Search Results for: Double Caged Q-Rhodamine 9EG7 conjugate

Step 1 : Login to DNAnexus Step 2 : Once you login, you should see the Projects page. If you have used DNAnexus previously, you may see more than one project listed. If this is your first time using Read More...

Step 1 : Login to DNAnexus Step 2 : Once you login, you should see the Projects page. If you have used DNAnexus previously, you may see more than one project listed. If this is your first time using Read More...

Given the following R code: numbers

Double-click IGV icon on desktop. Genomes -> Load Genome from Server (Human hg18) File -> Load from Server -> Available Datasets -> Body Map 2.0 (Illumina HiSeq) -> Merged 50 bp and 75 Read More...

Given the following R code: numbers

Another important data structure in R is the data matrix. Data frames and data matrices are similar in that both are tabular in nature and are defined by dimensions (i.e., rows (m) and columns ( Read More...

We can add information to our metadata by accessing and assigning to metadata columns or using ?AddMetaData() . Add condition to metadata (either wildtype of double knockout). adp$condition

Another important data structure in R is the data matrix. Data frames and data matrices are similar in that both are tabular in nature and are defined by dimensions (i.e., rows (m) and columns ( Read More...

R doesn't care about spaces in your code. However, it can vastly improve readability if you include them. For example, "thisissohardtoread" but "this is fine". You can use tab completion Read More...

For RNA sequencing studies, we need to use a splice aware aligner to account for reads that map across exons. Bowtie2 is a commonly used aligner for DNA sequencing and is not splice aware. Let' Read More...

R: Data types: integer, numeric, character, and logical Data structures: vectors, lists, data frames, matrices. x

R: Data types: integer, numeric, character, and logical Data structures: vectors, lists, data frames, matrices. ::: {.cell} x ::: :::

Another important data structure in R is the data matrix. Data frames and data matrices are similar in that both are tabular in nature and are defined by dimensions (ie. rows (m) and columns (n), Read More...

Installing RStudio Desktop on the Mac We recommend using RStudio Desktop, because it *provides a user-friendly environment with 4 pane views which makes it easier to use for examining data, writing scripts and running R analyses .* Read More...

If you already have RStudio Desktop , check that it is the latest version. On the Mac, launch RStudio Desktop from the Applications folder and Check for Updates under the Help menu. If you have the Read More...

If you already have R, check that it is the latest version. On the Mac, launch R from the Applications folder and Check For R Updates under the R menu. If you have the latest Read More...

Data types are familiar in many programming languages, but also in natural language where we refer to them as the parts of speech, e.g. nouns, verbs, adverbs, etc. Once you know if a word Read More...

As mentioned, an object's type/mode can be used to understand the methods that can be applied to it. Objects of mode numeric can be treated as such, meaning mathematical operators can be used Read More...

Given a list of numbers, it is difficult to perform mathematical operations. For instance list_of_numbers=[1,2,3,4,5] Multiplying list_of_numbers by 2 will duplicate this list. However, multiplying a list of numbers by two should Read More...

Given a list of numbers, it is difficult to perform mathematical operations. For instance list_of_numbers=[1,2,3,4,5] Multiplying list_of_numbers by 2 will duplicate this list. However, multiplying a list of numbers by two should Read More...

#misspelled object #mtcars mean(mcars$wt) Error in mean(mcars$wt): object 'mcars' not found object not found errors can be fixed by checking to make sure the object name was correctly typed and/or Read More...

#misspelled object #mtcars mean(mcars$wt) Error in mean(mcars$wt): object 'mcars' not found object not found errors can be fixed by checking to make sure the object name was correctly typed and/or Read More...

02/03/2026 - Note: It is recommended to take the Getting Started with AI Productivity Double Feature class prior to this. Unlock the power of your new personal assistant with our comprehensive overview class. Learn how to Read More...

The data type of an R object affects how that object can be used or will behave. Examples of base R data types include numeric, integer, complex, character, and logical. R objects can also have Read More...

The data type of an R object affects how that object can be used or will behave. Examples of base R data types include numeric, integer, complex, character, and logical. R objects can also have Read More...

