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Hello all,
I'm a first year graduate student and just picked/joined my thesis lab. I have a bunch of illumina DNA sequencing data for both genome assembly and ChIP-Seq-like experiments. Im completely new to the computational aspects in these approaches - e.g. I have recently taught myself to move around in a Unix environment and my only achievement so far was to run fastQC on the sequence reads. Also, I have been working toward learning python.
What I would like to do next is align reads (ChIP-seq type experiment) to a human reference genome. Should I use MAQ? Bowtie? BWA?
How about peak callers? PeakSeq?
In the future I will also be dealing with RNA-seq data for both transcriptome assemblies and differential expression analyses. Any help here would also be welcome. e.g. how does one take RNA-seq data from two different tissues through the analysis pipeline and end up with those nice log-log plots?
Many many thanks,
Sciara C.
I'm a first year graduate student and just picked/joined my thesis lab. I have a bunch of illumina DNA sequencing data for both genome assembly and ChIP-Seq-like experiments. Im completely new to the computational aspects in these approaches - e.g. I have recently taught myself to move around in a Unix environment and my only achievement so far was to run fastQC on the sequence reads. Also, I have been working toward learning python.
What I would like to do next is align reads (ChIP-seq type experiment) to a human reference genome. Should I use MAQ? Bowtie? BWA?
How about peak callers? PeakSeq?
In the future I will also be dealing with RNA-seq data for both transcriptome assemblies and differential expression analyses. Any help here would also be welcome. e.g. how does one take RNA-seq data from two different tissues through the analysis pipeline and end up with those nice log-log plots?
Many many thanks,
Sciara C.