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Your search keyword '"Alomran A"' showing total 11 results
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11 results on '"Alomran A"'

2. Colorectal cancer in patients with SARS-CoV-2: a systematic review and meta-analysis

Author

Alhumaid, Saad, Al Mutair, Abbas, Busubaih, Jawad S., Al Dossary, Nourah, Alsuliman, Murtadha, Baltyour, Sarah A., Alissa, Ibrahim, Al Hassar, Hassan I., Al Aithan, Noor A., Albassri, Hani A., AlOmran, Suliman A., ALGhazal, Raed M., Busbaih, Ahmed, Alsalem, Nasser A., Alagnam, Waseem, Alyousef, Mohammed Y., Alseffay, Abdulaziz U., Al Aish, Hussain A., Aldiaram, Ali, Al eissa, Hisham A., Alhumaid, Murtadha A., Bukhamseen, Ali N., Al mutared, Koblan M., Aljwisim, Abdullah H., Twibah, Abdullah M., AlSaeed, Meteab M., Alkhalaf, Hussien A., ALShakhs, Fatemah M., Koritala, Thoyaja, Al-Tawfiq, Jaffar A., Dhama, Kuldeep, Rabaan, Ali A., and Al-Omari, Awad

Published
2022
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4. Coagulopathy of hospitalised COVID-19: A Pragmatic Randomised Controlled Trial of Therapeutic Anticoagulation versus Standard Care as a Rapid Response to the COVID-19 Pandemic (RAPID COVID COAG – RAPID Trial): A structured summary of a study protocol for a randomised controlled trial

Author

Sholzberg, Michelle, Tang, Grace H., Negri, Elnara, Rahhal, Hassan, Kreuziger, Lisa Baumann, Pompilio, Carlos E., James, Paula, Fralick, Michael, AlHamzah, Musaad, Alomran, Faris, Tseng, Eric, Lim, Gloria, Lillicrap, David, Carrier, Marc, Áinle, Fionnuala Ní, Beckett, Andrew, da Costa, Bruno R., Thorpe, Kevin, Middeldorp, Saskia, Lee, Agnes, Cushman, Mary, and Jüni, Peter

Published
2021
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6. Clinical features and prognostic factors of intensive and non-intensive 1014 COVID-19 patients: an experience cohort from Alahsa, Saudi Arabia

Author

Alhumaid, Saad, Al Mutair, Abbas, Al Alawi, Zainab, Al Salman, Khulud, Al Dossary, Nourah, Omar, Ahmed, Alismail, Mossa, Al Ghazal, Ali M., Jubarah, Mahdi Bu, Al Shaikh, Hanan, Al Mahdi, Maher M., Alsabati, Sarah Y., Philip, Dayas K., Alyousef, Mohammed Y., Al Brahim, Abdulsatar H., Al Athan, Maitham S., Alomran, Salamah A., Ahmed, Hatim S., Al-Shammari, Haifa, Elhazmi, Alyaa, Rabaan, Ali A., Al-Tawfiq, Jaffar A., and Al-Omari, Awad

Published
2021
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10. SCReadCounts: estimation of cell-level SNVs expression from scRNA-seq data

Author

Yu Chen, Hongyu Liu, Nawaf Alomran, Nathan Edwards, Pavlos Bousounis, N M Prashant, Anelia Horvath, and Mercedeh Movassagh

Subjects
Somatic cell, SNP, Computational biology, QH426-470, Biology, Proteomics, medicine.disease_cause, Polymorphism, Single Nucleotide, Germline mutation, RNA, Small Cytoplasmic, SNV, scRNA-seq, Genetics, medicine, Coding region, Single cell, Allele, Single cell RNA sequencing, X chromosome, Mutation, Sequence Analysis, RNA, Methodology Article, Somatic mutation, Allele expression, RNA, DNA microarray, Single-Cell Analysis, TP248.13-248.65, Software, Biotechnology
Abstract

Background Recent studies have demonstrated the utility of scRNA-seq SNVs to distinguish tumor from normal cells, characterize intra-tumoral heterogeneity, and define mutation-associated expression signatures. In addition to cancer studies, SNVs from single cells have been useful in studies of transcriptional burst kinetics, allelic expression, chromosome X inactivation, ploidy estimations, and haplotype inference. Results To aid these types of studies, we have developed a tool, SCReadCounts, for cell-level tabulation of the sequencing read counts bearing SNV reference and variant alleles from barcoded scRNA-seq alignments. Provided genomic loci and expected alleles, SCReadCounts generates cell-SNV matrices with the absolute variant- and reference-harboring read counts, as well as cell-SNV matrices of expressed Variant Allele Fraction (VAFRNA) suitable for a variety of downstream applications. We demonstrate three different SCReadCounts applications on 59,884 cells from seven neuroblastoma samples: (1) estimation of cell-level expression of known somatic mutations and RNA-editing sites, (2) estimation of cell- level allele expression of biallelic SNVs, and (3) a discovery mode assessment of the reference and each of the three alternative nucleotides at genomic positions of interest that does not require prior SNV information. For the later, we applied SCReadCounts on the coding regions of KRAS, where it identified known and novel somatic mutations in a low-to-moderate proportion of cells. The SCReadCounts read counts module is benchmarked against the analogous modules of GATK and Samtools. SCReadCounts is freely available (https://github.com/HorvathLab/NGS) as 64-bit self-contained binary distributions for Linux and MacOS, in addition to Python source. Conclusions SCReadCounts supplies a fast and efficient solution for estimation of cell-level SNV expression from scRNA-seq data. SCReadCounts enables distinguishing cells with monoallelic reference expression from those with no gene expression and is applicable to assess SNVs present in only a small proportion of the cells, such as somatic mutations in cancer.

Published
2021

11. Al Kharj diabetic patients’ perception about diabetes mellitus using revised-illness perception questionnaire (IPQ-R).

Author

Al-Ghamdi, Sameer, Ahmad, Gulfam, Hassan Ali, Ali, Bahakim, Nasraddin, Alomran, Salman, Alhowikan, Waleed, Almutairi, Salman, Basalem, Tariq, and Aljuaid, Faisal

Subjects
CHRONIC diseases, STATISTICAL correlation, PEOPLE with diabetes, DIET, FOOD habits, GENETIC disorders, TYPE 2 diabetes, SENSORY perception, PRIMARY health care, QUESTIONNAIRES, RESEARCH evaluation, HEALTH literacy, ACUTE diseases, PSYCHOLOGY
Abstract

Background: Illness perception questionnaires for various medical conditions have become more useful in recent years. However, very few have addressed this issue for Type 2 diabetes in Saudi Arabia. Methods: A self-administered questionnaire was distributed to Type 2 diabetic patients attendees of primary health care centers and Al Kharj Military Industries Corporation Hospital in Al Kharj, Saudi Arabia, from November 24th 2016 to April 24th, 2017. Results: Overall, 383 of the 500 distributed questionnaires were returned, and 187 were males (48.8). Most participants understood that what led to diabetes was hereditary, including diet or eating habits. The Cronbach’s alpha value for identity, timeline (cyclical), and emotional factors were relatively high, showing that these scales had a strong level of internal consistency; it also showed that the timeline (acute/chronic) and treatment control scales were low, thus showing internal consistency of these scales. Cronbach’s value of coherence and consequences scales were low. Conclusion: Saudis with type 2 diabetes mellitus had appropriate knowledge of their disease. They agreed that diabetes was likely to be permanent and would have major consequences on their lives. [ABSTRACT FROM AUTHOR]

Published
2018
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