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First, we will want to fix the three immediate problems discussed above. Once those have been fixed, we are going to create a bar plot, using ggplot2 to plot the total gene counts per sample. Read More...
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Use pivot_longer to reshape countB. Your reshaped data should look the same as the data below. {{Sdet}} Solution } library ( tidyverse ) countB % rownames_to_column ( "Feature" ) countB_l ## 1 Tspan6 1 703 71 ## 2 Tspan6 2 567 970 ## 3 Tspan6 3 867 242 ## 4 TNMD 1 490 342 ## 5 TNMD 2 482 935 ## 6 Read More...
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Using the boxplot you created above, reorder the x-axis so that color is organized from worst (J) to best (D). There are multiple possible solutions. Hint: Check out functions in the forcats package (a tidyverse Read More...
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Let's use some other geoms. Plot the number of passengers (a simple count) that survived by ticket class and facet by sex. {{Sdet}} Possible Solution{{Esum}} ggplot(titanic) + geom_bar(aes(x=Pclass, fill= Read More...
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Add a variable to the data frame called age_cat (child = % mutate(age_cat= case_when(Age = 12 & Age = 18 ~ "adult" )) %>% ggplot() + geom_bar(aes(x=age_cat, fill=factor(Sex)), position=position_ Read More...
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Q5 Use pivot_longer to reshape countB. You will need to import countB (file_path = "./data/countB.csv"). Your reshaped data should look the same as the data below. # A tibble: 27 × 4 Feature Replicate Read More...
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Q4. Load in a tab delimited file (file_path= "./data/WebexSession_report.txt") using read_delim(). You will need to troubleshoot the error message and modify the function arguments as needed. Q4: Solution Read More...
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Load in a tab delimited file (file_path= "./data/WebexSession_report.txt") using read_delim() . You will need to troubleshoot the error message and modify the function arguments as needed. {{Sdet}} Solution } library ( Read More...
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Bioinformatics
Data associated with the lesson 8 data wrangling challenge can be found here .
Frederick, MD
Collaborative
The Biopharmaceutical Development Program (BDP) provides resources for the development of investigational biological agents. The BDP supports feasibility through development and Phase I/II cGMP manufacturing plus regulatory documentation.The BDP was established in 1993. We Read More...
Bethesda, MD
Core Facility
Trans NIH Facility
The PET Department, CC, functions as a core facility that supports basic, translational, and clinical research using PET. It is a vertically integrated facility, with resources to produce positron-emitting radionuclides, manufacture PET radiopharmaceuticals in a Read More...
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06/13/2025 - Dr. Fuhai Li,&nb p;A ociate Profe or at the chool of Medicine and Computer cience & Engineering, Wa hington Univer ity, will pre ent novel approache that combine large language Read More...
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Bioinformatics
04/14/2025 - Gene set analysis (GSA) is essential in genomic research, yet traditional methods often lack transparency and produce contextually irrelevant results, making interpretation challenging. While large language models (LLMs) offer a promising solution for result Read More...
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Bioinformatics
07/10/2025 - Diagno tic error remain a leading cau e of preventable harm in healthcare, particularly in high- take , time-pre ured environment like the emergency department. Large Language Model (LLM ) offer promi ing new capabilitie for Read More...
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Bioinformatics
02/27/2025 - NGS produces millions of sequences per sample and the challenge is to identify where in the genome each sequence came from. Fortunately, there are aligners that help scientists with this task. After this class, Read More...
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Bioinformatics
05/10/2024 - Please join us for the May Data Sharing and Reuse Seminar featuring Dr. Ali Loveys and Fiona Meng from FI Consulting. They will be sharing their presentation on Laying the Foundation for AI-Ready Data. Read More...
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Get the data Lesson 1 No data available. Lesson 2 No data available. Lesson 3 Lesson 3 covered data import and reshaping. Data unavailable through base R or other R packages, can be downloaded here . The survey / species data Read More...
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Bioinformatics
10/13/2023 - Zhiyong Lu, Ph.D. will present AI in Medicine: Improving Access to Literature Data for Knowledge Discovery at the monthly Data Sharing and Reuse Seminar. The explosion of biomedical big data and Read More...
