srividya22

#' Convert counts to transcripts per million (TPM).
#' 
#' Convert a numeric matrix of features (rows) and conditions (columns) with
#' raw feature counts to transcripts per million.
#' 
#'    Lior Pachter. Models for transcript quantification from RNA-Seq.
#'    arXiv:1104.3889v2 
#'    
#'    Wagner, et al. Measurement of mRNA abundance using RNA-seq data:
#'    RPKM measure is inconsistent among samples. Theory Biosci. 24 July 2012.

srividya22

# RPKM versus TPM
# 
# RPKM and TPM are both normalized for library size and gene length.
#
# RPKM is not comparable across different samples.
#
# For more details, see: http://blog.nextgenetics.net/?e=51

rpkm <- function(counts, lengths) {
  rate <- counts / lengths 

srividya22

#!/usr/bin/env perl

=head1 NAME

    rename_genes_in_maker_gff.pl       

=head1 SYNOPSIS
 
    rename_genes_in_maker_gff.pl input_gff output_gff outputdir species  
        where input_gff is the input gff file,

srividya22

#!/usr/bin/env perl

=head1 NAME

    rename_genes_in_maker_gff.pl       

=head1 SYNOPSIS
 
    rename_genes_in_maker_gff.pl input_gff output_gff outputdir species  
        where input_gff is the input gff file,

srividya22

Genome Annotation using MAKER

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.

Software & Data

Software prerequisites:

1. RepeatModeler and RepeatMasker with all dependencies (I used NCBI BLAST) and RepBase (version used was 20150807).
2. MAKER MPI version 2.31.8 (though any other version 2 releases should be okay).
3. [Augustus](http://bio

srividya22

Genome Annotation using MAKER

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.

Software & Data

Software prerequisites:

1. RepeatModeler and RepeatMasker with all dependencies (I used NCBI BLAST) and RepBase (version used was 20150807).
2. MAKER MPI version 2.31.8 (though any other version 2 releases should be okay).
3. [Augustus](http://bio

srividya22

# turn a find or cut (cut delimiter, get first column) output into a list
/etc find . -name "*bash*" | xargs
cut -d, -f1 file.csv | xargs

# find a file and grep for a word in the file
find . -name "*.java" | xargs grep "Stock"

# handeling filenames which have WHITESPACE
ls *txt | xargs  -d '\n' grep "cost"

srividya22

#!/usr/bin/env python
# Script to identify gaps regions in an assembly
# input : fasta 
# output : bed
# usage : get_gap_postions.py fasta bed
# Import necessary packages
import argparse
import re
from Bio import SeqIO

srividya22

Links: 
http://quinlanlab.org/tutorials/bedtools/bedtools.html

Use Case 1:  Given a.bam and b.regions.bed. how to get the parts of b.regions.bed that are not covered by a.bam?
Answer:
bedtools genomecov -ibam aln.bam -bga \
               | awk '$4==0' |
               | bedtools intersect -a regions -b - > foo
               
Option -bga	Report depth in BedGraph format, as above (i.e., -bg). However with this option, regions with zero coverage are also reported. This allows one to quickly extract all regions of a genome with 0 coverage by applying: “grep -w 0$” to the output.

srividya22

Testing Snakemake virtual memory usage

John Blischak 2014-05-14

Multiple users have observed that submitting jobs via Snakemake requires much more memory than is necessary to run the command (e.g. mailing list post, [Bitbucket issue][issue]).