In 2023, the metropolitan area of New York-Newark-Jersey City had the biggest population in the United States. Based on annual estimates from the census, the metropolitan area had around 19.5 million inhabitants, which was a slight decrease from the previous year. The Los Angeles and Chicago metro areas rounded out the top three. What is a metropolitan statistical area? In general, a metropolitan statistical area (MSA) is a core urbanized area with a population of at least 50,000 inhabitants – the smallest MSA is Carson City, with an estimated population of nearly 56,000. The urban area is made bigger by adjacent communities that are socially and economically linked to the center. MSAs are particularly helpful in tracking demographic change over time in large communities and allow officials to see where the largest pockets of inhabitants are in the country. How many MSAs are in the United States? There were 421 metropolitan statistical areas across the U.S. as of July 2021. The largest city in each MSA is designated the principal city and will be the first name in the title. An additional two cities can be added to the title, and these will be listed in population order based on the most recent census. So, in the example of New York-Newark-Jersey City, New York has the highest population, while Jersey City has the lowest. The U.S. Census Bureau conducts an official population count every ten years, and the new count is expected to be announced by the end of 2030.

The National Crime Victimization Survey (NCVS), previously the National Crime Survey (NCS), has been collecting data on personal and household victimization through an ongoing survey of a nationally-representative sample of residential addresses since 1973. The survey is administered by the United States Census Bureau (under the United States Department of Commerce) on behalf of the Bureau of Justice Statistics (under the United States Department of Justice). Occasionally there have been extract or supplement files created from the NCVS and NCS data series. This extract contains two data files, a weighted person-based file, and a weighted incident-based file, which contain the "core" counties within the top 40 National Crime Victimization Survey Metropolitan Statistical Areas (MSAs). Core counties within these MSAs are defined as those self-representing primary sampling units that are common to the MSA definitions determined by the Office of Management and Budget for the 1970-based, 1980-based, and 1990-based sample designs. Each MSA is comprised of only the core counties and not all counties within the MSA. The person-based file contains select household and person variables for all people in NCVS-interviewed households in the core counties of the 40 largest MSAs from January 1979 through December 2004. The incident-based file contains select household, person, and incident variables for persons who reported a violent crime within any of the core counties of the 40 largest MSAs from January 1979 through December 2004. Household, person, and incident information for persons reporting non-violent crime are excluded from this file. The 40 largest MSAs were determined based on the number of household interviews in an MSA.

Through a cooperative agreement, RTI International worked with the Bureau of Justice Statistics (BJS) to create public-use files of victimization data for the 52 largest metropolitan statistical areas (MSAs) covering the 2000-2015 survey years. The National Crime Victimization Survey (NCVS) is one of two national indicators of crime in the U.S. Historically, NCVS estimates of crime were not available at the state or local level because, prior to 2016, the NCVS sample was designed to exclusively produce national estimates. It is important to be able to understand victimization and victimization risk at the local level to inform and improve crime prevention efforts, investigation and victim response practices, and the location and mix of victim services. To protect respondent confidentiality, with a few exceptions, subnational identifiers are traditionally not included on NCVS public-use files. Instead, information required to conduct analyses of crime at subnational levels must be accessed through a Federal Statistical Research Data Center (FSRDC) by obtaining Special Sworn Status from the U.S. Census Bureau. To provide a greater number of analysts with access to NCVS subnational data, in 2007 the Bureau of Justice Statistics (BJS) released a public-use file containing person- and incident-level data from 1979-2004 for the "core" counties (i.e., self-representing PSUs) within the 40 largest metropolitan statistical areas (MSAs). To accommodate interest from analysts and other interested parties in updating the file with more recent data, BJS has created public-use files for the 52 largest MSAs covering the 2000-2015 survey years. The 52 MSAs included on these files are those with a 2015 population of 1 million or more persons and an average annual NCVS sample size of at least 250 persons during the period of 2006-2015. While some of the MSAs from these files were also included on the 1979-2004 version, the definitions used to define MSAs are not the same. The 1979-2004 files were based on the "core" counties that were common to the MSA definitions determined by the Office of Management and Budget (OMB) for the 1970-, 1980-, and 1990-based NCVS sample designs. For the current files (i.e., 2000-2015), MSA definitions are based on the most recent delineation files available from OMB at the time of data collection for each survey year included on the files.

Graph and download economic data for Resident Population in San Diego-Carlsbad, CA (MSA) (SDIPOP) from 2000 to 2024 about San Diego, residents, CA, population, and USA.

The 2006 Second Edition TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER database. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on the latest available governmental unit boundaries. The Census TIGER database represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The 2006 Second Edition TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. This shapefile represents the 2000 Census Metropolitan Statistical Areas (MSA) for Los Alamos County stored in the 2006 TIGER Second Edition dataset.

GPN-MSA predictions for all possible SNPs in the human genome (~9 billion)

For more information check out our paper and repository.

  Querying specific variants or genes

Install the latest tabix:In your current conda environment (might be slow):conda install -c bioconda -c conda-forge htslib=1.18

or in a new conda environment:conda create -n tabix -c bioconda -c conda-forge htslib=1.18 conda activate tabix

Query a specific region (e.g. BRCA1), from the remote file:… See the full description on the dataset page: https://huggingface.co/datasets/songlab/gpn-msa-hg38-scores.

