SAM and BAM filtering one-liners
@author: David Fredman, [email protected] (sans poly-A tail)
@dependencies: http://sourceforge.net/projects/bamtools/ and http://samtools.sourceforge.net/
Please extend with additional/faster/better solutions via a pull request!
BWA mapping (using piping for minimal disk I/O)
| # This script was created to convert a directory full | |
| # of markdown files into rst equivalents. It uses | |
| # pandoc to do the conversion. | |
| # | |
| # 1. Install pandoc from http://johnmacfarlane.net/pandoc/ | |
| # 2. Copy this script into the directory containing the .md files | |
| # 3. Ensure that the script has execute permissions | |
| # 4. Run the script | |
| # | |
| # By default this will keep the original .md file |
| ## RNA-seq analysis with DESeq2 | |
| ## Stephen Turner, @genetics_blog | |
| # RNA-seq data from GSE52202 | |
| # http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=gse52202. All patients with | |
| # ALS, 4 with C9 expansion ("exp"), 4 controls without expansion ("ctl") | |
| # Import & pre-process ---------------------------------------------------- | |
| # Import data from featureCounts |
Justin Payne, May 30 2015
I get a lot of value out of putting bioinformatics tools in Docker containers, since once they're containerized with an automated build script (called a "Dockerfile") it's really easy to keep them up to date and manage their installations on different machines without their individual dependencies stepping all over each other. It's a really convenient way to try out new tools without taking the risk of borking your carefully-maintained "working" Linux install. Tools like boot2docker make Docker images runnable on non-Linux platforms, as well, resulting in improved portability of tools that might have platform (or even distro) specific dependencies. I've done this a couple of times, now, so I thought I'd share some tips and tricks.
| #!/bin/bash | |
| # | |
| # AUTHOR: Anand M. | |
| # RNA-Seq variant calling pieline accoring to GATK Best practices. | |
| # https://www.broadinstitute.org/gatk/guide/article?id=3891 | |
| # | |
| # Call with following arguments | |
| # bash rna_seq_variant_pipeline.sh <Input_Reads1.fq.gz> <Input_Reads2.fq.gz> <output_basename> | |
| # | |
| # Assumes STAR aligner is under path |
| # A simple cheat sheet of Spark Dataframe syntax | |
| # Current for Spark 1.6.1 | |
| # import statements | |
| from pyspark.sql import SQLContext | |
| from pyspark.sql.types import * | |
| from pyspark.sql.functions import * | |
| #creating dataframes | |
| df = sqlContext.createDataFrame([(1, 4), (2, 5), (3, 6)], ["A", "B"]) # from manual data |
| # Bootstrap tour step | |
| .bsTourStep <- function(i, id, title, content, pos = "right", tab = NULL){ | |
| id <- paste0("#", id) | |
| x <- paste0(" {\n element: \"", id, | |
| "\",\n title: \"", title, | |
| "\",\n content: \"", content, | |
| "\",\n placement: \"", pos, "\"") | |
| if(i==1 && !is.null(tab)){ | |
| x <- paste0(x, ",\n onShow: function (tour) { $(\"", tab, "\").tab('show');}\n }") | |
| } else { |
Please see the most up-to-date version of this protocol on my blog at https://darencard.net/blog/.
MAKER is a great tool for annotating a reference genome using empirical and ab initio gene predictions. GMOD, the umbrella organization that includes MAKER, has some nice tutorials online for running MAKER. However, these were quite simplified examples and it took a bit of effort to wrap my head completely around everything. Here I will describe a de novo genome annotation for Boa constrictor in detail, so that there is a record and that it is easy to use this as a guide to annotate any genome.
