Biology subjects

Pulman, J. A.

Publications and source records attributed to Pulman, J. A..

3 recordsLinked to original sources

bioRxiv2021

SRF-CLICAL: an approach for patient risk stratification using random forest models

An important part of good clinical care is identifying which patients have a high likelihood of experiencing adverse outcomes. Similarly, due to the significant impact cancer treatment can have on a patients quality of life, it is also important to properly identify which patients are likely to benefit from more aggressive treatment options. As such, models for predictive risk stratification can be extremely useful in clinical decision making. In this paper, we present, Survival Random Forest-Clinical Categorization Algorithm (SRF-CLICAL), a new method for patient risk stratification using random forests for survival, regression and classification. As a proof of concept, we demonstrate this method on two different cohorts of cancer patients.

bioinformatics↗

bioRxiv2020

A contiguous de novo genome assembly of sugar beet EL10 (Beta vulgaris L.)

A contiguous assembly of the inbred EL10 sugar beet (Beta vulgaris ssp. vulgaris) genome was constructed using PacBio long read sequencing, BioNano optical mapping, Hi-C scaffolding, and Illumina short read error correction. The EL10.1 assembly was 540 Mb, of which 96.7% was contained in nine chromosome-sized pseudomolecules with lengths from 52 to 65 Mb, and 31 contigs with a median size of 282 kb that remained unassembled. Gene annotation incorporating RNAseq data and curated sequences via the MAKER annotation pipeline generated 24,255 gene models. Results indicated that the EL10.1 genome assembly is a contiguous genome assembly highly congruent with the published sugar beet reference genome. Gross duplicate gene analyses of EL10.1 revealed little large-scale intra-genome duplication. Reduced gene copy number for well-annotated gene families relative to other core eudicots was observed, especially for transcription factors. Variation in genome size in B. vulgaris was investigated by flow cytometry among 50 individuals drawn from EL10 progeny and three unrelated germplasm accessions, producing estimates from 633 to 875 Mb/1C. Read depth mapping with short-read whole genome sequences from other sugar beet germplasm suggested that relatively few regions of the sugar beet genome appeared associated with high-copy number variation.

genomics↗

bioRxiv2017

A modified GC-specific MAKER gene annotation method reveals improved and novel gene predictions of high and low GC content in Oryza sativa

Accurate structural annotation depends on well-trained gene prediction programs. Training data for gene prediction programs are often chosen randomly from a subset of high-quality genes that ideally represent the variation found within a genome. One aspect of gene variation is GC content, which differs across species and is bimodal in grass genomes. We find that gene prediction programs trained on genes with random GC content do not completely predict all grass genes with extreme GC content. We present a new GC-specific MAKER annotation protocol to predict new and improved gene models and assess the biological significance of this method in Oryza sativa.

bioinformatics↗