[行业软件]CLC Genomics Workbench Premium 24.0.1 x64 [复制链接]

上一主题下一主题查看指定楼层

离线pony8000

UID: 125

IT资讯组

发帖: 53395

今日发帖

最后登录: 2024-11-06

只看楼主倒序阅读使用道具楼主发表于: 2019-10-15 11:38:07

自助获取论坛邀请码

新的CLC Genomics Workbench 24可以完成更多工作
具有改进的NGS读取处理能力和集成的生物医学工作台功能
CLC Genomics Workbench 24.0破解版是一个免费的生物医学基因组学分析插件，全面的参考数据管理器，取代了QIAGEN生物医学基因组学工作台，对我们的轨道系统和性能增强进行了许多改进，包括压缩数据。
CLC Genomics Workbench是一个功能强大的软件解决方案，是基因组学，建模，表观遗传学和元基因组学领域的一整套工具，可帮助科学家和专业人员利用尖端技术，独特功能和算法。慢慢应对分析遗传信息的挑战。这款用户友好的生物信息学软件可让您全面分析NGS数据。您还可以借助该软件找到共生微生物之间的关系，并轻松分析复杂的元基因组数据。
CLC Genomics Workbench软件完全支持NGS平台，例如Illumina，IonTorrent，PacBio和GeneReader，并提供用于基因水平各种分析的细胞RNA工作流程。该软件还可以让您在人类疾病研究中取得重要发现并执行最佳分析。

适合所有人的基因组学工作台
CLC Genomics Workbench是一个功能强大的解决方案，
适用于每个人，无论工作流程如何。
利用尖端技术，独特功能和
算法，工业界
和学术界的科学领导者广泛使用该技术来克服
与数据分析相关的挑战。

在一个程序中用于基因组学，转录组学，表观基因组学和宏基因组学的完整工具包

全面的NGS数据分析

用户友好的生物信息学软件解决方案可对NGS数据进行全面分析，包括整个基因组和从头组装转录组，有针对性的重测序分析，变异调用，ChIP-seq和DNA甲基化（亚硫酸氢盐测序分析）。

发现微生物群，其元基因组和宿主之间的关键相关性。通过用于分类学和功能性微生物组分析的工具和简化的分析工作流程，可以轻松了解复杂的宏基因组学数据。

受支持的NGS平台是Illumina，IonTorrent，PacBio和GeneReader。

RNA-seq和小RNA（miRNA，lncRNA）转录组学工作流程，用于在基因和转录本水平进行差异表达分析。

新增：生物医学基因组学分析1.0在CLC Genomics Workbench上安装此插件可提供以前通过运行Biomedical Genomics Workbench并安装现已淘汰的插件QIAseq Targeted Panel Analysis可获得的功能。获得对生物医学即用型工作流程，QIAseq分析工具和工作流程或GeneRead分析工具和工作流程的访问权限。

用于人类，小鼠和大鼠基因组的生物医学工作流程包括遗传性疾病工作流程（三重分析）和用于FFPE或液体活检的肿瘤学体细胞突变检测工作流程（单个样品或肿瘤正常匹配的样品），包括对SNP，MNV，InDels，Tandem的灵敏检测重复序列，结构变体，融合基因和CNV。包括带有保守性分数的注释和dbSNP，ClinVar上的过滤步骤。获取插件。

CLC Genomics Workbench软件的功能：

遗传数据分析
利用先进的技术和算法
NGS数据分析
专业且有吸引力的用户界面
在生物科学领域进行信息研究和分析

在人类疾病研究中发现导致突破性发现的信号现在，可通过CLC Genomics Workbench和免费插件Biomedical Genomics Analysis提供生物医学基因组学分析和面板数据分析功能。这些一起替代了Biomedical Genomics Workbench，以及插件QIAseq靶向面板分析和QIAGEN GeneRead Panel Analysis插件。即用型工作流程通过Biomedical Genomics Analysis插件访问即用型工作流程。现有生物医学基因组学工作台用户熟悉的即用型工作流程已得到改进和更新。现在，CLC Genomics Workbench 12版本中的所有用户均可使用它们。

领导自己的发现修改工作流和发现参数，以假设为导向的分析将指导您获得最有希望的突破。发现更多，更快简单性，灵活性和准确性相结合，可为您提供比开源替代方案快50％以上的解决方案，并具有得到全面支持的附加优势。
定制的工作流程可加速您的数据分析CLC基因组学工作台的开发旨在支持各种NGS生物信息学应用。工作流可以将质量控制步骤，适配器修整，读取映射，变体检测以及多个过滤和注释步骤组合在一起，形成一个管道，您可以与同事共享并单击即可执行。
系统要求
Windows：Windows 11，Windows 8，Windows 10，Windows Server 2012和Windows Server 2016
64位操作系统
需要
2 GB RAM建议使用4 GB RAM 需要
1024 x 768显示器需要
1600 x 1200显示器建议使用
Intel或AMD CPU

