CRISPResso2 | deep sequencing data for rapid and intuitive interpretation | Genomics library

 by   pinellolab Python Version: v2.2.12 License: Non-SPDX

kandi X-RAY | CRISPResso2 Summary

kandi X-RAY | CRISPResso2 Summary

CRISPResso2 is a Python library typically used in Artificial Intelligence, Genomics applications. CRISPResso2 has no vulnerabilities, it has build file available and it has low support. However CRISPResso2 has 62 bugs and it has a Non-SPDX License. You can download it from GitHub.

CRISPResso2 is a software pipeline designed to enable rapid and intuitive interpretation of genome editing experiments. A limited web implementation is available at:
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            kandi-support Support

              CRISPResso2 has a low active ecosystem.
              It has 199 star(s) with 79 fork(s). There are 14 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 19 open issues and 174 have been closed. On average issues are closed in 223 days. There are 3 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of CRISPResso2 is v2.2.12

            kandi-Quality Quality

              CRISPResso2 has 62 bugs (0 blocker, 0 critical, 5 major, 57 minor) and 891 code smells.

            kandi-Security Security

              CRISPResso2 has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              CRISPResso2 code analysis shows 0 unresolved vulnerabilities.
              There are 14 security hotspots that need review.

            kandi-License License

              CRISPResso2 has a Non-SPDX License.
              Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

            kandi-Reuse Reuse

              CRISPResso2 releases are available to install and integrate.
              Build file is available. You can build the component from source.
              Installation instructions, examples and code snippets are available.
              CRISPResso2 saves you 4773 person hours of effort in developing the same functionality from scratch.
              It has 13161 lines of code, 218 functions and 33 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed CRISPResso2 and discovered the below as its top functions. This is intended to give you an instant insight into CRISPResso2 implemented functionality, and help decide if they suit your requirements.
            • Process a single fastq output
            • Get a new variant object based on reference sequence
            • This function returns the index of the peewand scaffold sequence
            • Generate a plot of the conversion map
            • Get a color lookup for a list of nucs
            • Add sgRNA to the plot
            • Plots the quantification window locations
            • Annotate heatmap plot
            • Plot the heatmap
            • Plots the alleles tables
            • Plot position dependent indels
            • This function returns the position of the pe - scaffold sequence
            • Extract amplicon information
            • Generate a matplotlib plot of modification frequency
            • Plot global modifications reference
            • Plots the similarity between two counts
            • Plot amplicon modifications
            • Plot the non - coding mutations
            • Process input BAM file
            • Make an aggregate report
            • Plot the frameshift analysis
            • Process a FASTA file
            • Filter fastq files
            • Guess the bases of the alignment
            • Make a summary report from a given folder
            • Plot alleles heatmap
            • Process a fastq output
            Get all kandi verified functions for this library.

            CRISPResso2 Key Features

            No Key Features are available at this moment for CRISPResso2.

            CRISPResso2 Examples and Code Snippets

            No Code Snippets are available at this moment for CRISPResso2.

            Community Discussions

            QUESTION

            Iterating Over Strings in Shell Commands Using Snakemake
            Asked 2019-Dec-18 at 19:27

            To give a little background, I'm trying to put together a pipeline to analyze deep sequencing results of in-silico predicted CRISPR off targets. I amplify a known sequence from the genome in 50 different places and each amplicon contains a predicted off target site where my original CRISPR guide could potentially bind. I input the two paired end NGS files into the program CRISPResso along with the amplicon sequence and off-target guide. The two paired end files, amplicon sequence, and gRNA are different for each of the 50 sites. I need to do this with multiple conditions, donors, and replicates so the numbers add up quick.

            I created the snakemake workflow below:

            ...

            ANSWER

            Answered 2019-Dec-15 at 13:51

            The config file you show should have a space after the hyphen, i.e.:

            Source https://stackoverflow.com/questions/59342187

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install CRISPResso2

            CRISPResso2 can be installed using the conda package manager Bioconda, or it can be run using the Docker containerization system.

            Support

            Please check that your input file(s) are in FASTQ format (compressed fastq.gz also accepted). If you get an empty report, please double check that your amplicon sequence is correct and in the correct orientation. It can be helpful to inspect the first few lines of your FASTQ file - the start of the amplicon sequence should match the start of your sequences. If not, check to see if the files are trimmed (see point below). It is important to determine whether your reads are trimmed or not. CRISPResso2 assumes that the reads ARE ALREADY TRIMMED! If reads are not already trimmed, select the adapters used for trimming under the ‘Trimming Adapter’ heading under the ‘Optional Parameters’. This is FUNDAMENTAL to CRISPResso analysis. Failure to trim adaptors may result in false positives. This will result in a report where you will observe an unrealistic 100% modified alleles and a sharp peak at the edges of the reference amplicon in figure 4. The quality filter assumes that your reads uses the Phred33 scale, and it should be adjusted for each user’s specific application. A reasonable value for this parameter is 30. If your amplicon sequence is longer than your sequenced read length, the R1 and R2 reads should overlap by at least 10bp. For example, if you sequence using 150bp reads, the maximum amplicon length should be 290 bp. Especially in repetitive regions, multiple alignments may have the best score. If you want to investigate alternate best-scoring alignments, you can view all alignments using this tool: http://rna.informatik.uni-freiburg.de/Teaching/index.jsp?toolName=Gotoh. As input, sequences from the 'Alleles_frequency_table.txt' can be used. Specifically, for a given row, the value in the 'Aligned_Sequence' should be entered into the 'Sequence a' box after removing any dashes, and the value in the 'Reference_Sequence' should be entered into the 'Sequence b' box after removing any dashes. The alternate alignments can be selected in the 'Results' panel in the Output section.
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            CLONE
          • HTTPS

            https://github.com/pinellolab/CRISPResso2.git

          • CLI

            gh repo clone pinellolab/CRISPResso2

          • sshUrl

            git@github.com:pinellolab/CRISPResso2.git

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