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    <title>NGS on Chatomics</title>
    <link>https://divingintogeneticsandgenomics.com/tags/ngs/</link>
    <description>Recent content in NGS on Chatomics</description>
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    <language>en-us</language>
    <copyright>&amp;copy; 2018 Ming &#39;Tommy&#39; Tang</copyright>
    <lastBuildDate>Sun, 31 Dec 2017 19:58:00 -0800</lastBuildDate>
    
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    <item>
      <title>The End of 2017</title>
      <link>https://divingintogeneticsandgenomics.com/archive/the-end-of-2017/</link>
      <pubDate>Sun, 31 Dec 2017 19:58:00 -0800</pubDate>
      
      <guid>https://divingintogeneticsandgenomics.com/archive/the-end-of-2017/</guid>
      <description>In the end of last year, I wrote a post summarizing the passing 2016. Now, it is time to write the same for 2017! How time flies!
Last year, I wrote:
For the coming 2017, I should be:
1. busy with Phoebe.
2. writing 1-2 papers.
3. writing a book chapter on ChIP-seq for the biostar handbook. It should come out in the mid of 2017.
3. writing a small R package for practice.</description>
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    <item>
      <title>linux commands basics</title>
      <link>https://divingintogeneticsandgenomics.com/archive/linux-commands-basics/</link>
      <pubDate>Wed, 06 Aug 2014 18:18:00 -0700</pubDate>
      
      <guid>https://divingintogeneticsandgenomics.com/archive/linux-commands-basics/</guid>
      <description>I am attending the NGS course at MSU. This is a great course with great instructors and friendly colleagues.
I highly recommend this course to everyone. http://bioinformatics.msu.edu/ngs-summer-course-2014
This morning, we learned SNP calling by samtools and sam file specification (I will write another blog for the SNP calling) .in the night , TA Elijah gave an awesome introduction to linux commands.
personally, I think this should be taught in the first day of the course.</description>
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    <item>
      <title>Several NGS bioinformatics training materials</title>
      <link>https://divingintogeneticsandgenomics.com/archive/several-ngs-bioinformatics-training-materials/</link>
      <pubDate>Wed, 12 Mar 2014 08:21:00 -0700</pubDate>
      
      <guid>https://divingintogeneticsandgenomics.com/archive/several-ngs-bioinformatics-training-materials/</guid>
      <description>1. Next Generation sequencing wiki book http://en.wikibooks.org/wiki/Next_Generation_Sequencing_(NGS)
 UCDavis training course https://training.bioinformatics.ucdavis.edu/documentation/
 MSU training course by Titus Brown http://ged.msu.edu/angus/index.html
 GOBLET http://www.mygoblet.org/training-portal
  more http://ged.msu.edu/angus/bioinformatics-courses.html
 a list maintained by Stephen Turner in UVA http://stephenturner.us/edu.html
 GVL practial protocols for ChIP-seq, RNA-seq, variant calling etc https://genome.edu.au/wiki/GVL
  These will keep me busy for a while...I feel I do not have enough time to learn :)</description>
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    <item>
      <title>ChIP-seq analysis programs</title>
      <link>https://divingintogeneticsandgenomics.com/archive/chip-seq-analysis-programs/</link>
      <pubDate>Mon, 20 Jan 2014 12:49:00 -0800</pubDate>
      
      <guid>https://divingintogeneticsandgenomics.com/archive/chip-seq-analysis-programs/</guid>
      <description>This is the first blog in the year of 2014. I am graduating in the coming August, there are so many things to do and I do not have much time to blog. However, I do not want it to be inactive.
I have extensive experience with ChIP-seq data analysis, and I want to list all the programs that I usually use.
With raw Fastq data, one needs to align it to the reference genome by an aligner.</description>
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    <item>
      <title>ChIP-exo data analysis</title>
      <link>https://divingintogeneticsandgenomics.com/archive/chip-exo-data-analysis/</link>
      <pubDate>Sat, 16 Nov 2013 07:58:00 -0800</pubDate>
      