更新新功能介绍
CLC Genomics Workbench Premium 23.0.2
发布日期： 2023-02-13

改进和错误修复
氨基酸变化的运行时间得到了显着改善。
修复了“修剪读取”报告中的问题，即“修剪（断开的对）”的数量不是按作为输入提供的序列列表报告的，而是以增量方式加在一起。报告的“修剪读取”数量相应减少。当修剪来自多个序列列表的成对读取并生成损坏的读取对时，会出现此问题。
修复了一个罕见的问题，如果读取同时根据质量分数和适配器直读进行修整，则可能导致修剪读取保留读取的错误部分。
修复了导致解复用读取工具始终基于“条形码，序列”序列结构进行多重解复的问题。对标记列表的调整（例如添加链接器或将条形码放在末尾）将被忽略。在工作流上下文中运行时，此问题不会影响该工具。
修复了当数据集很大或检测到具有许多可能转录本的融合基因时，可能导致在 Windows 上检测和优化融合基因失败的问题。
修复了导出过滤的空注释轨道时可能导致 VCF 导出失败的问题。
修复了导致 Design Primers 表格中的片段长度不正确的问题。打开表格时会重新计算这些值，因此不需要重复以前的设计。
修复了导致 QIAseq xHYB 病毒面板参考数据集在 Windows 上下载失败的问题。
Fixed a rare issue where Rebuild Index could not repair a corrupt search index.
Various minor bug fixes

齐根CLC基因组学工作台 23.0.1
发布日期： 2023-01-17

改进和错误修复
Fixed an issue affecting Trim Reads, where the wrong part of a read was retained if the read was both trimmed to a fixed length and also trimmed by another method from the opposite end of the read.
Fixed an issue affecting Trim Reads when both adapter trimming using a trim adapter list and fixed length trimming were selected. This issue could cause the resulting trimmed reads to be shorter than expected.
Fixed an issue where fusion plots created by Detect and Refine Fusion Genes were omitted in the report and were not accessible via the fusion track table.
Fixed an issue where workflows containing a Branch on Coverage element would fail for read mappings with no zero coverage regions when using reports output by QC for Read Mapping.
Fixed an issue where dates indicated with forward slashes in CSV format files were not recognized as dates by Import Metadata.
Fixed an issue where the history entry in a sequence list after sorting always stated the sorting was based on length, even the sorting was based on name or marked status.
Fixed an issue causing Annotate with GFF/GTF/GVF file to fail when the option “Ignore duplicate annotation” was checked.
Fixed an issue causing Standard Import of GenBank format to stall if qualifier names spanned more than one line.
Various minor improvements
请参阅下面的 CLC 基因组学工作台 23.0 的发行说明，了解自此软件上一个常规版本以来更改的完整列表。

QIAGEN CLC 基因组学工作台 23.0
发布日期： 2023-01-17

新工具
Homology Based Cloning – Design cloning experiments for cloning methods relying on homologous ends, such as Gibson Assembly

