Error Rates and Powers in Genome-Scale RNAi Screens

In most genome-scale RNA interference (RNAi) screens, the ultimate goal is to select siRNAs with a large inhibition or activation effect. The selection of hits typically requires statistical control of 2 errors: false positives and false negatives. Traditional methods of controlling false positives and false negatives do not take into account the important feature in RNAi screens: many small-interfering RNAs (siRNAs) may have very small but real nonzero average effects on the measured response and thus cannot allow us to effectively control false positives and false negatives. To address for deficiencies in the application of traditional approaches in RNAi screening, the author proposes a new method for controlling false positives and false negatives in RNAi high-throughput screens. The false negatives are statistically controlled through a false-negative rate (FNR) or false nondiscovery rate (FNDR). FNR is the proportion of false negatives among all siRNAs examined, whereas FNDR is the proportion of false negatives among declared nonhits. The author also proposes new concepts, q*-value and p*-value, to control FNR and FNDR, respectively. The proposed method should have broad utility for hit selection in which one needs to control both false discovery and false nondiscovery rates in genome-scale RNAi screens in a robust manner.

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Do forests ‘fall silent’ following aerial applications of 1080 poison? Development and application of bird monitoring methods using automated sound recording devices

10.26686/wgtn.17065226 ◽

2021 ◽

Author(s):

◽

Asher Cook

Keyword(s):

New Zealand ◽

False Negative ◽

False Negative Rate ◽

Bird Species ◽

Quantitative Information ◽

Error Rates ◽

Type I ◽

Monitoring Methods ◽

Manual Method ◽

Automated Method

<p>Electronic bioacoustic techniques are providing new and effective ways of monitoring birds and have a number of advantages over other traditional monitoring methods. Given the increasing popularity of bioacoustic methods, and the difficulties associated with automated analyses (e.g. high Type I error rates), it is important that the most effective ways of scoring audio recordings are investigated. In Chapter Two I describe a novel sub-sampling and scoring technique (the ‘10 in 60 sec’ method) which estimates the vocal conspicuousness of bird species through the use of repeated presence-absence counts and compare its performance with a current manual method. The ‘10 in 60 sec’ approach reduced variability in estimates of vocal conspicuousness, significantly increased the number of species detected per count and reduced temporal autocorrelation. I propose that the ‘10 in 60 sec’ method will have greater overall ability to detect changes in underlying birdsong parameters and hence provide more informative data to scientists and conservation managers. It is often anecdotally suggested that forests ‘fall silent’ and are devoid of birdsong following aerial 1080 operations. However, it is difficult to objectively assess the validity of this claim without quantitative information that addresses the claim specifically. Therefore in Chapter Three I applied the methodological framework outlined in Chapter Two to answer a controversial conservation question: Do New Zealand forests ‘fall silent’ after aerial 1080 operations? At the community level I found no evidence for a reduction in birdsong after the 1080 operation and eight out of the nine bird taxa showed no evidence for a decline in vocal conspicuousness. Only one species, tomtit (Petroica macrocephala), showed evidence for a decline in vocal conspicuousness, though this effect was non-significant after applying a correction for multiple tests. In Chapter Four I used tomtits as a case study species to compare manual and automated approaches to: (1) estimating vocal conspicuousness and (2) determine the feasibility of using an automated detector on a New Zealand passerine. I found that data from the automated method were significantly positively correlated with the manual method although the relationship was not particularly strong (Pearson’s r = 0.62, P < 0.0001). The automated method suffered from a relatively high false negative rate and the data it produced did not reveal a decline in tomtit call rates following the 1080 drop. Given the relatively poor performance of the automated method, I propose that the automatic detector developed in this thesis requires further refinement before it is suitable for answering management-level questions for tomtit populations. However, as pattern recognition technology continues to improve automated methods are likely to become more viable in the future.</p>

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Do forests ‘fall silent’ following aerial applications of 1080 poison? Development and application of bird monitoring methods using automated sound recording devices

10.26686/wgtn.17065226.v1 ◽

2021 ◽

Author(s):