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Bioinformatics
02/16/2023 - February 13-17 is International Love Data Week 2023 , a week-long celebration highlighting the importance of research data management, sharing, preservation, and reuse. The NIH Library loves data and is celebrating all February (and March, too!) Read More...
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Bioinformatics
02/14/2023 - February 13-17 is International Love Data Week 2023 , a week-long celebration highlighting the importance of research data management, sharing, preservation, and reuse. The NIH Library loves data and is celebrating all February (and March, too!) Read More...
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Bioinformatics
05/02/2022 - Federated Learning (FL) has emerged as a potential solution due to its capability in training models without sharing data. To enable effective FL in real applications, a robust communication framework is crucial. Join Drs. Read More...
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Bioinformatics
10/20/2021 - Presenter: Trevor Bedford, Ph.D. Associate Professor Vaccine and Infectious Disease Division Human Biology Division Herbold Computational Biology Program Fred Hutchinson Cancer Research Center Genomic epidemiology has enabled critical insights during the COVID-19 pandemic. Read More...
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05/10/2021 - Abstract: Deep learning is revolutionizing the prediction of protein tertiary structure and is close to solve this grand challenge hanging over the scientific world for many years. In this talk, I will describe how Read More...
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Protein Expression Laboratory The Protein Expression Laboratory develops, improves, and delivers protein-centric services. Our goal is to help client investigators achieve their research goals with the lowest possible cost in the shortest time. All PEL Read More...
Frederick, MD
Collaborative
The Antibody Characterization Laboratory (ACL) is the laboratory responsible for the development of well-characterized monoclonal antibody reagents. The NCI’s Office of Cancer Clinical Proteomics Research funds ACL as a resource to the entire cancer Read More...
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CREx News & Updates July 2021 Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More NIH Collaborative Research Exchange (CREx) News Site Spotlight FACILITY HIGHLIGHTS Learn more about services from the NHLBI Read More...
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09/29/2025 - Plea e u e thi link to acce overview, regi tration, and other information: http ://event .cancer.gov/nci/od -data-jamboree Childhood cancer i a rare di ea e with ~15,000 ca e diagno ed Read More...
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07/23/2025 - This presentation will explore the next emerging stage where biobanking is characterised by being part of system - Biobanking 4.0. Biobanking has always been about data generation with tissue specimens providing the biological and genomic Read More...
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Bioinformatics
05/19/2025 - Immunotherapy has the potential to revolutionize the way we treat cancer, but a key challenge has been finding ways to tailor that therapy to the right patient at the right time. Attend this webinar, Read More...
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Bioinformatics
The filtlowabund_scaledcounts_airways.txt includes normalized and non-normalized transcript count data from an RNAseq experiment. You can read more about the experiment here . You can obtain the data outside of class here . The diffexp_ Read More...
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Bioinformatics
Lesson 2 Exercise Questions: Part 2 (Tidyverse) The filtlowabund_scaledcounts_airways.txt includes normalized and non-normalized transcript count data from an RNAseq experiment. You can read more about the experiment here . You can obtain the data outside Read More...
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Bioinformatics
The filtlowabund_scaledcounts_airways.txt includes normalized and non-normalized transcript count data from an RNAseq experiment. You can read more about the experiment here . You can obtain the data outside of class here . The diffexp_ Read More...
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Bioinformatics
Lesson 4 Exercise Questions: Tidyverse The filtlowabund_scaledcounts_airways.txt includes normalized and non-normalized transcript count data from an RNAseq experiment. You can read more about the experiment here . You can obtain the data outside of Read More...
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Bioinformatics
The filtlowabund_scaledcounts_airways.txt includes normalized and non-normalized transcript count data from an RNAseq experiment. You can read more about the experiment here . You can obtain the data outside of class here . The diffexp_ Read More...
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Bioinformatics
Lesson 4 Exercise Questions: Tidyverse The filtlowabund_scaledcounts_airways.txt includes normalized and non-normalized transcript count data from an RNAseq experiment. You can read more about the experiment here . You can obtain the data outside of Read More...
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Bioinformatics
Help Session Lesson 3 Loading data Import data from the sheet "iris_data_long" from the excel workbook (file_path = "./data/iris_data.xlsx"). Make sure the column names are unique and Read More...