.
Create K-medoids Clustering for RNA-Seq finds clusters of features, e.g., genes/transcripts/miRNAs etc, whose expressions behave similarly, for example first increasing over time and then decreasing. The tool produces a Clustering Collection which contains a Sankey plot showing how these features move between clusters under different conditions, for example different treatments. A line graph representation of features from individual clusters or pairs of clusters is present as well.
来自插件的新工具
Detect and Refine Fusion Genes – Find fusion genes in RNA-Seq data by identifying potential fusions and then refining that list by evaluation of the evidence for each fusion. This is an updated version of the tool formerly distributed in the Biomedical Genomics Analysis plugin. The updates made are listed in an Improvements section below.
Target Region Coverage Analysis – Analyze and compare coverage from multiple samples. This tool was formerly distributed in the Biomedical Genomics Analysis plugin.
Create Consensus Sequences from Variants – Create consensus sequences from a variant track and a reference sequence. This tool was formerly distributed in the Biomedical Genomics Analysis plugin.
Annotate with GFF/GVF/GTF file – Add annotations from a GFF, GVF or GTF format file onto sequences, individual or in sequence lists. This tool was formerly distributed in the Annotate with GFF file plugin.
其他新功能和改进
RNA-Seq 分析工具
New tutorial: Get hands-on experience with new RNA-Seq analysis functionality, including Create K-medoids Clustering for RNA-Seq (see New Tools above), with the RNA-Seq analysis with four tissues and six timepoints tutorial.
Improvements to RNA-Seq Analysis:
Substantial speed improvements. Reads that map to multiple transcripts or genes will be distributed differently than earlier due to different choices of random seed in the new implementation. The algorithm is still deterministic.
Transcripts are no longer renamed in Transcript Expression (TE) output unless renaming is necessary to avoid duplicate names. Previously, transcripts were renamed to the gene name plus a number e.g. “BRCA_1”. This change means that TE tracks in this version of the software cannot typically be used together with TE tracks generated using older versions to produce Heat Maps, PCA plots, Expression, etc.
Reports UMI fragment counts when relevant. UMI counts are included in the Fragment statistics section of the report if the input reads are annotated with UMIs by tools from the Biomedical Genomics Analysis plugin, and if the library type is set to 3′ sequencing for RNA-Seq Analysis.
Improvements to Heat Maps:
Samples can be ordered by the Tree, Sample, or Active metadata layer options, or any individual metadata entry.
Optimize tree layouts – a new option for reordering features to produce a top-left to bottom-right diagonal.
The order of the metadata categories can be adjusted. This order is reflected in the legend.
Metadata categories are alphabetically sorted.
The Expression Browser includes a new plot for visualizing genes across samples and contrasts and metadata categories are sorted alphabetically.
Venn diagrams support four and five groups. Previously up to 3 were supported. Tooltips indicate which groups are part of a specific intersection.
PCA plots produced by PCA for RNA-Seq:
Have two table views. The first table view shows the loadings of the principal components. The second table view shows the coordinates of the points.
The order of the metadata categories in 2D PCA plots can be adjusted. This order is reflected in the legend.
miRNA 分析工具
Quantify miRNA:
Handles custom databases containing duplicated names.
Does not allow custom databases containing sequences longer than 60bp. This avoids misallocation of reads to sequences that are similar to small RNAs.
When adding multiple inputs to Extract IsomiR Counts, the extracted expression tables contain an entry for the combined set of IsomiRs identified among the samples, making them compatible for analysis in Differential Expression in Two Groups and Differential Expression for RNA-Seq.
两组RNA-seq的差异表达和差异表达
A new option for creating a subset has been added to the miRNA Statistical Comparison Table produced by Differential Expression for RNA-Seq and Differential Expression in Two Groups.
It is possible to downweigh outliers. This option is disabled by default and recommended only when the results seem enriched for genes that are expressed at anomalously high levels in a small proportion of samples.
The Max Group Means column of Statistical Comparison Tracks and Tables now shows TPM instead of RPKM. Note that this column is used for filtering data in tools such as Create Heat Map for RNA-Seq and the Pathway Analysis tool of the Ingenuity Pathway Analysis plugin.
检测和完善融合基因
这是检测和优化融合基因的更新版本，以前分布在生物医学基因组学分析插件中。此处列出的更新与生物医学基因组学分析 22.2 一起分发的版本相关。