◽

Asher Cook

Keyword(s):

New Zealand ◽

False Negative ◽

False Negative Rate ◽

Bird Species ◽

Quantitative Information ◽

Error Rates ◽

Type I ◽

Monitoring Methods ◽

Manual Method ◽

Automated Method

<p>Electronic bioacoustic techniques are providing new and effective ways of monitoring birds and have a number of advantages over other traditional monitoring methods. Given the increasing popularity of bioacoustic methods, and the difficulties associated with automated analyses (e.g. high Type I error rates), it is important that the most effective ways of scoring audio recordings are investigated. In Chapter Two I describe a novel sub-sampling and scoring technique (the ‘10 in 60 sec’ method) which estimates the vocal conspicuousness of bird species through the use of repeated presence-absence counts and compare its performance with a current manual method. The ‘10 in 60 sec’ approach reduced variability in estimates of vocal conspicuousness, significantly increased the number of species detected per count and reduced temporal autocorrelation. I propose that the ‘10 in 60 sec’ method will have greater overall ability to detect changes in underlying birdsong parameters and hence provide more informative data to scientists and conservation managers. It is often anecdotally suggested that forests ‘fall silent’ and are devoid of birdsong following aerial 1080 operations. However, it is difficult to objectively assess the validity of this claim without quantitative information that addresses the claim specifically. Therefore in Chapter Three I applied the methodological framework outlined in Chapter Two to answer a controversial conservation question: Do New Zealand forests ‘fall silent’ after aerial 1080 operations? At the community level I found no evidence for a reduction in birdsong after the 1080 operation and eight out of the nine bird taxa showed no evidence for a decline in vocal conspicuousness. Only one species, tomtit (Petroica macrocephala), showed evidence for a decline in vocal conspicuousness, though this effect was non-significant after applying a correction for multiple tests. In Chapter Four I used tomtits as a case study species to compare manual and automated approaches to: (1) estimating vocal conspicuousness and (2) determine the feasibility of using an automated detector on a New Zealand passerine. I found that data from the automated method were significantly positively correlated with the manual method although the relationship was not particularly strong (Pearson’s r = 0.62, P < 0.0001). The automated method suffered from a relatively high false negative rate and the data it produced did not reveal a decline in tomtit call rates following the 1080 drop. Given the relatively poor performance of the automated method, I propose that the automatic detector developed in this thesis requires further refinement before it is suitable for answering management-level questions for tomtit populations. However, as pattern recognition technology continues to improve automated methods are likely to become more viable in the future.</p>

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Handling Water Reflections for Computer Vision in Aquaculture

Transactions of the ASABE ◽

10.13031/trans.12466 ◽

2018 ◽

Vol 61 (2) ◽

pp. 469-479 ◽

Cited By ~ 4

Author(s):

Chao Zhou ◽

Chuanheng Sun ◽

Kai Lin ◽

Daming Xu ◽

Qiang Guo ◽

...

Keyword(s):

Image Processing ◽

Computer Vision ◽

Support Vector Machine ◽

Classification Accuracy ◽

False Positive Rate ◽

False Negative ◽

False Negative Rate ◽

Image Texture ◽

Support Vector ◽

Type I

Abstract. In aquaculture, almost all images collected of an aquaculture scene contain reflections, which often affect the results and accuracy of machine vision. Classifying these images and obtaining images of interest are key to subsequent image processing. The purpose of this study was to identify useful images and remove images that had a substantial effect on the results of image processing for computer vision in aquaculture. In this study, a method for classification of reflective frames based on image texture and a support vector machine (SVM) was proposed for an actual aquaculture site. Objectives of this study were to: (1) develop an algorithm to improve the speed of the method and to ensure that the method has a high classification accuracy, (2) design an algorithm to improve the intelligence and adaptability of the classification, and (3) demonstrate the performance of the method. The results show that the average classification accuracy, false positive rate, and false negative rate for two types of reflective frames (type I and II) were 96.34%, 4.65%, and 2.23%, respectively. In addition, the running time was very low (1.25 s). This strategy also displayed considerable adaptability and could be used to obtain useful images or remove images that have substantial effects on the accuracy of image processing results, thereby improving the applicability of computer vision in aquaculture. Keywords: Aquaculture, Genetic algorithm, Gray level-gradient co-occurrence matrix, Principal component analysis, Reflection frame, Support vector machine.

