and R is better for the latter.
+
+Ultimately, either should be okay! Perhaps more importantly, *consider what your research group and collaborator are more comfortable with*.
+
+## Posit Cloud Setup
+
+Posit Cloud/RStudio is an Integrated Development Environment (IDE). Think about it as Microsoft Word to a plain text editor. It provides extra bells and whistles to using R that is easier for the user.
+
+Today, we will pay close attention to:
+
+-   Script editor: where sequence of instructions are typed and saved as a text document as a R program. To run the program, the console will execute every single line of code in the document.
+
+-   Console (interpreter): Instead of giving a entire program in a text file, you could interact with the R Console line by line. You give it one line of instruction, and the console executes that single line. It is what R looks like without RStudio.
+
+-   Environment: Often, code will store information *in memory*, and it is shown in the environment. More on this later.
+
+## Using Quarto for your work
+
+Why should we use Quarto for data science work?
+
+-   Encourages reproducible workflows
+
+-   Code, output from code, and prose combined together
+
+-   Extendability to Python, Julia, and more.
+
+More options and guides can be found in [Introduction to Quarto](https://quarto.org/docs/get-started/hello/rstudio.html) .
+
+## Grammar Structure 1: Evaluation of Expressions
+
+-   **Expressions** are be built out of **operations** or **functions**.
+
+-   Operations and functions combine **data types** to return another data type.
+
+-   We can combine multiple expressions together to form more complex expressions: an expression can have other expressions nested inside it.
+
+For instance, consider the following expressions entered to the R Console:
+
+
+```r
+18 + 21
+```
+
+```
+## [1] 39
+```
+
+```r
+max(18, 21)
+```
+
+```
+## [1] 21
+```
+
+```r
+max(18 + 21, 65)
+```
+
+```
+## [1] 65
+```
+
+```r
+18 + (21 + 65)
+```
+
+```
+## [1] 104
+```
+
+```r
+length("ATCG")
+```
+
+```
+## [1] 1
+```
+
+Here, our input **data types** to the operation are **numeric** in lines 1-4 and our input data type to the function is **character** in line 5.
+
+Operations are just functions in hiding. We could have written:
+
+
+```r
+sum(18, 21)
+```
+
+```
+## [1] 39
+```
+
+```r
+sum(18, sum(21, 65))
+```
+
+```
+## [1] 104
+```
+
+Remember the function machine from algebra class? We will use this schema to think about expressions.
+
+![Function machine from algebra class.](https://cs.wellesley.edu/~cs110/lectures/L16/images/function.png)
+
+If an expression is made out of multiple, nested operations, what is the proper way of the R Console interpreting it? Being able to read nested operations and nested functions as a programmer is very important.
+
+
+```r
+3 * 4 + 2
+```
+
+```
+## [1] 14
+```
+
+```r
+3 * (4 + 2)
+```
+
+```
+## [1] 18
+```
+
+Lastly, a note on the use of functions: a programmer should not need to know how the function is implemented in order to use it - this emphasizes [abstraction and modular thinking](#a-programming-language-has-following-elements), a foundation in any programming language.
+
+## Grammar Structure 2: Storing data types in the global environment
+
+To build up a computer program, we need to store our returned data type from our expression somewhere for downstream use. We can assign a variable to it as follows:
+
+
+```r
+x = 18 + 21
+```
+
+If you enter this in the Console, you will see that in the Environment, the variable `x` has a value of `39`.
+
+### Execution rule for variable assignment
+
+> Evaluate the expression to the right of `=`.
+>
+> Bind variable to the left of `=` to the resulting value.
+>
+> The variable is stored in the environment.
+>
+> `<-` is okay too!
+
+The environment is where all the variables are stored, and can be used for an expression anytime once it is defined. Only one unique variable name can be defined.
+
+The variable is stored in the working memory of your computer, Random Access Memory (RAM). This is temporary memory storage on the computer that can be accessed quickly. Typically a personal computer has 8, 16, 32 Gigabytes of RAM. When we work with large datasets, if you assign a variable to a data type larger than the available RAM, it will not work. More on this later.
+
+Look, now `x` can be reused downstream:
+
+
+```r
+x - 2
+```
+
+```
+## [1] 37
+```
+
+```r
+y = x * 2
+```
+
+## Grammar Structure 3: Evaluation of Functions
+
+A function has a **function name**, **arguments**, and **returns** a data type.
+
+### Execution rule for functions:
+
+> Evaluate the function by its arguments, and if the arguments are functions or contains operations, evaluate those functions or operations first.
+>
+> The output of functions is called the **returned value**.
+
+
+```r
+sqrt(nchar("hello"))
+```
+
+```
+## [1] 2.236068
+```
+
+```r
+(nchar("hello") + 4) * 2
+```
+
+```
+## [1] 18
+```
+
+## Functions to read in data
+
+We are going to read in a Comma Separated Value (CSV) spreadsheet, that contains information about cancer cell lines.
+
+The first line calls the function `read.csv()` with a string argument representing the file path to the CSV file (we are using an URL online, but this is typically done locally), and the returned data type is stored in `metadata` variable. The resulting `metadata` variable is a new data type you have never seen before. It is a **data structure** called a **data frame** that we will be exploring next week. It holds a table of several data types that we can explore.
