HOMER
Software for motif discovery and next-gen sequencing analysis
Next-Generation Sequencing Analysis
ChIP-Seq is the best thing that happened to ChIP since the
antibody. It is 100x better than ChIP-Chip since it
escapes most of the problems of microarray probe
hybridization. Plus it is cheaper, and genome
wide. But ChIP-Seq is only the tip of the iceberg -
there are many inventive ways to use a sequencer.
Below are a list of the the more popular methods that will
be covered below:ChIP-Seq: Isolation and sequencing of
genomic DNA "bound" by a specific transcription factor,
covalently modified histone, or other nuclear
protein. This methodology provides genome-wide maps
of factor binding. Most of HOMER's routines cater to
the analysis of ChIP-Seq data.
DNase-Seq: Treatment of nuclei with a restriction enzyme such as DNase I will result in cleavage of DNA at accessible regions. Isolation of these regions and their detection by sequencing allows the creation of DNase hypersensitivity maps, providing information about which regulatory elements are accessible in the genome.
MNase-Seq: Micrococcal Nuclease (MNase) is a restriction enzyme that degrades genomic DNA not wrapped around histones. The remaining DNA represents nucleosomal DNA, and can be sequencing to reveal nucleosome positions along the genome. This method can also be combined with ChIP to map nucleosomes that contain specific histone modifications.
RNA-Seq: Extraction, fragmentation, and sequencing of RNA populations within a sample. The replacement for gene expression measurements by microarray. There are many variants on this, such as Ribo-Seq (isolation of ribosomes translating RNA), small RNA-Seq (to identify miRNAs), etc.
GRO-Seq: RNA-Seq of nascent RNA. Transcription is halted, nuclei are isolated, labeled nucleotides are added back, and transcription briefly restarted resulting in labeled RNA molecules. These newly created, nascent RNAs are isolated and sequenced to reveal "rates of transcription" as opposed to the total number of stable transcripts measured by normal RNA-seq.
Hi-C: Genomic interaction assay for understanding genome 3D structure. This assay is much more specialized - For more information about how to use HOMER to analyze Hi-C data, check out the Hi-C analysis section.
Unsolicited advice: If you are going to perform RNA-Seq, use a protocol for STRAND-SPECIFIC RNA-Seq. Why would you throw away the strand information?
More Unsolicited advice: Run controls!!!
Yet More Unsolicited advice: Be careful about GC-bias!!
DNase-Seq: Treatment of nuclei with a restriction enzyme such as DNase I will result in cleavage of DNA at accessible regions. Isolation of these regions and their detection by sequencing allows the creation of DNase hypersensitivity maps, providing information about which regulatory elements are accessible in the genome.
MNase-Seq: Micrococcal Nuclease (MNase) is a restriction enzyme that degrades genomic DNA not wrapped around histones. The remaining DNA represents nucleosomal DNA, and can be sequencing to reveal nucleosome positions along the genome. This method can also be combined with ChIP to map nucleosomes that contain specific histone modifications.
RNA-Seq: Extraction, fragmentation, and sequencing of RNA populations within a sample. The replacement for gene expression measurements by microarray. There are many variants on this, such as Ribo-Seq (isolation of ribosomes translating RNA), small RNA-Seq (to identify miRNAs), etc.
GRO-Seq: RNA-Seq of nascent RNA. Transcription is halted, nuclei are isolated, labeled nucleotides are added back, and transcription briefly restarted resulting in labeled RNA molecules. These newly created, nascent RNAs are isolated and sequenced to reveal "rates of transcription" as opposed to the total number of stable transcripts measured by normal RNA-seq.
Hi-C: Genomic interaction assay for understanding genome 3D structure. This assay is much more specialized - For more information about how to use HOMER to analyze Hi-C data, check out the Hi-C analysis section.
Unsolicited advice: If you are going to perform RNA-Seq, use a protocol for STRAND-SPECIFIC RNA-Seq. Why would you throw away the strand information?
More Unsolicited advice: Run controls!!!
Yet More Unsolicited advice: Be careful about GC-bias!!
(mini tutorial for each of these data types are on their way... someday...)
HOMER offers solid tools and methods for interpreting Next-gen-Seq experiments. In addition to UCSC visualization support and peak finding [and motif finding of course], HOMER can help assemble data across multiple experiments and look at positional specific relationships between sequencing tags, motifs, and other features. You do not need to use the peak finding methods in this package to use motif finding.
Basic Analysis can be separated into the following steps for each experiment type:
New Tutorial: Introduction to next-gen sequencing, FASTQ files, mapping, samtools, and more.
- Mapping to the genome (NOT performed by HOMER, but important to understand)
- Creation Tag directories,
quality control, and normalization. (makeTagDirectory)
- UCSC visualization (makeUCSCfile, makeBigWig.pl)
- Peak finding / Transcript detection / Feature identification (findPeaks)
- Motif analysis (findMotifsGenome.pl)
- Annotation of Peaks (annotatePeaks.pl)
- Quantification of Data at Peaks/Regions in the Genome/Histograms and Heatmaps (annotatePeaks.pl)
- Quantification of
Transcripts (analyzeRNA.pl)
- General sequence manipulation tools (homerTools)
- Miscellaneous Tools for
Sharing Data between programs, etc. (tagDir2bed.pl, bed2pos.pl,
pos2bed.pl ...)
- Finding overlapping or differentially bound peaks (mergePeaks, getDifferentialPeaks)
- ChIP-Seq analysis
automation (analyzeChIP-Seq.pl)
- Description of file formats
NOTE: The current implementation is geared for single tag sequencing. Experiments such as ChIP-seq don't necessarily gain much from paired-end sequencing (in terms of information/per bp).
Can't figure something out? Questions, comments, concerns, or other feedback:
cbenner@ucsd.edu