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Comparative study of ultrasonographic findings with the operative findings of biliary surgery

Journal of Surgical Sciences ◽

10.3329/jss.v22i1.44011 ◽

2020 ◽

Vol 22 (1) ◽

pp. 25-29

Author(s):

Zubayer Ahmad ◽

Mohammad Ali ◽

Kazi lsrat Jahan ◽

ABM Khurshid Alam ◽

G M Morshed

Keyword(s):

Bile Duct ◽

Common Bile Duct ◽

Imaging Modality ◽

False Positive Rate ◽

Gallstone Disease ◽

False Negative ◽

False Negative Rate ◽

Biliary Disease ◽

Biliary Surgery ◽

Operative Findings

Background: Biliary disease is one of the most common surgical problems encountered all over the world. Ultrasound is widely accepted for the diagnosis of biliary system disease. However, it is a highly operator dependent imaging modality and its diagnostic success is also influenced by the situation, such as non-fasting, obesity, intestinal gas. Objective: To compare the ultrasonographic findings with the peroperative findings in biliary surgery. Methods: This prospective study was conducted in General Hospital, comilla between the periods of July 2006 to June 2008 among 300 patients with biliary diseases for which operative treatment is planned. Comparison between sonographic findings with operative findings was performed. Results: Right hypochondriac pain and jaundice were two significant symptoms (93% and 15%). Right hypochondriac tenderness, jaundice and palpable gallbladder were most valuable physical findings (respectively, 40%, 15% and 5%). Out of 252 ultrasonically positive gallbladder, stone were confirmed in 249 cases preoperatively. Sensitivity of USG in diagnosis of gallstone disease was 100%. There was, however, 25% false positive rate detection. Specificity was, however, 75% in this case. USG could demonstrate stone in common bile duct in only 12 out of 30 cases. Sensitivity of the test in diagnosing common bile duct stone was 40%, false negative rate 60%. In the series, ultrasonography sensitivity was 100% in diagnosing stone in cystic duct. USG could detect with relatively good but less sensitivity the presence of chronic cholecystitis (92.3%) and worm inside gallbladder (50%). Conclusion: Ultrasonography is the most important investigation in the diagnosis of biliary disease and a useful test for patients undergoing operative management for planning and anticipating technical difficulties. Journal of Surgical Sciences (2018) Vol. 22 (1): 25-29

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Preliminary Results of MyCog, a Brief Assessment for the Detection of Cognitive Impairment in Primary Care

Innovation in Aging ◽

10.1093/geroni/igaa057.833 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

pp. 259-260

Author(s):

Laura Curtis ◽

Lauren Opsasnick ◽

Julia Yoshino Benavente ◽

Cindy Nowinski ◽

Rachel O’Conor ◽

...

Keyword(s):

