Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Multiple Comparison Tests01:13

Multiple Comparison Tests

4.6K
Multiple comparison test, abbreviated as MCT, is a post hoc analysis generally performed after comparing multiple samples with one or more tests. An MCT will help identify a significantly different sample among multiple samples or a factor among multiple factors.
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
4.6K
Kendall's Tau Test01:16

Kendall's Tau Test

1.3K
Kendall's tau test, also known as the Kendall rank coefficient test, is a nonparametric method for assessing association between two variables. This test is particularly useful for identifying significant correlations when the distributions of the sample and population are unknown. Developed in 1938 by the British statistician Sir Maurice George Kendall, the tau coefficient (denoted as τ) serves as a rank correlation coefficient, with values ranging from -1 to +1.
A τ value of +1 indicates...
1.3K
Compacting Factor test01:22

Compacting Factor test

681
The compacting factor test is a method used to assess the workability of concrete. It is  especially suitable for concrete mixes containing aggregates up to one and a half inches in size. This test involves specialized equipment consisting of two truncated cone-shaped hoppers and a cylinder, all with polished interior surfaces to minimize friction.
The procedure begins by placing concrete into the upper hopper without any compaction. Once filled, the bottom door of this hopper is opened,...
681
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

1.4K
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
1.4K
Wilcoxon Signed-Ranks Test for Matched Pairs01:09

Wilcoxon Signed-Ranks Test for Matched Pairs

583
The Wilcoxon signed-rank test for matched pairs evaluates the null hypothesis by combining the ranks of differences with their signs. It essentially tests whether the median of the differences in a population of matched pairs is zero. Since the test incorporates more information than the sign test, it generally yields more trustable conclusions. This test also does not require the data to follow a normal distribution, but two conditions must be met for it to be applicable: (1) the data must...
583
Kendall's Coefficient of Concordance01:20

Kendall's Coefficient of Concordance

1.2K
Kendall's Coefficient of Concordance (W), also known as Kendall's W, is a non-parametric statistical measure used to assess the agreement or concordance between multiple raters or judges when they rank a set of items. It is often used when you have ordinal data (ranks) and you want to see if there is consistency or consensus among the raters. It is widely applied in research areas such as psychology, medicine, and social sciences, where multiple judges are asked to rank or rate subjects...
1.2K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Identifying Comorbid Fibromyalgia in Inflammatory Arthritis: The Role of Disease Activity in Fibromyalgia Survey Questionnaire Performance.

Journal of clinical rheumatology : practical reports on rheumatic & musculoskeletal diseases·2026
Same author

Sex and substance use in first episode psychosis: Impact on clinical symptoms, psychosocial functioning and cognitive performance.

Spanish journal of psychiatry and mental health·2026
Same author

Impact of preference signaling and geographic preferencing on research productivity and regional matching in orthopaedic surgery residency.

American journal of surgery·2026
Same author

[Crowned Dens Syndrome Mimicking Acute Meningitis in an Elderly Patient].

Revista medica de Chile·2025
Same author

[Disappearing bone disease of the shoulder (Gorham-Stout Syndrom)].

Revista medica de Chile·2024
Same author

[IGG4-related disease. Report of 52 patients].

Revista medica de Chile·2023

Related Experiment Video

Updated: Mar 24, 2026

Detection of Copy Number Alterations Using Single Cell Sequencing
09:45

Detection of Copy Number Alterations Using Single Cell Sequencing

Published on: February 17, 2017

12.2K

Computational Performance Assessment of k-mer Counting Algorithms.

Nelson Pérez1, Miguel Gutierrez1, Nelson Vera1

  • 1GICOGE, Universidad Distrital Francisco José de Caldas , Bogotá, Colombia .

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|March 17, 2016
PubMed
Summary

This study assesses k-mer counting tools for bioinformatics, evaluating computational needs and performance. Disk-partitioning techniques offer superior speed and parallelization with lower RAM usage for k-mer analysis.

Keywords:
computational performance assessmentdata structuresk-mer counters

More Related Videos

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

8.1K

Related Experiment Videos

Last Updated: Mar 24, 2026

Detection of Copy Number Alterations Using Single Cell Sequencing
09:45

Detection of Copy Number Alterations Using Single Cell Sequencing

Published on: February 17, 2017

12.2K
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

8.1K

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Accurate k-mer counting is crucial for genomic analysis.
  • Numerous k-mer counting tools exist, each with varying computational demands and performance characteristics.
  • A standardized framework for tool assessment is needed to guide researchers.

Purpose of the Study:

  • To evaluate and compare the performance of nine k-mer counting tools.
  • To establish a reference framework for assessing computational requirements, parallelization, and efficiency.
  • To identify advantages, disadvantages, and bottlenecks of different k-mer counting algorithms.

Main Methods:

  • Performance assessment of BFCounter, DSK, Jellyfish, KAnalyze, KHMer, KMC2, MSPKmerCounter, Tallymer, and Turtle.
  • Measured parameters included RAM usage, processing time, parallelization, and disk I/O.
  • Utilized a dataset of 36,504,800 reads from the human 14th chromosome.
  • Evaluated for k-mer lengths of 31 and 55.

Main Results:

  • Bloom filter-based and disk-partitioning tools exhibited lower RAM consumption.
  • Disk-partitioning techniques resulted in the shortest execution times.
  • Maximal parallelization was achieved with disk partitioning, lock-free hash tables, or multiple hash tables.

Conclusions:

  • Disk-partitioning techniques are highly efficient for k-mer counting in terms of speed and parallelization.
  • Tool selection should consider specific computational resources and analysis requirements.
  • The findings provide a valuable reference for optimizing k-mer counting in large-scale genomic studies.