HANDS2: accurate assignment of homoeallelic base-identity in allopolyploids despite missing data
نویسندگان
چکیده
Characterization of homoeallelic base-identity in allopolyploids is difficult since homeologous subgenomes are closely related and becomes further challenging if diploid-progenitor data is missing. We present HANDS2, a next-generation sequencing-based tool that enables highly accurate (>90%) genome-wide discovery of homeolog-specific base-identity in allopolyploids even in the absence of a diploid-progenitor. We applied HANDS2 to the transcriptomes of various cruciferous plants belonging to genus Brassica. Our results suggest that the three C genomes in Brassica are more similar to each other than the three A genomes, and provide important insights into the relationships between various Brassica tetraploids and their diploid-progenitors at a single-base resolution.
منابع مشابه
DEA with Missing Data: An Interval Data Assignment Approach
In the classical data envelopment analysis (DEA) models, inputs and outputs are assumed as known variables, and these models cannot deal with unknown amounts of variables directly. In recent years, there are few researches on handling missing data. This paper suggests a new interval based approach to apply missing data, which is the modified version of Kousmanen (2009) approach. First, the prop...
متن کاملکاربرد جای گذاری چندگانه در تحقیقات پزشکی و اپیدمیولوژی
Data missing, which occurs for different reasons, is an unavoidable problem in epidemiological studies. It is quite widespread and, therefore, it is considered as a challenge in research design and data analysis by many methodologists. Complete case analysis is often used in studies with missing data however, this approach may result in inaccurate estimates and inferences due to bias associated...
متن کاملPerformance evaluation of different estimation methods for missing rainfall data
There are numerous methods to estimate missing values of which some are used depending on the data type and regional climatic characteristics. In this research, part of the monthly precipitation data in Sarab synoptic station, east Azerbaijan province, Iran was randomly considered missing values. In order to study the effectiveness of various methods to estimate missing data, by seven classic s...
متن کاملComparing Three Regression Models for Reconstructing Groundwater Level Data (A Case Study)
The base for hydrology studies is accurate data. However, the gaps and shortage of sufficient data exist n the most hydrology data such as underground water data as the most important and cheapest water source, lack of data take places due to various reasons such as Inability to measure and faille to register statistics. Missing data or incorrect statistics, Therefore, estimating the missin...
متن کاملMissing data imputation in multivariable time series data
Multivariate time series data are found in a variety of fields such as bioinformatics, biology, genetics, astronomy, geography and finance. Many time series datasets contain missing data. Multivariate time series missing data imputation is a challenging topic and needs to be carefully considered before learning or predicting time series. Frequent researches have been done on the use of diffe...
متن کامل