Primary Care ◽

Cognitive Impairment ◽

Cognitive Aging ◽

False Positive ◽

False Positive Rate ◽

False Negative ◽

False Negative Rate ◽

Self Report ◽

Card Sorting ◽

Primary Care Settings

Abstract Early detection of Cognitive impairment (CI) is imperative to identify potentially treatable underlying conditions or provide supportive services when due to progressive conditions such as Alzheimer’s Disease. While primary care settings are ideal for identifying CI, it frequently goes undetected. We developed ‘MyCog’, a brief technology-enabled, 2-step assessment to detect CI and dementia in primary care settings. We piloted MyCog in 80 participants 65 and older recruited from an ongoing cognitive aging study. Cases were identified either by a documented diagnosis of dementia or mild cognitive impairment (MCI) or based on a comprehensive cognitive battery. Administered via an iPad, Step 1 consists of a single self-report item indicating concern about memory or other thinking problems and Step 2 includes two cognitive assessments from the NIH Toolbox: Picture Sequence Memory (PSM) and Dimensional Change Card Sorting (DCCS). 39%(31/80) participants were considered cognitively impaired. Those who expressed concern in Step 1 (n=52, 66%) resulted in a 37% false positive and 3% false negative rate. With the addition of the PSM and DCCS assessments in Step 2, the paradigm demonstrated 91% sensitivity, 75% specificity and an area under the ROC curve (AUC)=0.82. Steps 1 and 2 had an average administration time of <7 minutes. We continue to optimize MyCog by 1) examining additional items for Step 1 to reduce the false positive rate and 2) creating a self-administered version to optimize use in clinical settings. With further validation, MyCog offers a practical, scalable paradigm for the routine detection of cognitive impairment and dementia.

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Ultrasound guided needle biopsy of axilla to evaluate nodal metastasis after preoperative systemic therapy in cohort of 106 breast cancers enriched with BRCA1/2 pathogenic variant carriers

Hereditary Cancer in Clinical Practice ◽

10.1186/s13053-021-00187-w ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Baiba Līcīte ◽

Arvīds Irmejs ◽

Jeļena Maksimenko ◽

Pēteris Loža ◽

Genādijs Trofimovičs ◽

...

Keyword(s):

Breast Cancer ◽

Systemic Therapy ◽

False Positive Rate ◽

False Negative ◽

False Negative Rate ◽

Axillary Node ◽

Pathogenic Variant ◽

Axillary Lymph ◽

Ultrasound Guided ◽

Node Positive

Abstract Background Aim of the study is to evaluate the role of ultrasound guided fine needle aspiration cytology (FNAC) in the restaging of node positive breast cancer after preoperative systemic therapy (PST). Methods From January 2016 – October 2020 106 node positive stage IIA-IIIC breast cancer cases undergoing PST were included in the study. 18 (17 %) were carriers of pathogenic variant in BRCA1/2. After PST restaging of axilla was performed with ultrasound and FNAC of the marked and/or the most suspicious axillary node. In 72/106 cases axilla conserving surgery and in 34/106 cases axillary lymph node dissection (ALND) was performed. Results False Positive Rate (FPR) of FNAC after PST in whole cohort and BRCA1/2 positive subgroup is 8 and 0 % and False Negative Rate (FNR) – 43 and 18 % respectively. Overall Sensitivity − 55 %, specificity- 93 %, accuracy 70 %. Conclusion FNAC after PST has low FPR and is useful to predict residual axillary disease and to streamline surgical decision making regarding ALND both in BRCA1/2 positive and negative subgroups. FNR is high in overall cohort and FNAC alone are not able to predict ypCR and omission of further axillary surgery. However, FNAC performance in BRCA1/2 positive subgroup is more promising and further research with larger number of cases is necessary to confirm the results.

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A Method of Segmenting Apples Based on Gray-Centered RGB Color Space

Remote Sensing ◽

10.3390/rs13061211 ◽

2021 ◽

Vol 13 (6) ◽

pp. 1211

Author(s):

Pan Fan ◽

Guodong Lang ◽

Bin Yan ◽

Xiaoyan Lei ◽

Pengju Guo ◽

...

Keyword(s):

Vision System ◽

False Positive Rate ◽

Clustering Algorithms ◽

False Negative ◽

Color Space ◽

False Negative Rate ◽

Feature Selection Method ◽

Image Features ◽

Accurate Identification ◽

Rgb Color Space

In recent years, many agriculture-related problems have been evaluated with the integration of artificial intelligence techniques and remote sensing systems. The rapid and accurate identification of apple targets in an illuminated and unstructured natural orchard is still a key challenge for the picking robot’s vision system. In this paper, by combining local image features and color information, we propose a pixel patch segmentation method based on gray-centered red–green–blue (RGB) color space to address this issue. Different from the existing methods, this method presents a novel color feature selection method that accounts for the influence of illumination and shadow in apple images. By exploring both color features and local variation in apple images, the proposed method could effectively distinguish the apple fruit pixels from other pixels. Compared with the classical segmentation methods and conventional clustering algorithms as well as the popular deep-learning segmentation algorithms, the proposed method can segment apple images more accurately and effectively. The proposed method was tested on 180 apple images. It offered an average accuracy rate of 99.26%, recall rate of 98.69%, false positive rate of 0.06%, and false negative rate of 1.44%. Experimental results demonstrate the outstanding performance of the proposed method.

