Quantifying the proportion of polymorphic mutations that are deleterious or neutral is of fundamental importance to our understanding of evolution, disease genetics and the maintenance of variation genome-wide. Here, we develop an approximation to the distribution of fitness effects (DFE) of segregating single-nucleotide mutations in humans. Unlike previous methods, we do not assume that synonymous mutations are neutral or not strongly selected, and we do not rely on fitting the DFE of all new nonsynonymous mutations to a single probability distribution, which is poorly motivated on a biological level. We rely on a previously developed method that utilizes a variety of published annotations (including conservation scores, protein deleteriousness estimates and regulatory data) to score all mutations in the human genome based on how likely they are to be affected by negative selection, controlling for mutation rate. We map this and other conservation scores to a scale of fitness coefficients via maximum likelihood using diffusion theory and a Poisson random field model on SNP data. Our method serves to approximate the deleterious DFE of mutations that are segregating, regardless of their genomic consequence. We can then compare the proportion of mutations that are negatively selected or neutral across various categories, including different types of regulatory sites. We observe that the distribution of intergenic polymorphisms is highly peaked at neutrality, while the distribution of nonsynonymous polymorphisms has a second peak at . Other types of polymorphisms have shapes that fall roughly in between these two. We find that transcriptional start sites, strong CTCF-enriched elements and enhancers are the regulatory categories with the largest proportion of deleterious polymorphisms.

The distribution of fitness effects (DFE) among new mutations plays a critical role in adaptive evolution and the maintenance of genetic variation. While fitness landscape models predict several key features of the DFE, most theory to date focuses on predictable environmental conditions, while ignoring stochastic environmental fluctuations that feature prominently in the ecology of many organisms. Here, we derive an extension of Fisher's geometric model that incorporates two common effects of environmental variation: (1) non-adaptive genotype-by-environment interactions (GxE), in which the phenotype of a given genotype varies across environmental contexts; and (2) random fluctuation of the fitness optimum, which generates fluctuating selection. We show that both factors cause a mismatch between the DFE within single generations and the distribution of geometric mean fitness effects (averaged over multiple generations) that governs long-term evolutionary change. Such mismatches permit strong evolutionary constraints – despite an abundance of beneficial fitness variation within single environmental contexts – and to conflicting DFE estimates from direct versus indirect inference methods. Finally, our results suggest an intriguing parallel between the genetics and ecology of evolutionary constraints, with environmental fluctuations and pleiotropy placing qualitatively similar limits on the availability of adaptive genetic variation.

The Early Years Foundation Stage Profile (EYFSP) is a teacher assessment of children’s development at the end of the EYFS (the end of the academic year in which the child turns five). This dataset contains the results of the EYFSP by gender and location of school/educational institution. Also includes data by region by ethnic group, language, and free school meal (FSM) eligibility. Indicators include: The percentage of children achieving a Good Level of Development (GLD) The percentage of children achieving at least the expected level across all 17 early learning goals The average total point score across all the early learning goals The EYFS profile was significantly revised from 2021/22. It is therefore not possible to directly compare 2021/22 assessment outcomes with earlier years . Additionally, 2019/20 and 2020/21 data collections were cancelled due to coronavirus (COVID-19). Data files for years up to 2019 are retained on this page for reference, but data from 2021/22 and 2022/23 are in separate files. This dataset is one of the Greater London Authority's measures of Economic Fairness. Click here to find out more.

Provisional deaths registration data for single year of age and average age of death (median and mean) of persons whose death involved coronavirus (COVID-19), England and Wales. Includes deaths due to COVID-19 and breakdowns by sex.

Single-month estimates of employment, unemployment and economic inactivity, UK, rolling three-monthly figures published monthly, seasonally adjusted. Labour Force Survey.

Details of central government tenders and contracts, including those for The Department for Education, will be published on Contracts Finder

https://www.gov.uk/contracts-finder

Contracts Finder is the government's single platform for providing access to public procurement related information and documentation free of charge

Period life expectancy by age and sex for 1980 to 2023 for England, Wales (and combined), Scotland, Northern Ireland, Great Britain, and the UK. Each life table is based on population estimates, births and deaths for a single year.

The LIDAR Composite DTM (Digital Terrain Model) is a raster elevation model covering ~99% of England at 10m spatial resolution. The DTM (Digital Terrain Model) is produced from the last or only laser pulse returned to the sensor. We remove surface objects from the Digital Surface Model (DSM), using bespoke algorithms and manual editing of the data, to produce a terrain model of just the surface.

The digital terrain model has been resampled to 10 metres from the LIDAR Composite DTM 2m dataset using a bilinear interpolation technique.