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Bioinformatics
11/30/2023 - Greetings, NCI intramural researchers, Earlier this year we reached out to gather your input on the formation of a bioinformatics community within the NCI Intramural Research Program. Why create such Read More...
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Bioinformatics
05/23/2023 - NIH Text Mining and Natural Language Processing SIG is pleased to welcome you to a special event dedicated to Large Language Models. Abstract : The release of ChatGPT and the subsequent launch of GPT-4 by Read More...
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Bioinformatics
05/19/2023 - Patient-derived cancer models (PDCM) have become an essential tool in both cancer research and preclinical studies. Each model type offers unique advantages and is better suited for specific research areas: cell lines are low Read More...
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Bioinformatics
Load the data For these exercises, you will explore the titanic data from kaggle.com , which was downloaded from here . You will need to download the data and load into R. As this is a Read More...
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Bioinformatics
The filtlowabund_scaledcounts_airways.txt includes normalized and non-normalized transcript count data from an RNAseq experiment. You can read more about the experiment here . You can obtain the data outside of class here . The diffexp_ Read More...
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Bioinformatics
Lesson 2 Exercise Questions: Part 2 (Tidyverse) The filtlowabund_scaledcounts_airways.txt includes normalized and non-normalized transcript count data from an RNAseq experiment. You can read more about the experiment here . You can obtain the data outside Read More...
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Bioinformatics
The filtlowabund_scaledcounts_airways.txt includes normalized and non-normalized transcript count data from an RNAseq experiment. You can read more about the experiment here . You can obtain the data outside of class here . The diffexp_ Read More...
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Bioinformatics
Lesson 4 Exercise Questions: Tidyverse The filtlowabund_scaledcounts_airways.txt includes normalized and non-normalized transcript count data from an RNAseq experiment. You can read more about the experiment here . You can obtain the data outside of Read More...
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Bioinformatics
10/19/2022 - Our bodies host millions of microorganisms, and our relationship with these tiny living companions is complex. While microbial communities support normal processes and defend against harmful pathogens, infections with some viruses and bacteria can Read More...
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Bioinformatics
10/14/2022 - The call for better data and evidence for decision-making has become very real as evidenced by the Federal Data Strategy, as well as the passage of both the Foundations of Evidence-based Policymaking Act (Evidence Read More...
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Bioinformatics
10/05/2022 - For our next CDSL webinar we will have presentations by two CDSL fellows: Ekaterina Kazantseva and Sanna Madan. Ekaterina is a master’s student in Dr. Mikhail Kolmogorov's group and the title of Read More...
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Bioinformatics
09/29/2022 - The size and complexity of data necessary to derive meaningful scientific and clinical insights are advancing at an unprecedented rate. At the core of this complexity is an ever-expanding array of technologies, instrumentation, and Read More...
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Bioinformatics
03/30/2022 - Predicting how changes in the genome manifest as phenotypic differences is an extremely challenging problem that requires a deep understanding of multiscale biological mechanisms. And while we know a great deal about how information Read More...
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Bioinformatics
05/13/2021 - Meeting Link The slides and recording of the webinar will be available within a day of the event. Heterogeneity poses a major challenge in translational research. For example, inter-tumor heterogeneity limits the biomarker discovery Read More...
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Bioinformatics
04/05/2021 - Dear colleagues, We'll be hosting a special guest lecture by Prof. John Moult from UMD. Abstract: Computing the three-dimensional structure of a protein molecule from its amino acid sequence is a long-standing grand Read More...
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Bioinformatics
03/24/2021 - WebEx: Register Accurate detection of somatic mutations is challenging but critical to understanding how cancer forms and progresses. Such detection is also critical for targeting more effective treatments. In this seminar, Dr. Mohammad Sahraeian, Read More...
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Bioinformatics
11/30/2020 - Register Meeting ID: 918 4307 1125 One tap mobile +13017158592,,91843071125# US (Washington D.C) +19294362866,,91843071125# US (New York) Dial by your location +1 301 715 8592 US (Washington D.C) +1 929 436 2866 US (New York) +1 312 626 6799 US (Chicago) +1 346 248 7799 US (Houston) +1 669 900 6833 US (San Jose) +1 253 215 8782 US (Tacoma) Meeting Read More...
