Dataset Information

Optimal scaling of digital transcriptomes.

ABSTRACT: Deep sequencing of transcriptomes has become an indispensable tool for biology, enabling expression levels for thousands of genes to be compared across multiple samples. Since transcript counts scale with sequencing depth, counts from different samples must be normalized to a common scale prior to comparison. We analyzed fifteen existing and novel algorithms for normalizing transcript counts, and evaluated the effectiveness of the resulting normalizations. For this purpose we defined two novel and mutually independent metrics: (1) the number of "uniform" genes (genes whose normalized expression levels have a sufficiently low coefficient of variation), and (2) low Spearman correlation between normalized expression profiles of gene pairs. We also define four novel algorithms, one of which explicitly maximizes the number of uniform genes, and compared the performance of all fifteen algorithms. The two most commonly used methods (scaling to a fixed total value, or equalizing the expression of certain 'housekeeping' genes) yielded particularly poor results, surpassed even by normalization based on randomly selected gene sets. Conversely, seven of the algorithms approached what appears to be optimal normalization. Three of these algorithms rely on the identification of "ubiquitous" genes: genes expressed in all the samples studied, but never at very high or very low levels. We demonstrate that these include a "core" of genes expressed in many tissues in a mutually consistent pattern, which is suitable for use as an internal normalization guide. The new methods yield robustly normalized expression values, which is a prerequisite for the identification of differentially expressed and tissue-specific genes as potential biomarkers.

SUBMITTER: Glusman G

PROVIDER: S-EPMC3819321 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Optimal scaling of digital transcriptomes.

Glusman Gustavo G Caballero Juan J Robinson Max M Kutlu Burak B Hood Leroy L

PloS one 20131106 11

Deep sequencing of transcriptomes has become an indispensable tool for biology, enabling expression levels for thousands of genes to be compared across multiple samples. Since transcript counts scale with sequencing depth, counts from different samples must be normalized to a common scale prior to comparison. We analyzed fifteen existing and novel algorithms for normalizing transcript counts, and evaluated the effectiveness of the resulting normalizations. For this purpose we defined two novel a ...[more]

PMID: 24223126

Similar Datasets

Project description:Development time is a critical life-history trait that has profound effects on organism fitness and on population growth rates. For ectotherms, development time is strongly influenced by temperature and is predicted to scale with body mass to the quarter power based on 1) the ontogenetic growth model of the metabolic theory of ecology which describes a bioenergetic balance between tissue maintenance and growth given the scaling relationship between metabolism and body size, and 2) numerous studies, primarily of vertebrate endotherms, that largely support this prediction. However, few studies have investigated the allometry of development time among invertebrates, including insects. Abundant data on development of diverse insects provides an ideal opportunity to better understand the scaling of development time in this ecologically and economically important group. Insects develop more quickly at warmer temperatures until reaching a minimum development time at some optimal temperature, after which development slows. We evaluated the allometry of insect development time by compiling estimates of minimum development time and optimal developmental temperature for 361 insect species from 16 orders with body mass varying over nearly 6 orders of magnitude. Allometric scaling exponents varied with the statistical approach: standardized major axis regression supported the predicted quarter-power scaling relationship, but ordinary and phylogenetic generalized least squares did not. Regardless of the statistical approach, body size alone explained less than 28% of the variation in development time. Models that also included optimal temperature explained over 50% of the variation in development time. Warm-adapted insects developed more quickly, regardless of body size, supporting the "hotter is better" hypothesis that posits that ectotherms have a limited ability to evolutionarily compensate for the depressing effects of low temperatures on rates of biological processes. The remaining unexplained variation in development time likely reflects additional ecological and evolutionary differences among insect species.

Project description:Background:Digital templating systems foster patient-specific measurements for preoperative planning. Questions/Purposes:We aim (1) to verify the accuracy of a templating system, (2) to describe the effects of scaling marker position on the accuracy of digital templating of the hip, and (3) to provide a practical guide for scaling marker position using patient body mass index (BMI). Methods:A scaling sphere was placed in five positions along the anterior-posterior axis of an acetabular implant and pelvis phantom, and x-rays were obtained. Each radiograph was templated for the acetabular component and recorded. A retrospective review identified CT scans of preoperative hip arthroplasty cases. The center of the greater trochanter was calculated from these CT scans as the percent distance from the anterior thigh and recorded with the patient's BMI. Results:By centering the scaling sphere on the acetabular component, an accurate cup size was achieved. A difference of 3.5 cm in sphere placement resulted in a full cup size magnification error. Positioning the scaling sphere at the level of the pubic symphysis resulted in a difference of four cup sizes. This patient population had an average BMI of 28.72 kg/m2 (standard deviation 6.26 kg/m2) and an average position of the center of the greater trochanter of 51% (standard deviation of 6%) from the anterior surface of thigh. Conclusions:Digital templating relies on scaling marker position to accurately estimate implant size. Based on the findings in this study, scaling markers for hip imaging should be placed laterally, mid-thigh in the anterior-posterior direction for patients with a BMI between 25 and 40 kg/m2. If abnormal hip anatomy or extremes of BMI are discovered, then scaling sphere positioning should be optimized on a case-by-case basis. Digital templating systems for total hip arthroplasty must use precisely placed scaling markers at the level of the hip joint to allow for accurate implant size estimation.

Dataset Information

Optimal scaling of digital transcriptomes.

Publications

Optimal scaling of digital transcriptomes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets