README for MACS (1.4.2)
Time-stamp: <2012-03-19 17:43:47 Tao Liu>
With the improvement of sequencing techniques, chromatin immunoprecipitation followed by high throughput sequencing (ChIP-Seq) is getting popular to study genome-wide protein-DNA interactions. To address the lack of powerful ChIP-Seq analysis method, we present a novel algorithm, named Model-based Analysis of ChIP-Seq (MACS), for identifying transcript factor binding sites. MACS captures the influence of genome complexity to evaluate the significance of enriched ChIP regions, and MACS improves the spatial resolution of binding sites through combining the information of both sequencing tag position and orientation. MACS can be easily used for ChIP-Seq data alone, or with control sample with the increase of specificity.
Please check the file 'INSTALL' in the distribution.
This is the only REQUIRED parameter for MACS. If the format is ELANDMULTIPET, user must provide two treatment files separated by comma, e.g. s_1_1_eland_multi.txt,s_1_2_eland_multi.txt.
The control or mock data file in either BED format or any ELAND output format specified by --format option. Please follow the same direction as for -t/--treatment.
The name string of the experiment. MACS will use this string NAME to create output files like 'NAME_peaks.xls', 'NAME_negative_peaks.xls', 'NAME_peaks.bed' , 'NAME_summits.bed', 'NAME_model.r' and so on. So please avoid any confliction between these filenames and your existing files.
Format of tag file, can be "ELAND", "BED", "ELANDMULTI", "ELANDEXPORT", "ELANDMULTIPET" (for pair-end tags), "SAM", "BAM" or "BOWTIE". Default is "AUTO" which will allow MACS to decide the format automatically. Please use "AUTO" only when you combine different formats of files.
The BED format is defined in "http://genome.ucsc.edu/FAQ/FAQformat#format1".
If the format is ELAND, the file must be ELAND result output file, each line MUST represents only ONE tag, with fields of:
Sequence name (derived from file name and line number if format is not Fasta)
Type of match
NM: no match found. QC: no matching done: QC failure (too many Ns basically). RM: no matching done: repeat masked (may be seen if repeatFile.txt was specified). U0: Best match found was a unique exact match. U1: Best match found was a unique 1-error match. U2: Best match found was a unique 2-error match. R0: Multiple exact matches found. R1: Multiple 1-error matches found, no exact matches. R2: Multiple 2-error matches found, no exact or 1-error matches.
Number of exact matches found.
Number of 1-error matches found.
Number of 2-error matches found. Rest of fields are only seen if a unique best match was found (i.e. the match code in field 3 begins with "U").
Genome file in which match was found.
Position of match (bases in file are numbered starting at 1).
Direction of match (F=forward strand, R=reverse).
How N characters in read were interpreted: ("."=not applicable, "D"=deletion, "I"=insertion). Rest of fields are only seen in the case of a unique inexact match (i.e. the match code was U1 or U2).
Position and type of first substitution error (e.g. 12A: base 12 was A, not whatever is was in read).
Position and type of first substitution error, as above.
If the format is ELANDMULTI, the file must be ELAND output file from multiple-match mode, each line MUST represents only ONE tag, with fields of:
- Sequence name
- Either NM, QC, RM (as described above) or the following:
- x:y:z where x, y, and z are the number of exact, single-error, and 2-error matches found.
- Blank, if no matches found or if too many matches found, or the following: BAC_plus_vector.fa:163022R1,170128F2,E_coli.fa:3909847R1 This says there are two matches to BAC_plus_vector.fa: one in the reverse direction starting at position 160322 with one error, one in the forward direction starting at position 170128 with two errors. There is also a single-error match to E_coli.fa.
If the data is from Pair-End sequencing. You can sepecify the format as ELANDMULTIPET ( stands for ELAND Multiple-match Pair-End Tags), then the --treat (and --control if needed) parameter must be two file names separated by comma. Each file must be in ELAND multiple-match format described above. e.g.
macs14 --format ELANDMULTIPET -t s_1_1_eland_multi.txt,s_2_1_eland_multi.txt ...
If you use ELANDMULTIPET, you may need to modify --petdist parameter.
If the format is BAM/SAM, please check the definition in (http://samtools.sourceforge.net/samtools.shtml). Pair-end mapping results can be saved in a single BAM file, if so, MACS will automatically keep the left mate(5' end) tag.
If the format is BOWTIE, you need to provide the ASCII bowtie output file with the suffix '.map'. Please note that, you need to make sure that in the bowtie output, you only keep one location for one read. Check the bowtie manual for detail if you want at (http://bowtie-bio.sourceforge.net/manual.shtml)
Here is the definition for Bowtie output in ASCII characters I copied from the above webpage:
- Name of read that aligned
- Orientation of read in the alignment, - for reverse complement, + otherwise
- Name of reference sequence where alignment occurs, or ordinal ID if no name was provided
- 0-based offset into the forward reference strand where leftmost character of the alignment occurs
- Read sequence (reverse-complemented if orientation is -)
- ASCII-encoded read qualities (reversed if orientation is -). The encoded quality values are on the Phred scale and the encoding is ASCII-offset by 33 (ASCII char !).
- Number of other instances where the same read aligns against the same reference characters as were aligned against in this alignment. This is not the number of other places the read aligns with the same number of mismatches. The number in this column is generally not a good proxy for that number (e.g., the number in this column may be '0' while the number of other alignments with the same number of mismatches might be large). This column was previously described as "Reserved".