Which of the following will throw an error and why? 4 _ chr :1:2: unexpected input ## 1: 4_ ## ^ . 4 chr :1:3: unexpected symbol ## 1: .4chr ## ^ {{Edet}} Create the following objects; give each object an appropriate name (your best guess at what name to Read More...

This is our first coding help session. We have designed some practice problems to get you acquainted with using R before beginning to wrangle in our next lesson. Practice problems Which of the following will Read More...

Because we are now creating different folders that stores results from various stages in our data analysis, we could set up some environmental variables for these so we can more easily reference these folders while Read More...

After the index file for the genome has been created, we will use a tool called bedGraphToBigWig to generate bigWig (bw) files from bedGraph (bg). Again, we use cat and parallel where cat reads/ids. Read More...

Lesson 1: Introduction to Unix and the Shell Lesson Objectives Course overview. Introduce Unix and describe how it differs from other operating systems. Introduce and get set up on DNAnexus and the GOLD system. Discuss ways Read More...

This page contains content taken directly from the Biostar Handbook by Istvan Albert. Activate the bioinformatics environment. conda activate bioinfo First let's make a place to store today's work. In your biostar_class Read More...

This page uses content directly from the Biostar Handbook by Istvan Albert. Remember to activate the bioinfo environment. conda activate bioinfo Then create a new directory for files we will be working with today in Read More...

Step 1 for generating bigWig files is to convert the BAM alignment results to a bedGraph file that contains coverage along genomic regions. Enchancing your vocabulary: BED file - this is also known as Browser Extensible Read More...

Change in the ~/biostar_class/hbr_uhr/hbr_uhr_hisat2 folder for this portion of the class. cd ~/biostar_class/hbr_uhr/hbr_uhr_hisat2 Now that we have our SAM files generated for the Read More...

R objects have certain attributes, and these attributes will be important for how they can interact with certain methods / functions. Understanding the mode (storage type) or the class of an object will be important for Read More...

Launch NoMachine . Located in the Applications folder. Read the Application window content and click the Continue button until you arrive at the window depicted below. Click the New button to create a new connection. Selecting Read More...

You have to VPN using Cisco AnyConnect Secure Mobility Client . Click Connect button and follow usual instructions. Following NoMachine Installation for Biowulf , double click the connection shortcut. You should see something like below. Fill in Read More...

NoMachine Installation for Biowulf To run programs with a graphical user interface (GUI) in a unix environment like Biowulf, you need to connect via a terminal emulator such as NoMachine. For example, if you want Read More...

Open Web Browser with link https://www.nomachine.com and Click Download now Mac OS X button. Navigate to Downloads folder on your Mac and double click the NoMachine DMG install file. In this example, Read More...

Running RStudio on Biowulf with NoMachine Using NoMachine to run Rstudio on Biowulf has the benefit of accessing data on the Biowulf/Helix drives. This comes at the cost of setup time and slower responsiveness. Read More...

There are rules regarding the naming of objects. Avoid spaces or special characters EXCEPT '_' and '.' No numbers or underscores at the beginning of an object name. For example: 1a<-"apples" # Read More...

Q1. What is the value of each object? Run the code and print the values. mass <- 47.5 # mass? age <- 122 # age? mass <- mass * 2.0 # mass? age <- Read More...

Q1. Let's use some functions. a. Use sum() to add the numbers from 1 to 10. Q1a: Solution sum(1:10) ## [1] 55 b. Compute the base 10 logarithm of the elements in the following vector and save to an Read More...

All of the objects we imported in the previous lesson, were data frames. In this lesson, we will learn how to view and find out more information regarding the data stored in a data frame. Read More...

Let's reshape the data. I will rely heavily on dplyr functions to perform these tasks. First, I want to isolate the alpha chain and beta chain data. #isolate alpha and beta dfTRA< Read More...

To run remove adapters for all FASTQ files in one go, the parallel command will be introduced. This command enables the analyst to run multiple tasks in parallel such as trimming of high throughput sequencing Read More...

The first step in analyzing RNA sequencing is to perform quality assessment of the FASTQ files. This step ensures that the quality of the data is good and there no issues with contaminations such as Read More...