Bootstrapping results for the example MSAs from Fig 1.

These data were derived from the original DEMs produced by the BOREAS HYD-08 team. The original DEMs were in the UTM projection, while this product is projected in the AEAC projection (see Section 7 for further projection details). The pixel size of the data is 100 meters, which is appropriate for the 1:50,000- scale contours from which the DEMs were made. The original data were compiled from information available in the 1970s and 1980s. This data set covers the two MSAs that are contained within the SSA and the NSA.

Graph and download economic data for Resident Population in San Francisco-Oakland-Hayward, CA (MSA) (SFCPOP) from 2000 to 2022 about San Francisco, residents, CA, population, and USA.

Crime data assembled by census block group for the MSA from the Applied Geographic Solutions' (AGS) 1999 and 2005 'CrimeRisk' databases distributed by the Tetrad Computer Applications Inc. CrimeRisk is the result of an extensive analysis of FBI crime statistics. Based on detailed modeling of the relationships between crime and demographics, CrimeRisk provides an accurate view of the relative risk of specific crime types at the block group level. Data from 1990 - 1996,1999, and 2004-2005 were used to compute the attributes, please refer to the 'Supplemental Information' section of the metadata for more details. Attributes are available for two categories of crimes, personal crimes and property crimes, along with total and personal crime indices. Attributes for personal crimes include murder, rape, robbery, and assault. Attributes for property crimes include burglary, larceny, and mother vehicle theft. 12 block groups have no attribute information. CrimeRisk is a block group and higher level geographic database consisting of a series of standardized indexes for a range of serious crimes against both persons and property. It is derived from an extensive analysis of several years of crime reports from the vast majority of law enforcement jurisdictions nationwide. The crimes included in the database are the "Part I" crimes and include murder, rape, robbery, assault, burglary, theft, and motor vehicle theft. These categories are the primary reporting categories used by the FBI in its Uniform Crime Report (UCR), with the exception of Arson, for which data is very inconsistently reported at the jurisdictional level. Part II crimes are not reported in the detail databases and are generally available only for selected areas or at high levels of geography. In accordance with the reporting procedures using in the UCR reports, aggregate indexes have been prepared for personal and property crimes separately, as well as a total index. While this provides a useful measure of the relative "overall" crime rate in an area, it must be recognized that these are unweighted indexes, in that a murder is weighted no more heavily than a purse snatching in the computation. For this reason, caution is advised when using any of the aggregate index values. The block group boundaries used in the dataset come from TeleAtlas's (formerly GDT) Dynamap data, and are consistent with all other block group boundaries in the BES geodatabase.

   This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase.


   The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive.


   The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders.


   Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.


   This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase.


   The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive.


   The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders.


   Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

These are the data used for the Racial and Ethnic Diversity for the Austin MSA story map. The story map was published July 2024 but displays data from 2000, 2010, and 2020.

Decennial census data were used for all three years. 2000: DEC Summary File 1, P004 2010: DEC Redistricting Data (PL 94-171), P2 2020: DEC Redistricting Data (PL 94-171), P2

Geographic crosswalks were used to harmonize 2000, 2010, and 2020 geographies.

Racial and Ethnic Diversity Index for the Austin MSA Storymap: https://storymaps.arcgis.com/stories/88ee265f00934af7a750b57f7faebd2c

City of Austin Open Data Terms of Use – https://data.austintexas.gov/stories/s/ranj-cccq

Training windows for GPN-MSA-Sapiens

For more information check out our paper and repository. Path in Snakemake: results/dataset/multiz100way/89/128/64/True/defined.phastCons.percentile-75_0.05_0.001

Occurrences of the development types detailed in Table 1.

These DEMs were produced from digitized contours at a cell resolution of 100 meters. Vector contours of the area were used as input to a software package that interpolates between contours to create a DEM representing the terrain surface. The vector contours had a contour interval of 25 feet. The data cover the BOREAS MSAs of the SSA and NSA and are given in a UTM map projection.

An interactive Web application that enables users to visualize multiple alignments created by database search results or other software applications. The MSA Viewer allows users to upload an alignment and set a master sequence and to explore the data using features such as zooming and changing of coloration.

Graph and download economic data for All Employees: Government: State Government in Sacramento-Roseville-Folsom, CA (MSA) (SMU06409009092000001SA) from Jan 1990 to Jun 2025 about state govt, Sacramento, CA, government, employment, and USA.

Graph and download economic data for Resident Population in Rochester, MN (MSA) (ROTPOP) from 2000 to 2024 about Rochester, MN, residents, population, and USA.

Graph and download economic data for Resident Population in Los Angeles-Long Beach-Santa Ana, CA (MSA) (LOSPOP) from 2000 to 2009 about Los Angeles, residents, CA, population, and USA.

Graph and download economic data for Resident Population in Baton Rouge, LA (MSA) (BTRPOP) from 2000 to 2024 about Baton Rouge, LA, residents, population, and USA.

Graph and download economic data for Resident Population in Portland-Vancouver-Hillsboro, OR-WA (MSA) (PORPOP) from 2000 to 2024 about Portland, OR, WA, residents, population, and USA.