Rigor & Reproducibility Training

The School of Graduate Studies offers courses that fulfill training for Rigor and Reproducibility that are required by NIH.

For a boilerplate document that can be used to describe the NIH compliant Rigor and Reproducibility training for grad students and postdocs for fellowship applications (F30,31,32) and training grants (T32), please click here.


Available Courses

The Biomedical Sciences graduate programs in New Brunswick/Piscataway are now requiring all incoming PhD students (starting Fall 2017) to take one of 3 biostatistics courses to ensure Rigor and Reproducibility training for all biomedical PhD students.

  • The requirement includes the following graduate program: Biochemistry, Cell, and Developmental Biology, Biomedical Engineering, Pharmacology, Exposure Science, Microbiology and Molecular Genetics, Neuroscience, Physiology, Toxicology
  • It is up to the student to decide which class s/he would like to take to fulfill this requirement and the options are listed below. 
    • The Fall course is entitled "Statistics in Biomedical Science" CTSC 5103S.  SGS Course number 16:115:557 (index#: 22748) Thursdays 5-8 PM by Zoom. For a course syllabus, click here
    • One Spring course is entitled "Interdisciplinary Biostatistics"  16:125:578 on Wednesdays from 5 - 8 pm via Zoom. For a course syllabus, click here
    • Another Spring course, offered every other year, is entitled “Deeper Data Analysis for Neuroscience and Psychology 16:830:533:01 on Thursdays from 10:00 AM- 12:30 PM. For a course syllabus from 2020, click here
  • These will be 3 credit courses and cover the following topics:         

    Determining Power, Defining Endpoints, Randomization, Blinding, Assay Expertise Level, Data Management / Analysis, Data Inclusion / Exclusion, Bias, Reproducibility, Statistical Theory, and Statistical Methodology


To address the new NIH requirements concerning scientific rigor and reproducibility (NOT-OD-16-011), Rutgers piloted a series of webinars that is funded by an NIH R25 grant (PI: DiCicco-Bloom) and developed in collaboration with the Society for Neuroscience (Promoting Awareness and Knowledge to Enhance Scientific Rigor in Neuroscience).  Rutgers biomedical science programs required all 1st year PhD students as well as and 5th year PhD students and postdoctoral fellows who were registered for Responsible Conduct of Research training to watch the webinars in 2016 which covered the following topics:   

  • Planning experiments and preparing for data collection | January 20, 2016 watch now
  • Minimizing bias in experimental design and execution | February 23, 2016 watch now
  • Post-experimental data analysis | May 19, 2016 watch now
  • Data management and reporting | July 18, 2016 watch now

Rutgers University Biostatistics & Epidemiology Services Center (RUBIES)

(RUBIES) has been created to provide statistics, programming, and data analysis to investigators on a mostly fee-for-services basis.

RUBIES will deliver a wide range of services including data cleaning, statistical programming, study design, data analysis and interpretation, and technical report preparation, as well as the production of statistical summaries, tables, and graphs.  The first hour of consultation is free, after which additional work completed based on an agreed-upon written estimate of cost (non-faculty investigators should be accompanied by their faculty mentor for the initial meeting).  RUBIES staff will ensure completion of more complex requests by working with faculty or by referring those requests to faculty with relevant expertise in Epidemiology, Statistics, or Biostatistics.   For more information about RUBIES or to request a consultation, please visit rubies.rutgers.edu. Human Cell Authentication Technology Available at Rutgers.


RUCDR Infinite Biologics™

How do you ensure the identity of the cell lines with which you do research? NIH and AHRQ now require cell line authentication for new and competing research grant applications, and it is now a requirement for publication in many leading journals.

RUCDR Infinite Biologics™, part of the Rutgers Human Genetics Institute of New Jersey, has developed the industry-leading human cell authentication technology, known as SNPtrace™, marketed worldwide by Fluidigm™. This technology is available at low cost to the Rutgers community. This method interrogates a 96-SNP panel of ethnicity, gender, and other markers—providing a unique identifier for each individual or cell line. Initially, RUCDR requires a reference sample for comparison. Once the SNP profile of the reference is established, future samples can be compared to the stored data. The cost is $40 per cell pellet or $25 per submitted DNA. For inquiries concerning this service, contact Vrunda Bhatt at Bhatt@dls.rutgers.edu or 848 445-8141.


Molecular Resource Facility (MRF) at Rutgers NJMS

The MRF is pleased to announce the availability of Short Tandem Repeat (STR) DNA profiling for the authentication of human cell lines!! STR profiling aids in the detection of misidentified, cross-contaminated, or genetically drifted cells, which invalidate research results. STR profiling is a rapid, reproducible, and standardized PCR-based method for the authentication of human cell lines.

On October 9, 2015, the NIH published new guidelines to implement rigor and transparency in NIH & AHRQ Research Grant applications.  In addition, many journals now require proof of cell line authentication prior to publication including Nature publishing group, American Association for Cancer Research (AACR) publications, BioMed Central journals, PLOS ONE, Society for Endocrinology publications, etc. For rapid and reproducible results the MRF will use Promega’sPowerPlex® 18D System which allows the amplification of 18 STR loci simultaneously in a single tube!! For more information don’t hesitate to contact mrfadm@njms.rutgers.edu or call 973-972-2625.


Useful materials for complying with new NIH requirements

These NIH updates focus on four areas deemed important for enhancing rigor and transparency:

1) the scientific premise forming the basis of the proposed research,

2) rigorous experimental design for robust and unbiased results,

3) consideration of relevant biological variables, and

4) authentication of key biological and/or chemical resources.