      <guid>https://divingintogeneticsandgenomics.com/archive/chip-exo-data-analysis/</guid>
      <description>Our neighboring lab just generated some ChIP-exo data, (if you do not know the technique, look at this paper http://www.ncbi.nlm.nih.gov/pubmed/23026909) and the company did some analysis but not what they want. The bedgraph files generated by the company were separated for plus strand and minus strand. They want just peak files like in the ChIP-seq experiment.
I was aware of several software can be used to deal with this type of data:</description>
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    <item>
      <title>Two pipelines for NGS analysis</title>
      <link>https://divingintogeneticsandgenomics.com/archive/two-pipelines-for-ngs-analysis/</link>
      <pubDate>Mon, 12 Aug 2013 06:11:00 -0700</pubDate>
      
      <guid>https://divingintogeneticsandgenomics.com/archive/two-pipelines-for-ngs-analysis/</guid>
      <description>bcbio-nextgen from Brad Chapman https://github.com/chapmanb/bcbio-nextgen
Documentation https://bcbio-nextgen.readthedocs.org/en/latest/index.html
Metaseq from Ryan Dale https://github.com/daler/metaseq
Documentation http://pythonhosted.org/metaseq/</description>
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    <item>
      <title>DESeq2 is now in Bioconductor</title>
      <link>https://divingintogeneticsandgenomics.com/archive/deseq2-is-now-in-bioconductor/</link>
      <pubDate>Thu, 25 Jul 2013 13:26:00 -0700</pubDate>
      
      <guid>https://divingintogeneticsandgenomics.com/archive/deseq2-is-now-in-bioconductor/</guid>
      <description>http://seqanswers.com/forums/showthread.php?t=28350
http://bioconductor.org/packages/2.12/bioc/html/DESeq2.html
Thank you Simon and your team!</description>
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    <item>
      <title>install bioawk in unbuntu</title>
      <link>https://divingintogeneticsandgenomics.com/archive/install-bioawk-in-unbuntu/</link>
      <pubDate>Sat, 20 Jul 2013 20:21:00 -0700</pubDate>
      
      <guid>https://divingintogeneticsandgenomics.com/archive/install-bioawk-in-unbuntu/</guid>
      <description>Bioawk is written by Heng Li, and it can handle formats like:
bed: 1:chrom 2:start 3:end 4:name 5:score 6:strand 7:thickstart 8:thickend 9:rgb 10:blockcount 11:blocksizes 12:blockstarts sam: 1:qname 2:flag 3:rname 4:pos 5:mapq 6:cigar 7:rnext 8:pnext 9:tlen 10:seq 11:qual vcf: 1:chrom 2:pos 3:id 4:ref 5:alt 6:qual 7:filter 8:info gff: 1:seqname 2:source 3:feature 4:start 5:end 6:score 7:filter 8:strand 9:group 10:attribute fastx: 1:name 2:seq 3:qual 4:comment   I followed the tutorial here https://github.com/vsbuffalo/bioawk-tutorial</description>
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    <item>
      <title>a python script for extracting fastq sequences</title>
      <link>https://divingintogeneticsandgenomics.com/archive/a-python-script-for-extracting-fastq-sequences/</link>
      <pubDate>Thu, 04 Jul 2013 09:05:00 -0700</pubDate>
      
      <guid>https://divingintogeneticsandgenomics.com/archive/a-python-script-for-extracting-fastq-sequences/</guid>
      <description>a simple python script to handle fastq file.
fast fastq file parser, extract ~10,000 reads with their sequences and quality
from a fastq file (~70milion reads) based on names of the reads. HengLi in Princeton https://github.com/lh3/seqtk
has a wrapper for this kind of task.
the following code is from http://www.biostars.org/p/10353/
this script demonstrates the usage of set(hash-able), a data structure that is much faster than list
when you have two files, put the information from one file into a container, loop over the other file.</description>
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    <item>
      <title>The NGS WikiBook: a dynamic collaborative online training effort with long-term sustainability</title>
      <link>https://divingintogeneticsandgenomics.com/archive/the-ngs-wikibook-a-dynamic-collaborative-online-training-effort-with-long-term/</link>
      <pubDate>Mon, 01 Jul 2013 18:22:00 -0700</pubDate>
      
