Consed: a graphical tool for sequence finishing

Sequencing of large clones or small genomes is generally done by the shotgun approach Although complete automation of data processing in shotgun sequencing is clearly desirable and may be feasible in the near future, at present finishing still requires extensive human intervention. This is customarily done by use of an interactive computer program. The program (which is usually called a sequence editor) must, at a minimum, display the aligned sequences of the assembled reads and allow the user to access underlying raw data (e.g., the fluorescence trace profiles from automated sequencers) and other information that may be useful in evaluating the base calls and assembly. It should also facilitate the detection of regions where additional data are needed, help in determining reagents (e.g., sequencing primers and templates) needed to obtain these data, and allow editing to correct errors. A good editor makes the finishing process as efficient and painless as possible. The display should indicate, with appropriate size and color emphases, the most important information about the assembly, with less important information being easily accessible with a minimum of effort, and the user should have the ability to change which information is shown, on the basis of the task at hand. Locations requiring human inspection should be efficiently pinpointed. The user manipulations required to accomplish a given task should be as natural and efficient as possible. The program should allow customization to suit individual preferences, facilitate quick detection and correction of user mistakes, and be easy to learn. It should have a quick response time and allow recovery from hardware and software problems on the users's computer. A number of editors are available commercially or from academic developers. The pioneering work in both assembly and editing was done by Staden, and his gap4 program We have developed an editor consed that is intended to be used in conjunction with several other sequence data processing programs developed by our group, including the base-calling program phre

<i>Consed:</i> A Graphical Tool for Sequence Finishing

Sequencing of large clones or small genomes is generally done by the shotgun approach (Anderson et al. 1982). This has two phases: (1) a shotgun phase in which a number of reads are generated from random subclones and assembled into contigs, followed by (2) a directed, or finishing phase in which the assembly is inspected for correctness and for various kinds of data anomalies (such as contaminant reads, unremoved vector sequence, and chimeric or deleted reads), additional data are collected to close gaps and resolve low quality regions, and editing is performed to correct assembly or base-calling errors. Finishing is currently a bottleneck in large-scale sequencing efforts, and throughput gains will depend both on reducing the need for human intervention and making it as efficient as possible. We have developed a finishing tool, consed, which attempts to implement these principles. A distinguishing feature relative to other programs is the use of error probabilities from our programs phred andphrap as an objective criterion to guide the entire finishing process. More information is available athttp://www.genome.washington.edu/consed/consed.html.</jats:p

Consed: a graphical tool for sequence finishing

Sequencing of large clones or small genomes is generally done by the shotgun approach Although complete automation of data processing in shotgun sequencing is clearly desirable and may be feasible in the near future, at present finishing still requires extensive human intervention. This is customarily done by use of an interactive computer program. The program (which is usually called a sequence editor) must, at a minimum, display the aligned sequences of the assembled reads and allow the user to access underlying raw data (e.g., the fluorescence trace profiles from automated sequencers) and other information that may be useful in evaluating the base calls and assembly. It should also facilitate the detection of regions where additional data are needed, help in determining reagents (e.g., sequencing primers and templates) needed to obtain these data, and allow editing to correct errors. A good editor makes the finishing process as efficient and painless as possible. The display should indicate, with appropriate size and color emphases, the most important information about the assembly, with less important information being easily accessible with a minimum of effort, and the user should have the ability to change which information is shown, on the basis of the task at hand. Locations requiring human inspection should be efficiently pinpointed. The user manipulations required to accomplish a given task should be as natural and efficient as possible. The program should allow customization to suit individual preferences, facilitate quick detection and correction of user mistakes, and be easy to learn. It should have a quick response time and allow recovery from hardware and software problems on the users&apos;s computer. A number of editors are available commercially or from academic developers. The pioneering work in both assembly and editing was done by Staden, and his gap4 program We have developed an editor consed that is intended to be used in conjunction with several other sequence data processing programs developed by our group, including the base-calling program phre

Estimation of prevalence of autoimmune diseases in the United States using electronic health record data

BACKGROUND Previous epidemiologic studies of autoimmune diseases in the US have included a limited number of diseases or used metaanalyses that rely on different data collection methods and analyses for each disease.METHODS To estimate the prevalence of autoimmune diseases in the US, we used electronic health record data from 6 large medical systems in the US. We developed a software program using common methodology to compute the estimated prevalence of autoimmune diseases alone and in aggregate that can be readily used by other investigators to replicate or modify the analysis over time.RESULTS Our findings indicate that over 15 million people, or 4.6% of the US population, have been diagnosed with at least 1 autoimmune disease from January 1, 2011, to June 1, 2022, and 34% of those are diagnosed with more than 1 autoimmune disease. As expected, females (63% of those with autoimmune disease) were almost twice as likely as males to be diagnosed with an autoimmune disease. We identified the top 20 autoimmune diseases based on prevalence and according to sex and age.CONCLUSION Here, we provide, for what we believe to be the first time, a large-scale prevalence estimate of autoimmune disease in the US by sex and age.FUNDING Autoimmune Registry Inc., the National Heart Lung and Blood Institute, the National Center for Advancing Translational Sciences, the Intramural Research Program of the National Institute of Environmental Health Sciences