Fusions will not be called for overlapping genes.
Novel exon boundary improvements:
Options have been expanded to allow for detecting fusions with a single fusion partner (“Detect with novel exon boundaries”) as well as detecting those with 2 fusion partners (“Allow fusions with novel exon boundaries in both genes”)
The “Detect exon skippings” option supports detection of fusions with novel exon boundaries.
An option has been added to omit non-significant breakpoints from the report.
A minimum Z-score can now be specified for use when evaluating evidence for a fusion.
Speed improvements
The option “Allow fusions with novel exon boundaries in both genes” now defaults to false to reduce the number of false positive fusions. Setting it to true is useful for exhaustive searches of novel fusions.
Changes to the maximum number of equivalent matches to the reference allowed for a single read to be retained:
When remapping reads to a fusion chromosome, the maximum number is now 30. Previously it was 10.
When searching for unaligned ends, the maximum number remains unchanged, as 10.
The option “Maximum number of hits for a read” has been removed. It’s value was ignored in previous versions.
Fusions from mRNA transcripts without an associated gene in the Gene track are not used when detecting fusions. mRNA transcript features must have a gene id in one of the following columns to be matched with the associated gene: “Parent”, “gene_id” or “gene_name”.
Fixed an issue where paired end reads were treated as single end reads when the option to “Only use fusion primer reads” was enabled.
Fixed an issue where unaligned ends could be too long or too short for reads containing insertions and deletions. This change may lead to small differences in results compared to earlier versions, expected to be due to a decrease in false positive and false negatives reported.
亚硫酸氢盐作图
Map Reads to Bisulfite Reference speed improvement. This is data dependent, with about a 50% improvement likely for most data sets. This speed up might change the details of results very slightly.
Call Methylation Level speed improvement. This speedup might, in some cases, change results very slightly.
Import of read mappings from SAM/BAM now use methylation information from the optional SAM tags XR for read conversion and XG for reference conversion. The recognized values are “CT” and “GA”. Support for these tags is added so that information is not lost if a bisulfite mapping is exported and then re-imported.
Export of read mappings to SAM/BAM format now includes details on bisulfite conversion. These are specified using the SAM tags XR for read conversion and XG for reference conversion. The possible values of these tags are “CT” and “GA”. This is provided for increased compatibility with third party tools.
工作流程
Branch on Coverage – a new workflow control flow element where the downstream processing of read mappings can be controlled based on coverage values within reports.
Import with Metadata – new template workflow that imports sequence data into sequence lists and associates the imported elements to a CLC Metadata Table containing descriptive information for each sample.
Workflows containing Demultiplex Reads elements and workflows containing Split Sequence List elements can be run in Batch mode.
Barcodes can be preconfigured in Demultiplex Reads elements in workflows.
Workflow Export elements can be preconfigured to export to locations on AWS S3.
When Annotate with Overlap Information is included more than once in the same workflow, columns with overlap information are now always added in the same order. Previously, concurrency issues could cause column order to be different between different runs.
在 SRA 中搜索读取
Technical reads can be downloaded in addition to biological reads. The reads to import, as well as the read structure and orientation are configurable.
When multiple accessions are provided in an Accession query field, each is searched for separately. Previously only entries containing all the accessions entered were returned.
An estimate of the disk space and final size of imported sequence lists is no longer provided in the wizard, but further information about space requirements has been added to the manual.
A troubleshooting section has been added to the manual.
读取映射
Read mapping speed on Apple Silicon processors has been improved. Read mapping results are not affected by this. Tools benefiting from this change include Map Reads to Reference, RNA-Seq Analysis, Map Reads to Contigs and Map Bisulfite Reads to Reference.
In stand-alone read mappings and read mapping tracks, deletions are now highlighted in the coverage graph and in the shown reads.
For stand alone read mappings a “Match coloring” side panel provides the colors applied to reads when the compactness level is set to “Packed”.
导入和导出
VCF Import:
Supports symbolic alleles for inversions (<INV>), insertions (<INS>), deletions (<DEL>) and tandem duplications (<TANDEM:DUP>). Symbolic alleles that do not contain sequence information or are longer than 100,000 base pairs are imported to annotation tracks instead of variant tracks. Previously symbolic alleles were not imported.
Improved handling of variants with multiple loci encoded in the same vcf record.
VCF Export supports symbolic allele representation for insertions (<INS>), deletions (<DEL>) and tandem duplications (<TANDEM:DUP>). (Inversions (<INV>) were already supported.) With the exception of deletions, variants in annotation tracks are always exported as symbolic alleles. Deletions in annotation tracks and variants in variant tracks above a specified size are also exported as symbolic alleles. The default size is 1000 bp, which corresponds with the QCI Interpret requirement that InDels > 1000 bp must be represented as symbolic alleles.
The PacBio importer supports HiFi reads.
The read length when exporting to FASTQ format files has been increased from 524,288 bp to 16,777,216 bp.
SAM/BAM Mapping Files importer:
Performance improvements
The circular flag of references is now retained.
Import Tracks from File has been updated to show a warning if the file is not imported.
GFF3 Export retains the case of attribute headers. Previously, all headers were adjusted to lower case during export.
The history information of elements imported using Standard Import includes the specific importer used (e.g. “CSV table importer”, “Fasta Importer”, etc).
Standard Import can be used to import files from AWS S3 locations.