      <guid>https://divingintogeneticsandgenomics.com/archive/the-ngs-wikibook-a-dynamic-collaborative-online-training-effort-with-long-term/</guid>
      <description> The NGS wiki book http://en.wikibooks.org/wiki/Next_Generation_Sequencing_(NGS)
http://intl-bib.oxfordjournals.org/content/early/2013/06/21/bib.bbt045.full
for more details, refer to the link above.
Nine simple rules to begin with NGS analysis
RULE 1: DO NOT FEAR THE COMMAND LINE RULE 2: KNOW THE CONVENTIONS RULE 3: READ INTRODUCTORY REVIEWS RULE 4: START WITH QUALITY CHECKING RULE 5: PLAN FOR MISTAKES AND DOCUMENT WORKFLOW RULE 6: ALWAYS GET INFORMED AND GET HELP IF STUCK RULE 7: USE AN EFFICIENT INTEGRATIVE APPROACH RULE 8: AVOID REINVENTING THE WHEEL ( I mentioned this several times in my blog :) ) RULE 9: EDUCATION IS IMPORTANT </description>
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    <item>
      <title>VCF file annotation and manipulation tools</title>
      <link>https://divingintogeneticsandgenomics.com/archive/vcf-file-annotation-and-manipulation-tools/</link>
      <pubDate>Sat, 29 Jun 2013 05:14:00 -0700</pubDate>
      
      <guid>https://divingintogeneticsandgenomics.com/archive/vcf-file-annotation-and-manipulation-tools/</guid>
      <description>VCF (variant calling format) file, as specified in 1000 Genome http://www.1000genomes.org/wiki/Analysis/Variant%20Call%20Format/vcf-variant-call-format-version-41
is a common file to handle the variant information from the NGS sequencing data.
many tools have been developed to manipulate, extract information with this format.
some popular ones are:
tabix http://samtools.sourceforge.net/tabix.shtml for fast indexing and extracting certain regions of the whole genome.
VCFtools http://vcftools.sourceforge.net/ for many more manipulations including annotating, merging, concatenating, comparing etc.
bedtools http://code.google.com/p/bedtools/ for genomic region overlapping calculation.</description>
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    <item>
      <title>count how many mapped reads in a bam file</title>
      <link>https://divingintogeneticsandgenomics.com/archive/count-how-many-mapped-reads-in-a-bam-file/</link>
      <pubDate>Tue, 18 Jun 2013 19:09:00 -0700</pubDate>
      
      <guid>https://divingintogeneticsandgenomics.com/archive/count-how-many-mapped-reads-in-a-bam-file/</guid>
      <description>I wanted to count how many mapped reads are in a ChIP-seq bam file downloaded from UCSC ECODE project. http://genome.ucsc.edu/ENCODE/downloads.html
A quick google search:
http://left.subtree.org/
and http://seqanswers.com/forums/showthread.php?t=891
The output from short read aligners like Bowtie and BWA is commonly stored in SAM/BAM format. When presented with one of these files a common first task is to calculate the total number of alignments (reads) captured in the file. In this post I show some examples for finding the total number of reads using samtools and directly from Java code.</description>
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    <item>
      <title>FASTA/Q file manipulation tool readfq</title>
      <link>https://divingintogeneticsandgenomics.com/archive/fasta-q-file-manipulation-tool-readfq/</link>
      <pubDate>Tue, 11 Jun 2013 08:24:00 -0700</pubDate>
      
      <guid>https://divingintogeneticsandgenomics.com/archive/fasta-q-file-manipulation-tool-readfq/</guid>
      <description>it is developed by Heng Li in princeton.
https://github.com/lh3/readfq
it is super fast and I will have a try.
Readfq is a collection of routines for parsing the FASTA/FASTQ format. It seamlessly parses both FASTA and multi-line FASTQ with a simple interface. Readfq is first implemented in a single C header file and then ported to Lua, Perl and Python as a single function less than 50 lines. For users of scripting languages, I encourage to copy-and-paste the function instead of using readfq as a library.</description>
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    <item>
      <title>remap the Eland sorted.txt file from hg18 to hg19</title>
      <link>https://divingintogeneticsandgenomics.com/archive/remap-the-eland-sorted-txt-file-from-hg18-to-hg19/</link>
      <pubDate>Fri, 07 Jun 2013 13:51:00 -0700</pubDate>
      
      <guid>https://divingintogeneticsandgenomics.com/archive/remap-the-eland-sorted-txt-file-from-hg18-to-hg19/</guid>
      <description>Sometime ago, I wrote a blog about how to convert Eland sorted.txt file to bam file
convert Eland sorted.txt to bam file
the original Eland file was mapped to hg18, but I want to remap it to hg19.
essentially, I need a fastq file to map it by bowtie.
A quick google search:
http://seqanswers.com/forums/showthread.php?t=7061
so, the bamtools https://github.com/pezmaster31/bamtools (yes, github again...that&#39;s why I want to learn git a little bit, see my last post My first try on Git)</description>
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    <item>
      <title>count ChIP-seq, RNA-seq counts at features</title>
      <link>https://divingintogeneticsandgenomics.com/archive/count-chip-seq-rna-seq-counts-at-features/</link>
      <pubDate>Sat, 01 Jun 2013 17:16:00 -0700</pubDate>
      
      <guid>https://divingintogeneticsandgenomics.com/archive/count-chip-seq-rna-seq-counts-at-features/</guid>
      <description>several tools are:
subread
http://subread.sourceforge.net/
http://bioinf.wehi.edu.au/featureCounts/
Bedtools genomecov
http://bedtools.readthedocs.org/en/latest/content/tools/genomecov.html
HTseq:
http://www-huber.embl.de/users/anders/HTSeq/doc/count.html
Homer:
http://biowhat.ucsd.edu/homer/ngs/quantification.html</description>
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    <item>
      <title>A very good introduction of NGS analysis in the HOMER page</title>
      <link>https://divingintogeneticsandgenomics.com/archive/a-very-good-introduction-of-ngs-analysis-in-the-homer-page/</link>
      <pubDate>Sat, 01 Jun 2013 16:48:00 -0700</pubDate>
      
      <guid>https://divingintogeneticsandgenomics.com/archive/a-very-good-introduction-of-ngs-analysis-in-the-homer-page/</guid>
      <description>See the link here:
http://biowhat.ucsd.edu/homer/basicTutorial/index.html
Setting up your computing environment Next-generation sequencing analysis is a compute intensive process. Your average laptop is probably not up to the challenge. Most software is geared toward UNIX style operating systems, with large servers in mind. Typically, analysis algorithms will be distributed by researchers in one of three ways:
 Stand alone program to run in a UNIX environment (most common) Webserver where you upload data to be analyzed (i.</description>
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      <title>Framework for evaluating variant detection methods: comparison of aligners and callers</title>
      <link>https://divingintogeneticsandgenomics.com/archive/framework-for-evaluating-variant-detection-methods-comparison-of-aligners-and/</link>
      <pubDate>Mon, 13 May 2013 20:11:00 -0700</pubDate>
      
      <guid>https://divingintogeneticsandgenomics.com/archive/framework-for-evaluating-variant-detection-methods-comparison-of-aligners-and/</guid>
      <description>http://bcbio.wordpress.com/
Blue Collar Bioinformatics Framework for evaluating variant detection methods: comparison of aligners and callers with 5 comments
Variant detection and grading overview Developing pipelines for detecting variants from high throughput sequencing data is challenging due to rapidly changing algorithms and relatively low concordance between methods. This post will discuss automated methods providing evaluation of variant calls, enabling detailed diagnosis of discordant differences between multiple calling approaches. This allows us to:</description>
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    <item>
      <title>0-based and 1-based coordinates</title>
      <link>https://divingintogeneticsandgenomics.com/archive/0-based-and-1-based-coordinates/</link>
      <pubDate>Wed, 08 May 2013 19:14:00 -0700</pubDate>
      
