Dataset Information

Dataset on cellular and geo-spatial information of a 10?km distance along Akure-Ilesha road.

ABSTRACT: This dataset contains cellular and geo-spatial information of a 10?km distance along Akure-Ilsha road in Ondo state, Nigeria. The data was acquired using a designed data acquisition system which was kept inside golf3 vehicle interfaced with Acer laptop, the data was acquired as the vehicle moves from the reference point (7.39919, 5.05944 ) to its destination point (7.32818, 5.10836), it harvests GSM signal Strengths from a base station in intervals with its time, latitude and longitude simultaneously as the vehicle moves along the travelled rout; the data acquired shows the variation of signal strength against distance along the road from one base station to another in the travelled path. The raw data of this work is hosted in the Mendeley repository DOI:10.17632/tmksc8mkt8.1.

SUBMITTER: Diarah RS

PROVIDER: S-EPMC6322077 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Dataset on cellular and geo-spatial information of a 10 km distance along Akure-Ilesha road.

Diarah Reuben S RS Oyetunji Samson A SA Osueke Christian O CO Onokwai A O AO

Data in brief 20181217

This dataset contains cellular and geo-spatial information of a 10 km distance along Akure-Ilsha road in Ondo state, Nigeria. The data was acquired using a designed data acquisition system which was kept inside golf3 vehicle interfaced with Acer laptop, the data was acquired as the vehicle moves from the reference point (<i>7.39919, 5.05944 )</i> to its destination point (<i>7.32818, 5.10836)</i>, it harvests GSM signal Strengths from a base station in intervals with its time, latitude and longi ...[more]

PMID: 30627603

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Project description:Background: Treatment effectiveness and overall prognosis for glioma patients depend heavily on the genetic and epigenetic factors in each individual tumor. However, intra-tumoral genetic heterogeneity is known to exist and needs to be managed. Currently, evidence for genetic changes varying spatially within the tumor is qualitative, and quantitative data is lacking. We hypothesized that a greater genetic diversity or "genetic distance" would be observed for distinct tumor samples taken with larger physical distances between them. Methods: Stereotactic biopsies were obtained from untreated primary glioma patients as part of a clinical trial between 2011 and 2016, with at least one biopsy pair collected in each case. The physical (Euclidean) distance between biopsy sites was determined using coordinates from imaging studies. The tissue samples underwent whole exome DNA sequencing and epigenetic methylation profiling and genomic distances were defined in three separate ways derived from differences in number of genes, copy number variations (CNV), and methylation profiles. Results: Of the 31 patients recruited to the trial, 23 were included in DNA methylation analysis, for a total of 71 tissue samples (14 female, 9 male patients, age range 21-80). Samples from an 8 patient subset of the 23 evaluated patients were further included in whole exome and copy number variation analysis. Physical and genomic distances were found to be independently and positively correlated for each of the three genomic distance measures. The correlation coefficients were 0.63, 0.65, and 0.35, respectively for (a) gene level mutations, (b) copy number variation, and (c) methylation status. We also derived quantitative linear relationships between physical and genomic distances. Conclusion: Primary brain tumors are genetically heterogeneous, and the physical distance within a given glioma correlates to genomic distance using multiple orthogonal genomic assessments. These data should be helpful in the clinical diagnostic and therapeutic management of glioma, for example by: managing sampling error, and estimating genetic heterogeneity using simple imaging inputs.

Project description:Estimating population density and population dynamics is essential for understanding primate ecology and relies on robust methods. While distance sampling theory provides a robust framework for estimating animal abundance, implementing a constrained, non-systematic transect design could bias density estimates. Here, we assessed potential bias associated with line distance sampling surveys along roads based on a case study with olive baboons (Papio anubis) in Lake Manyara National Park (Tanzania). This was achieved by comparing density estimates of olive baboons derived from road transect surveys with density estimates derived from estimating the maximum number of social groups (via sleeping site counts) and multiplying this metric with the estimated average size of social groups. From 2011 to 2019, we counted olive baboons along road transects, estimated survey-specific densities in a distance sampling framework, and assessed temporal population trends. Based on the fitted half-normal detection function, the mean density was 132.5 baboons km-2 (95% CI: 110.4-159.2), however, detection models did not fit well due to heaping of sightings on and near the transects. Density estimates were associated with relatively wide confidence intervals that were mostly caused by encounter rate variance. Based on a generalized additive model, baboon densities were greater during the rainy seasons compared to the dry seasons but did not show marked annual trends. Compared to estimates derived from the alternative method (sleeping site survey), distance sampling along road transects overestimated the abundance of baboons more than threefold. Possibly, this overestimation was caused by the preferred use of roads by baboons. While being a frequently used technique (due to its relative ease of implementation compared to spatially randomized survey techniques), inferring population density of baboons (and possibly other species) based on road transects should be treated with caution. Beyond these methodological concerns and considering only the most conservative estimates, baboon densities in LMNP are among the highest across their geographic distribution range.

Dataset Information

Dataset on cellular and geo-spatial information of a 10?km distance along Akure-Ilesha road.

Publications

Dataset on cellular and geo-spatial information of a 10 km distance along Akure-Ilesha road.

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Dataset Information

Dataset on cellular and geo-spatial information of a 10?km distance along Akure-Ilesha road.

Publications

Dataset on cellular and geo-spatial information of a 10 km distance along Akure-Ilesha road.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset on cellular and geo-spatial information of a 10 km distance along Akure-Ilesha road.