GTGTGGTCTGCGAGTTCTAGCCTACTCGTTTCTCCCCTACTCACTCATTCACACACAAAAAĬTACAAGATTTGGCCCTCGCACGGGATGTGCGATAACCGCAAGATTGACTCAAGCGCGGAAAGCGCTGTAACC GTTTCTCCCCTACTCACTCATTCACACACAAAAACTGTGTTGTAACTACAAGATTTGGCCCTCGCACGGGĪTGTGCGATAACCGCAAGATTGACTCAAGCGCGGAAAGCGCTGTAACCACATGCTGTTAGTCCCTTTATGĬGGGGGGTAAACCGGCTGTGTTTGCTAGAGGCACAGAGGAGCAACATCCAACCTGCTTTTGTĬGGCTCCAATTCCTGCGTCGCCAAAGGTGTTAGCGCACCCAA So, Zika virus reads should not be counted by Rsubread while aligning.ĪAGGAAGGACTGGGCATGAGGGCCCAGTCCTTCCTTTCCCCTTCCGGGGGGTAAACCGGCTGTGTTTGCTĪGAGGCACAGAGGAGCAACATCCAACCTGCTTTTGTGGGGAACGGTGCGGCTCCAATTCCTGCGTCGCCAĪAGGTGTTAGCGCACCCAAACGGCGCATCTACCAATGCTATTGGTGTGGTCTGCGAGTTCTAGCCTACTC I will be aligning my reads to Senecavirus A genome. And I also pulled some sequences from the Zika virus which are names as Zika1 and Zika2. I created a fasta file with a few contigs each containing about 70-100 basepairs, and named each contig as read 1, read 2 and so on. fasta file by pulling some of the sequences from the Senecavirus A genome. source("")įor this simulation I created a small. Another important aspect of learning RNA-Seq analysis is understanding the algorithms behind the analysis.To this end, I decided to run a small simulation to understand how RNA-Seq analysis algorithms work.It is amazing how a single R package can do things like read aligning, read mapping and read counts in few lines of codes. Softwares with graphical user interface like CLC Workbench, have made RNA-Seq data analysis quite easier.However, they are expensive and in most of the cases you might not be able to tweak your analysis in the exact way you want. We can chat about your project and make recommendations to get you the help you need to proceed.RNA-Seq data analysis can be complicated. Not sure where to start? Just stop by NRB 933C. We have experience using Cell Profiler and Image analysis, as well as connections to many of the image analysis core facilities on campus. In addition, we can follow the R introductory course with advice tailored to your project, in consultations that can range from brief visits to yearlong support. We provide guidance on how to configure and use R, the main workhorse of immunogenomics, and how to develop project-specific analysis paths with RStudio. We have experience with clinical trial experimental design, differential expression analysis, as well as general statistics. General statistics advice and consulting services are available for help with experimental design or how to compare results from expression analysis. Seurat: We provide general consulting help on how to use Seurat We can help facilitate advice gathering from experts in the area.Ĭell Ranger: We have a Cell Ranger pipeline for department members This includes but is not limited to the Single Cell Genomics Core at BWH, as well as the Single Cell Core at HMS. In addition, we have connections to single cell cores in the Longwood Medical Area. We provide advice and training support for both Cell Ranger and Seurat. We have a robust workflow and tutorial along with experts to help you through this process. The second option involves using CLC Genomics workbench ( Link) this is software package is installed on several of the machines in the IT suite (NRB933). For this option there are several ready built pipelines available for researchers to use. There are two major solutions that we have available: The first option involves using to the schools' computing cluster (O2) this would involve using software such as the Tuxedo Suite ( Link). We provide a number of solutions for analyzing RNA-seq data, and we are here to help provide guidance throughout this process.
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