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Bioinformatics
08/21/2020 - Abstract: Machine learning (ML) has emerged as an essential tool for building models which can be used to predict clinical outcomes for age-related diseases. A significant challenge of ML is knowing which algorithms and Read More...
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Bioinformatics
07/09/2020 - The recent breakthroughs in high-throughput technologies have resulted in a vast amount of big-data resources. However, it remains a significant challenge to transfer the knowledge from the public data to a new research project Read More...
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Bioinformatics
06/24/2020 - Join us for a webinar: How to Analyze Single Cell RNA-Seq Data: Point, Click, Done Register: https://www.partek.com/webinar/how-to-analyze-single-cell-rna-seq-data-point-click-done/ Single cell mRNA sequencing allows for the identification of different cell subtypes Read More...
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Bioinformatics
11/19/2019 - Methods for Characterizing the Activity of Mutational Processes in Cancer The cancer sequencing efforts of the past decade have revealed signatures of the mutational processes shaping cancer genomes. These mutational signatures provide a window Read More...
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Bioinformatics
11/05/2018 - RNA-seq, expression microarrays, and other omics profiling platforms are powerful tools for discovery, and analytical pipelines often return large numbers of significant genes or other markers. This presents a challenge when trying to understand Read More...
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Bioinformatics
Let's grab some data. library ( tidyverse ) acount_smeta % dplyr :: rename ( "Feature" = "...1" ) acount #differential expression results dexp % filter ( ! Feature %in% dexp $ feature ) ## # A tibble: 48,176 × 9 ## Feature SRR1039508 SRR1039509 SRR1039512 SRR1039513 SRR1039516 SRR1039517 ## ## 1 Read More...
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Bioinformatics
Help Session Lesson 6 Let's grab some data. library ( tidyverse ) acount_smeta % dplyr :: rename ( "Feature" = "...1" ) acount #differential expression results dexp % filter ( ! Feature %in% dexp $ feature ) ## # A tibble: 48,176 × 9 ## Feature SRR1039508 SRR1039509 SRR1039512 Read More...
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All solutions should use the pipe. Import the file "./data/filtlowabund_scaledcounts_airways.txt" and save to an object named sc . Create a subset data frame from sc that only includes the columns Read More...
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Bioinformatics
Help Session Lesson 5 All solutions should use the pipe. Import the file "./data/filtlowabund_scaledcounts_airways.txt" and save to an object named sc . Create a subset data frame from sc that only Read More...
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Bioinformatics
Help Session Lesson 4 Plotting with ggplot2 For the following plots, let's use the diamonds data ( ?diamonds ). The diamonds dataset comes in ggplot2 and contains information about ~54,000 diamonds, including the price, carat, color, clarity, and Read More...
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Bioinformatics
Objectives Review important data wrangling functions Put our wrangling skills to use on a realistic RNA-Seq data set Data Wrangling Review Important functions by topic Importing / Exporting Data Importing and exporting data into the R Read More...
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Bioinformatics
02/21/2017 - This BTEP Workshop will cover the fundamentals and best practices of Exome-Seq analysis, including downstream interpretation of variants using a variety of in-house and NCI-licensed software solutions. There will be hands-on training on CCBR Read More...
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Bioinformatics
03/08/2016 - BTEP Workshop on Exome-Seq Data Analysis and Variant Annotation (2-day) This workshop will cover the basics and best practices of exome-seq analysis including downstream interpretation of variants using a variety of in-house, open-source and Read More...
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Bioinformatics
03/18/2015 - This workshop will cover basics of exome-seq analysis including downstream interpretation of variants using a variety of open-source and commercial webtools (Golden Helix, IGV, Ingenuity Variant Analysis, GeneGrid (Genomatix), MuPit/Cravat). Day 1 - AM (9:30 Read More...
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Bioinformatics
All solutions use the pipe. Solutions have multiple possibilities. Q1. Import the file "./data/filtlowabund_scaledcounts_airways.txt" and save to an object named sc. Create a data frame from sc that only Read More...