Produced by the Environment Agency in 2022, the DTM is derived from a combination of our Time Stamped archive and National LIDAR Programme surveys, which have been merged and re-sampled to give the best possible coverage. Where repeat surveys have been undertaken the newest, best resolution data is used. Where data was resampled a bilinear interpolation was used before being merged.

The 2022 LIDAR Composite contains surveys undertaken between 6th June 2000 and 2nd April 2022. Please refer to the metadata index catalgoues which show for any location which survey was used in the production of the LIDAR composite.

The data is available to download as a single GeoTiff raster aligned to the OS National grid. The data is presented in metres, referenced to Ordinance Survey Newlyn and using the OSTN’15 transformation method. All individual LIDAR surveys going into the production of the composite had a vertical accuracy of +/-15cm RMSE.

Table shows number and proportion of young people aged 16-18 who are not in employment, education or training (NEET). Also in the spreadsheet are figures for those aged 16-24 by region and 'NUTS2/3' areas. These tables now relate to academic age 16-18 which includes some information on those with an actual age of 19 and the information is now calculated on where a young person is resident and not as previously where educated. Therefore, data post Sep 12 cannot be directly compared with data before that. The annual local authority NEET figures provide an estimate, based on average figures for November to January each year. The 2010 data has been taken from the NCCIS database which has been reworked to attribute those in education back to their resident area, which means that this data will not match local CCIS information for this period. This data relies on the original submission containing accurate information about the resident area and should be taken as a guide only. The 16-24 regional data can also be found on the Labour Market Indicators page. Related links: DfE website - NEETS, DfE website - Participation in Education and Training Monthly data only available under license from NCCIS This dataset is one of the Greater London Authority's measures of Economic Fairness. Click here to find out more.

A dataset of all the meta-data for all of the datasets available through the data.gov.uk service. This is provided as a zipped CSV or JSON file. It is published nightly.

Updates: 27 Sep 2017: we've moved all the previous dumps to an S3 bucket at https://dgu-ckan-metadata-dumps.s3-eu-west-1.amazonaws.com/ - This link is now listed here as a data file.

From 13/10/16 we added .v2.jsonl dump, which is set to replace the .json dump (which will be discontinued after a 3 month transition). This is produced using 'ckanapi dump'. It provides an enhanced version of each dataset ('validated', or what you get from package_show in CKAN API v3 - the old json was the unvalidated version). This now includes full details of the organization the dataset is in, rather than just the owner_id. Plus it includes the results of the archival & qa for each dataset and resource, showing whether the link is broken, detected format and stars of openness. It also benefits from being json lines http://jsonlines.org/ format, so you don't need to load the whole thing into memory to parse the json - just a line at a time.

On 12/1/2015 the organizations of the CSV was changed:

• Before this date, each dataset was one line, and resources added as numbered columns. Since a dataset may have up to 300 resources, it ends up with 1025 columns, which is wider than many versions of Excel and Libreoffice will open. And the uncompressed size of 170Mb is more than most will deal with too. It is suggested you load it into a database, ahandle it with a python or ruby script, or use tools such as Refine or Google Fusion Tables.

• After this date, the datasets are provided in one CSV and resources in another. On occasions that you want to join them, you can join them using the (dataset) "Name" column. These are now manageable in spreadsheet software.

You can also use the standard CKAN API if you want to search or get a small section of the data. Please respect the traffic limits in the API: http://data.gov.uk/terms-and-conditions

Population figures over a 25-year period, by single year of age and sex for clinical commissioning groups in England. 2018-based estimates are the latest principal projection.

The census is undertaken by the Office for National Statistics every 10 years and gives us a picture of all the people and households in England and Wales. The most recent census took place in March of 2021.The census asks every household questions about the people who live there and the type of home they live in. In doing so, it helps to build a detailed snapshot of society. Information from the census helps the government and local authorities to plan and fund local services, such as education, doctors' surgeries and roads.Key census statistics for Leicester are published on the open data platform to make information accessible to local services, voluntary and community groups, and residents.Further information about the census and full datasets can be found on the ONS website - https://www.ons.gov.uk/census/aboutcensus/censusproducts

Period life expectancy by age and sex. Each life table is based on population estimates, births and deaths for a single year.

70% of White British households owned their own homes – the highest percentage out of all ethnic groups.

Period life expectancy (ex) values from the national life tables release, presented in time series format. These statistics are for males and females for England, Wales, Scotland, Northern Ireland and the UK.

Annual data on death registrations by single year of age for the UK (1974 onwards) and England and Wales (1963 onwards).

Population figures over a 25-year period, by single year of age and sex for local authorities in England. 2022-based datasets are the latest projection.

National and subnational mid-year population estimates for the UK and its constituent countries by administrative area, age and sex (including components of population change, median age and population density).

Survival estimates for adults diagnosed with cancer, by stage, for years 2012, 2013, 2014 and 2015, England