This lesson provides an introduction to R in the context of single cell RNA-Seq analysis with Seurat. Learning Objectives Learn about options for analyzing your scRNA-Seq data. Learn about resources for learning R programming. Learn Read More...

Objectives To understand some of the most basic features of the R language including: Creating R objects and understanding object types Using mathematical operations Using comparison operators Creating, subsetting, and modifying vectors By the end Read More...

Learning Objectives Learn about data structures including factors, lists, data frames, and matrices. Load, explore, and access data in a tabular format (data frames) Learn to write out (export) data from the R environment Data Read More...

Lesson 2: Getting Started with QIIME2 Lesson Objectives Obtain sequence data and sample metadata Import data and metadata Discuss other useful QIIME2 features including view QIIME2, provenance tracking, and the QIIME2 forum. DNAnexus DNAnexus provides a Read More...

R Crash Course: A few things to know before diving into wrangling Learning the Basics Objectives 1. Learn about R objects 3. Learn how to recognize and use R functions 4. Learn about data types and accessors Console Read More...

Lesson 13: Aligning raw sequences to reference genome Before getting started, remember to be signed on to the DNAnexus GOLD environment. Lesson 11 Review In Lesson 11 we learned to aggregate multiple FASTQC reports into one using MultiQC, Read More...

Step 1 for generating bigWig files is to convert the BAM alignment results to a bedGraph (with extension bg) file that contains coverage along genomic regions. Enhancing your vocabulary: BED file - this is also known Read More...

Lesson 14: Visualizing alignment results Before getting started, remember to be signed on to the DNAnexus GOLD environment. Lesson 13 Review Previously, we used the application HISAT2 to align the raw sequencing data from the Human Brain Read More...

To align FASTQ files for one sample, we construct the HISAT2 command with the following options. The "-x" flag prompts us to enter the base name (ie. without extension) of genome index. The Read More...

“Gene set enrichment analysis” refers to the process of discovering the common characteristics potentially present in a list of genes. When these characteristics are GO terms, the process is called “functional enrichment.” Warning Overall GO Read More...

Lesson 14: Visualizing alignment results Before getting started, remember to be signed on to the DNAnexus GOLD environment. Lesson 13 Review Previously, we used the application HISAT2 to align the raw sequencing data from the Human Brain Read More...

Lesson 13: Aligning raw sequences to reference genome Before getting started, remember to be signed on to the DNAnexus GOLD environment. Lesson 11 Review In Lesson 11 we learned to aggregate multiple FASTQC reports into one using MultiQC, Read More...

This page uses content directly from the Biostar Handbook by Istvan Albert. Obtain RNA-seq test data. The test data consists of two commercially available RNA samples: Universal Human Reference (UHR) and Human Brain Reference (HBR) . Read More...

Learning Objectives Learn about popular programming languagues in bioinformatics Compare advantages and disadvantages of Python and R Discuss what you will need to learn to use these languages Discuss learning resources Choosing a programming language Read More...

Learning Objectives Learn about popular programming languagues in bioinformatics Compare advantages and disadvantages of Python and R Discuss what you will need to learn to use these languages Discuss learning resources Choosing a programming language Read More...

R basics Objectives : To understand some of the most basic features of the R language including: Creating R objects and understanding object types Using mathematical operations Using comparison operators Creating, subsetting, and modifying vectors By Read More...

Data frames Objectives To be able to load, explore, and access data in a tabular format. To this end, students should understand the following: 1. how to import and export data 2. how to create, summarize, and Read More...

The first step for generating bigWig files is to convert the BAM alignment results to bedGraph (with extension bg) files that contains sequencing depth along genomic regions (ie. how many sequences mapped to a genomic Read More...

Make a new folder hcc1395_hisat2 to store the HISAT2 alignment results. mkdir hcc1395_hisat2 Stay in /data/user/hcc1395_b4b for this exercise. To perform alignment for all samples at once, the parallel Read More...

The nors data frame is not sorted. The .sort_values() attribute can be used to do this. Inside .sort_value(), the option by will be used to sort the NORS data by the variable(s) Read More...