+
+We run a few functions on `metadata`.
+
+
+```r
+metadata = read.csv("https://github.com/caalo/Intro_to_R/raw/main/classroom_data/CCLE_metadata.csv")
+head(metadata)
+```
+
+```
+##      ModelID PatientID CellLineName StrippedCellLineName Age SourceType
+## 1 ACH-000001 PT-gj46wT  NIH:OVCAR-3            NIHOVCAR3  60 Commercial
+## 2 ACH-000002 PT-5qa3uk        HL-60                 HL60  36 Commercial
+## 3 ACH-000003 PT-puKIyc        CACO2                CACO2  72 Commercial
+## 4 ACH-000004 PT-q4K2cp          HEL                  HEL  30 Commercial
+## 5 ACH-000005 PT-q4K2cp   HEL 92.1.7              HEL9217  30 Commercial
+## 6 ACH-000006 PT-ej13Dz   MONO-MAC-6             MONOMAC6  64 Commercial
+##   SangerModelID      RRID DepmapModelType AgeCategory GrowthPattern
+## 1     SIDM00105 CVCL_0465           HGSOC       Adult      Adherent
+## 2     SIDM00829 CVCL_0002             AML       Adult    Suspension
+## 3     SIDM00891 CVCL_0025            COAD       Adult      Adherent
+## 4     SIDM00594 CVCL_0001             AML       Adult    Suspension
+## 5     SIDM00593 CVCL_2481             AML       Adult         Mixed
+## 6     SIDM01023 CVCL_1426            AMOL       Adult    Suspension
+##   LegacyMolecularSubtype PrimaryOrMetastasis               SampleCollectionSite
+## 1                                 Metastatic                            ascites
+## 2                                    Primary haematopoietic_and_lymphoid_tissue
+## 3                                    Primary                              Colon
+## 4                                    Primary haematopoietic_and_lymphoid_tissue
+## 5                                                                   bone_marrow
+## 6                                    Primary haematopoietic_and_lymphoid_tissue
+##      Sex SourceDetail  LegacySubSubtype CatalogNumber
+## 1 Female         ATCC high_grade_serous        HTB-71
+## 2 Female         ATCC                M3       CCL-240
+## 3   Male         ATCC                          HTB-37
+## 4   Male         DSMZ                M6        ACC 11
+## 5   Male         ATCC                M6       HEL9217
+## 6   Male         DSMZ                M5       ACC 124
+##                                      CCLEName COSMICID PublicComments
+## 1                             NIHOVCAR3_OVARY   905933               
+## 2     HL60_HAEMATOPOIETIC_AND_LYMPHOID_TISSUE   905938               
+## 3                       CACO2_LARGE_INTESTINE       NA               
+## 4      HEL_HAEMATOPOIETIC_AND_LYMPHOID_TISSUE   907053               
+## 5  HEL9217_HAEMATOPOIETIC_AND_LYMPHOID_TISSUE       NA               
+## 6 MONOMAC6_HAEMATOPOIETIC_AND_LYMPHOID_TISSUE   908148               
+##   WTSIMasterCellID EngineeredModel TreatmentStatus OnboardedMedia PlateCoating
+## 1             2201                                     MF-001-041         None
+## 2               55                                     MF-005-001         None
+## 3               NA                         Unknown     MF-015-009         None
+## 4              783                  Post-treatment     MF-001-001         None
+## 5               NA                                     MF-001-001         None
+## 6             2167                                     MF-001-001         None
+##   OncotreeCode                      OncotreeSubtype    OncotreePrimaryDisease
+## 1        HGSOC     High-Grade Serous Ovarian Cancer  Ovarian Epithelial Tumor
+## 2          AML               Acute Myeloid Leukemia    Acute Myeloid Leukemia
+## 3         COAD                 Colon Adenocarcinoma Colorectal Adenocarcinoma
+## 4          AML               Acute Myeloid Leukemia    Acute Myeloid Leukemia
+## 5          AML               Acute Myeloid Leukemia    Acute Myeloid Leukemia
+## 6         AMOL Acute Monoblastic/Monocytic Leukemia    Acute Myeloid Leukemia
+##        OncotreeLineage
+## 1 Ovary/Fallopian Tube
+## 2              Myeloid
+## 3                Bowel
+## 4              Myeloid
+## 5              Myeloid
+## 6              Myeloid
+```
+
+```r
+nrow(metadata)
+```
+
+```
+## [1] 1864
+```
+
+```r
+ncol(metadata)
+```
+
+```
+## [1] 30
+```
+
+If you don't know what a function does, ask for help:
+
+
+```r
+?nrow
+```
+
+## Tips on Exercises / Debugging
+
+Common errors:
+
+-   Syntax error.
+
+-   Changing a variable without realizing you did so.
+
+-   The function or operation does not accept the input data type.
+
+-   It did something else than I expected!
+
+Solutions:
+
+-   Where is the problem?
+
+-   What kind of problem is it?
+
+-   Explain your problem to someone!