ReviewHuman genomics2005
A comprehensive literature review of haplotyping software and methods for use with unrelated individuals.
Review in Human genomics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed.
- Review
- Interrogating the Human Diplome: Computational Methods, Emerging Applications, and Challenges.Methods in molecular biology (Clifton, N.J.) · 2023Article
- An Evolutionary Insight Into the Heterogeneous Severity Pattern of the SARS-CoV-2 Infection.Frontiers in genetics · 2022Article
- Easy-HLA: a validated web application suite to reveal the full details of HLA typing.Bioinformatics (Oxford, England) · 2020Article
- Transformation-associated recombination (TAR) cloning for genomics studies and synthetic biology.Chromosoma · 2016Review
- A simple method for gene phasing using mate pair sequencing.BMC medical genetics · 2014Article
- 16(th) IHIW: global analysis of registry HLA haplotypes from 20 million individuals: report from the IHIW Registry Diversity Group.International journal of immunogenetics · 2013Article
- Haplotype and minimum-chimerism consensus determination using short sequence data.BMC genomics · 2012Article
- Next-generation phylogeography: a targeted approach for multilocus sequencing of non-model organisms.PloS one · 2012Article
- The importance of phase information for human genomics.Nature reviews. Genetics · 2011Review
- Haplotyping methods for pedigrees.Human heredity · 2009Review
- High-throughput haplotype determination over long distances by haplotype fusion PCR and ligation haplotyping.Nature protocols · 2009Article
- Haplotype inference from unphased SNP data in heterozygous polyploids based on SAT.BMC genomics · 2008Article
- Accommodating linkage disequilibrium in genetic-association analyses via ridge regression.American journal of human genetics · 2008Article
- Cubic exact solutions for the estimation of pairwise haplotype frequencies: implications for linkage disequilibrium analyses and a web tool 'CubeX'.BMC bioinformatics · 2007Article
- Understanding the accuracy of statistical haplotype inference with sequence data of known phase.Genetic epidemiology · 2007Article
- Constrained hidden Markov models for population-based haplotyping.BMC bioinformatics · 2007Article
- Statistical genetics concepts and approaches in schizophrenia and related neuropsychiatric research.Schizophrenia bulletin · 2007Review
- A novel strategy for defining haplotypes by selective depletion using restriction enzymes.Immunogenetics · 2007Article
- HaploRec: efficient and accurate large-scale reconstruction of haplotypes.BMC bioinformatics · 2006Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Interest in the assignment and frequency analysis of haplotypes in samples of unrelated individuals has increased immeasurably as a result of the emphasis placed on haplotype analyses by, for example, the International HapMap Project and related initiatives. Although there are many available computer programs for haplotype analysis applicable to samples of unrelated individuals, many of these programs have limitations and/or very specific uses. In this paper, the key features of available haplotype analysis software for use with unrelated individuals, as well as pooled DNA samples from unrelated individuals, are summarised. Programs for haplotype analysis were identified through keyword searches on PUBMED and various internet search engines, a review of citations from retrieved papers and personal communications, up to June 2004. Priority was given to functioning computer programs, rather than theoretical models and methods. The available software was considered in light of a number of factors: the algorithm(s) used, algorithm accuracy, assumptions, the accommodation of genotyping error, implementation of hypothesis testing, handling of missing data, software characteristics and web-based implementations. Review papers comparing specific methods and programs are also summarised. Forty-six haplotyping programs were identified and reviewed. The programs were divided into two groups: those designed for individual genotype data (a total of 43 programs) and those designed for use with pooled DNA samples (a total of three programs). The accuracy of programs using various criteria are assessed and the programs are categorised and discussed in light of: algorithm and method, accuracy, assumptions, genotyping error, hypothesis testing, missing data, software characteristics and web implementation. Many available programs have limitations (eg some cannot accommodate missing data) and/or are designed with specific tasks in mind (eg estimating haplotype frequencies rather than assigning most likely haplotypes to individuals). It is concluded that the selection of an appropriate haplotyping program for analysis purposes should be guided by what is known about the accuracy of estimation, as well as by the limitations and assumptions built into a program.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.