      <guid>https://divingintogeneticsandgenomics.com/archive/0-based-and-1-based-coordinates/</guid>
      <description>see the blog here: http://allaboutbioinfo.blogspot.com/search?updated-max=2011-08-18T16:56:00-07:00&amp;amp;max-results=7
###
There are two different coordinate base systems in different files: 0-base and 1-base. Different files use different base systems, and sometimes it causes confusions (especially when one tries to calculate the length of the region). Here I show the differences in two systems, and summarize several file formats that use both sytems.Bases in sequence positions 0-base system: the first base is 0. You represent a region as [a, b).</description>
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    <item>
      <title>batch converting coordinates to sequences</title>
      <link>https://divingintogeneticsandgenomics.com/archive/batch-converting-coordinates-to-sequences/</link>
      <pubDate>Tue, 30 Apr 2013 19:20:00 -0700</pubDate>
      
      <guid>https://divingintogeneticsandgenomics.com/archive/batch-converting-coordinates-to-sequences/</guid>
      <description>If you have a file which contains the coordinates of the chromosomes ( let&#39;s say you have a bed https://genome.ucsc.edu/FAQ/FAQformat.html#format1 file from a
ChIP-seq peak call) , how can you get the sequences of corresponding coordinates? ( you may need the sequences for motif analysis by MEME http://meme.nbcr.net/meme/intro.html )
  a simple way is using the table browser in UCSC genome browser           Extracting sequence in batch from an assembly                &amp;#10;  Question:</description>
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      <title>Cool use of Unix paste with NGS sequences:FASTQ to FASTA</title>
      <link>https://divingintogeneticsandgenomics.com/archive/cool-use-of-unix-paste-with-ngs-sequences-fastq-to-fasta/</link>
      <pubDate>Thu, 04 Apr 2013 19:29:00 -0700</pubDate>
      
      <guid>https://divingintogeneticsandgenomics.com/archive/cool-use-of-unix-paste-with-ngs-sequences-fastq-to-fasta/</guid>
      <description>http://thegenomefactory.blogspot.com.au/search?updated-max=2012-09-08T12:11:00%2B10:00&amp;amp;max-results=7 Cool use of Unix paste with NGS sequences While browsing SeqAnswers.com today I came across a post where Uwe Appelt provided a couple of lines of Unix shell wizadry to solve some problem. What attracted my attention was the following:
 paste - - - - &amp;lt; in.fq | filter | tr &amp;quot;\t&amp;quot; &amp;quot;\n&amp;quot; &amp;gt; out.fq
 Now, I&#39;ve done a reasonable amount of shell one-liners in my life, but I&#39;d never seen this before.</description>
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      <title>Trimming adaptors from short read sequences</title>
      <link>https://divingintogeneticsandgenomics.com/archive/trimming-adaptors-from-short-read-sequences/</link>
      <pubDate>Wed, 03 Apr 2013 09:49:00 -0700</pubDate>
      
      <guid>https://divingintogeneticsandgenomics.com/archive/trimming-adaptors-from-short-read-sequences/</guid>
      <description>http://bcbio.wordpress.com/2009/08/09/trimming-adaptors-from-short-read-sequences/
Blue Collar Bioinformatics Trimming adaptors from short read sequences with 11 comments
One common post processing step for next generation, or short read, sequencing is to remove adaptor sequences. Sample preparation for sequencing often involves selection of a particular fraction of interest like expressed genes, microRNAs, or copy number variant regions. Selecting, amplifying, and sequencing these regions can result in read sequences containing a common tag that needs to be identified and removed before continuing with other analysis steps like alignment to the genome.</description>
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