When exporting images to bitmap-based formats, the Screen resolution and High resolution options are now bounded so the maximum supported number of pixels will not be exceeded.
序列列表
Checkboxes can be enabled to select sequences within the graphical view of sequence lists. Lists can be sorted based on whether they are marked or not, and marked sequences can be deleted.
In the Annotation Table view, the following changes have been made to the right-click menu:
The underlying sequence of selected annotations can be deleted.
Names of sequences selected annotations are on can be copied to the clipboard.
The option to export to gff now exports to GFF3 format – Export Selected to GFF3 File. This option has also been updated in the Annotation Table view of individual sequence elements.
In the Table view, selected sequences can be deleted, and the names of selected sequences can be copied.
Various minor improvement to labels in right-click menus.
CLC 元数据表
When launching analyses in Batch mode, or when launching workflows with an Iterate element, CLC Metadata Tables with data associated can be used directly as input. Each row in the CLC Metadata Table is a batch unit, with data elements associated to a row, of a type compatible as input to the analysis, being the default contents of a batch unit. When launching workflows, the column to base the batch units on can be specified.
New options for editing CLC Metadata Tables, including for adding content from other CLC Metadata Tables or Excel, CSV or TSV files. Rows in a CLC Metadata Table can also be selected and used to make a new CLC Metadata Table.
When associating data automatically to CLC Metadata Tables, a preview of the associations that will be made is shown in the wizard.
其他改进
Search for Sequences at UniProt has been substantially updated and improved. Changes include new search fields and more informative information returned, including links to PubMed entries.
Quick Search and Local Search have been substantially improved. Please refer to the documentation for details.
The overview of batch units when launching tools or workflows in Batch mode and when launching workflows with control flow elements (Iterate, Collect and Distribute), have been aligned. In the latter, the contents of batch units can now be adjusted by including or excluding elements based on a part of their name. Previously this was only possible when launching analyses in Batch mode. Right-click options to remove batch units or to remove particular data elements from a batch unit, have been removed.
When Low Frequency Variant Detection, Fixed Ploidy Variant Detection or Basic Variant Detection was used with a mapping realigned using Local Realignment with a guidance variant track, it was possible for partial insertions to be called. Now, the full insertion must be present within at least one, individual read for it to be reported.
QC for Targeted Sequencing:
Can report coverage statistics per gene.
Supports analysis of read mappings generated by RNA-Seq Analysis.
The hg38 masking track GenomeReferenceConsortium_masking_hg38_no_alt_analysis_set is provided via the Reference Data Manager as a reference element, and is part of reference sets that use the “hg38_no_alt_analysis_set” genome sequence. It contains regions defined by the Genome Reference Consortium and primarily serves to remove false duplications, including one affecting the gene U2AF1. It is intended for use with Map Reads to Reference.
Annotate with Exon Numbers:
Can add exon numbers to elements in annotation, expression and statistical comparison tracks. Previously only variant tracks could be annotated with exon numbers.
Adds exon numbers when input elements start outside an exon but still overlap the exon.
Adds all exons when multiple exons overlaps a single input element.
Allows annotation with exons from only one transcript or CDS.
Filter on Custom Criteria can be used to filter Statistical Comparison Tracks, Statistical Comparison Tables, IsomiR tables, and miRNA Seed Tables.
Demultiplex Reads has been updated to:
Report barcodes without any matched reads
Show the barcodes names in the history.
Reports from Create Sample Reports and Combined Report generated using RNA-Seq reports now include the percentage of reads mapped to exons in the Fragment counting statistics table.
In Create Sample Report, the percentage of target region positions with coverage above a set threshold can be used as a QC metric.
QC for Sequencing Reads processes only the first 100,000 base pairs in long reads. Before the tool would fail when provided with very long reads.
Local Realignment no longer realigns reads into regions with no coverage, such as introns in RNA-Seq read mappings.
Remove Duplicate Mapped Reads uses an improved method to identify duplicate reads when handling paired end reads. In general, this improvement results in slightly more reads being considered duplicates.
The options for extracting reads according to their location relative to features in an overlap track have been expanded in Extract Reads. Previously reads had to lie fully within an annotated region to be extracted. Now, in addition to that condition, options are provided for extracting any overlapping reads, extracting only reads that fully span annotated regions or extracting all reads except those that overlap with annotations in the overlap track.
Assemble Sequences to Reference supports alignment of reads that span the origin of a circular reference.
Secondary Peak Calling has a new option “Peak detection stringency”.
The report from Copy Number Variant Detection (CNVs):
Includes a table showing the number of genes affected by CNV calls.
Contains new coverage plots at genome and chromosome levels.
The Trim Reads report now includes statistics for the number of reads in intact pairs and in broken pairs.
Updated restriction site database to REBASE 2022-06-30.
The Identify Known Mutations from Mappings output channel names when used in a workflow have been improved. The elements produced by the tool have not been changed.
While viewing data, in most situations, tooltips can be suppressed by holding down the Ctrl key. Similarly those tooltips can be displayed immediately, instead of a moment after the mouse cursor stops moving, by holding down the Shift key.
The Welcome Center content has been updated to focus on information helpful when getting started using the Workbench.
Third party plugins for CLC Workbenches can be installed when the Workbench is running in Viewing Mode.
A button has been added to the top Toolbar for contacting our Support team.
Various minor improvements

联系qq1400155802