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A new criterion for the alarm point using a combination of waveform amplitude and onset latency in Br(E)-MsEP monitoring in spine surgery

Journal of Neurosurgery Spine ◽

10.3171/2018.3.spine171348 ◽

2018 ◽

Vol 29 (4) ◽

pp. 435-441 ◽

Cited By ~ 2

Author(s):

Kazuyoshi Kobayashi ◽

Kei Ando ◽

Ryuichi Shinjo ◽

Kenyu Ito ◽

Mikito Tsushima ◽

...

Keyword(s):

Spine Surgery ◽

Predictive Value ◽

False Positive ◽

Roc Analysis ◽

False Positive Rate ◽

False Negative ◽

False Negative Rate ◽

High Rate ◽

Motor Deficit ◽

Onset Latency

OBJECTIVEMonitoring of brain evoked muscle-action potentials (Br[E]-MsEPs) is a sensitive method that provides accurate periodic assessment of neurological status. However, occasionally this method gives a relatively high rate of false-positives, and thus hinders surgery. The alarm point is often defined based on a particular decrease in amplitude of a Br(E)-MsEP waveform, but waveform latency has not been widely examined. The purpose of this study was to evaluate onset latency in Br(E)-MsEP monitoring in spinal surgery and to examine the efficacy of an alarm point using a combination of amplitude and latency.METHODSA single-center, retrospective study was performed in 83 patients who underwent spine surgery using intraoperative Br(E)-MsEP monitoring. A total of 1726 muscles in extremities were chosen for monitoring, and acceptable baseline Br(E)-MsEP responses were obtained from 1640 (95%). Onset latency was defined as the period from stimulation until the waveform was detected. Relationships of postoperative motor deficit with onset latency alone and in combination with a decrease in amplitude of ≥ 70% from baseline were examined.RESULTSNine of the 83 patients had postoperative motor deficits. The delay of onset latency compared to the control waveform differed significantly between patients with and without these deficits (1.09% ± 0.06% vs 1.31% ± 0.14%, p < 0.01). In ROC analysis, an intraoperative 15% delay in latency from baseline had a sensitivity of 78% and a specificity of 96% for prediction of postoperative motor deficit. In further ROC analysis, a combination of a decrease in amplitude of ≥ 70% and delay of onset latency of ≥ 10% from baseline had sensitivity of 100%, specificity of 93%, a false positive rate of 7%, a false negative rate of 0%, a positive predictive value of 64%, and a negative predictive value of 100% for this prediction.CONCLUSIONSIn spinal cord monitoring with intraoperative Br(E)-MsEP, an alarm point using a decrease in amplitude of ≥ 70% and delay in onset latency of ≥ 10% from baseline has high specificity that reduces false positive results.

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Letters to the Editor

PEDIATRICS ◽

10.1542/peds.68.1.144a ◽

1981 ◽

Vol 68 (1) ◽

pp. 144-145

Author(s):

Lachlan Ch De Crespigny ◽

Hugh P. Robinson

Keyword(s):

Real Time ◽

Linear Array ◽

False Positive Rate ◽

False Negative ◽

False Negative Rate ◽

Letters To The Editor ◽

Premature Babies ◽

Computed Tomography Scans ◽

Positive Rate ◽

Time Linear

We read with interest the report which suggested that the diagnosis of cerebroventricular hemorrhage ([CVH] including both subependymal [SEH] and intraventricular) with real time ultrasound was unreliable.1 Ultrasound, when compared with computed tomography scans, had a 35% false-positive rate and a 21% false-negative rate. In our institution over a 12-month period more than 200 premature babies have been examined (ADR real time linear array scanner with a 7-MHz transducer).

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