- Comma-separated list of mismatch descriptors. If there are no mismatches in the alignment, this field is empty. A single descriptor has the format offset:reference-base>read-base. The offset is expressed as a 0-based offset from the high-quality (5') end of the read.
For BED format, the 6th column of strand information is required by MACS. And please pay attention that the coordinates in BED format is zero-based and half-open (http://genome.ucsc.edu/FAQ/FAQtracks#tracks1).
For plain ELAND format, only matches with match type U0, U1 or U2 is accepted by MACS, i.e. only the unique match for a sequence with less than 3 errors is involed in calculation. If multiple hits of a single tag are included in your raw ELAND file, please remove the redundancy to keep the best hit for that sequencing tag.
For the experiment with several replicates, it is recommended to concatenate several ChIP-seq treatment files into a single file. To do this, under Unix/Mac or Cygwin (for windows OS), type:
cat replicate1.bed replicate2.bed replicate3.bed > all_replicates.bed
ELAND export format support sometimes may not work on your datasets, because people may mislabel the 11th and 12th column. MACS uses 11th column as the sequence name which should be the chromosome names.
Best distance between Pair-End Tags. Only available when format is 'ELANDMULTIPE'. Default is 200bps. When MACS reads mapped positions for 5' tag and 3' tag, it will decide the best pairing for them using this best distance parameter. A simple scoring system is used as following:
score = abs(abs(p5-p3)-200)+e5+e5
Where p5 is one of the position of 5' tag, and e5 is the mismatch/error for this mapped position of 5' tag. p3 and e3 are for 3' tag. Then the lowest scored paring is regarded as the best pairing. The 5' tag position of the pair is kept in model building and peak calling.
PLEASE assign this parameter to fit your needs!
It's the mappable genome size or effective genome size which is defined as the genome size which can be sequenced. Because of the repetitive features on the chromsomes, the actual mappable genome size will be smaller than the original size, about 90% or 70% of the genome size. The default hs -- 2.7e9 is recommended for UCSC human hg18 assembly. Here are all precompiled parameters for effective genome size:
-g hs = -g 2.7e9 -g mm = -g 1.87e9 -g ce = -g 9e7 -g dm = -g 1.2e8
The size of sequencing tags. If you DON'T specify it, MACS will try to use the first 10 sequences from your input treatment file to determine the tag size. Specifying it will override the automatic determined tag size.
The band width which is used to scan the genome for model building. You can set this parameter as the sonication fragment size expected from wet experiment. The previous side effect on the peak detection process has been removed. So this parameter only affects the model building.
The pvalue cutoff. Default is 1e-5.
This parameter is used to select the regions within MFOLD range of high-confidence enrichment ratio against background to build model. The regions must be lower than upper limit, and higher than the lower limit of fold enrichment. DEFAULT:10,30 means using all regions not too low (>10) and not too high (<30) to build paired-peaks model. If MACS can not find more than 100 regions to build model, it will use the --shiftsize parameter to continue the peak detection.
Check related --off-auto and --shiftsize for detail.
With this flag on, MACS will use the background lambda as local lambda. This means MACS will not consider the local bias at peak candidate regions.
These two parameters control which two levels of regions will be checked around the peak regions to calculate the maximum lambda as local lambda. By default, MACS considers 1000bp for small local region(--slocal), and 10000bps for large local region(--llocal) which captures the bias from a long range effect like an open chromatin domain. You can tweak these according to your project. Remember that if the region is set too small, a sharp spike in the input data may kill the significant peak.
Whether turn on the auto paired-peak model process. If set, when MACS failed to build paired model, it will use the nomodel settings, the '--shiftsize' parameter to shift and extend each tags. If not set, MACS will be terminated if paried-peak model is failed.
While on, MACS will bypass building the shifting model.
While '--nomodel' is set, MACS uses this parameter to shift tags to their midpoint. For example, if the size of binding region for your transcription factor is 200 bp, and you want to bypass the model building by MACS, this parameter can be set as 100. This option is only valid when --nomodel is set or when MACS fails to build paired-peak model.
It controls the MACS behavior towards duplicate tags at the exact same location -- the same coordination and the same strand. The default 'auto' option makes MACS calculate the maximum tags at the exact same location based on binomal distribution using 1e-5 as pvalue cutoff; and the 'all' option keeps every tags. If an integer is given, at most this number of tags will be kept at the same location. Default: 1.
When not set, scale the larger dataset down to the smaller dataset; when set, the smaller dataset will be scaled towards the larger dataset.
If this flag is on, MACS will store the fragment pileup in wiggle format for every chromosome. The gzipped wiggle files will be stored in subdirectories named NAME+'_MACS_wiggle/treat' for treatment data and NAME+'_MACS_wiggle/control' for control data. --single-profile option can be combined to generate a single wig file for the whole genome.
If this flag is on, MACS will store the fragment pileup in bedGraph format for every chromosome. The bedGraph file is in general much smaller than wiggle file. However, The process will take a little bit longer than -w option, since theoratically 1bp resolution data will be saved. The bedGraph files will be gzipped and stored in subdirectories named NAME+'_MACS_bedGraph/treat' for treatment and NAME+'_MACS_bedGraph/control' for control data. --single-profile option can be combined to generate a single bedGraph file for the whole genome.
-S/--single-profile (formerly --single-wig)
If this flag is on, MACS will store the fragment pileup in wiggle or bedGraph format for the whole genome instead of for every chromosomes. The gzipped wiggle files will be stored in subdirectories named EXPERIMENT_NAME+'_MACS_wiggle'+'_MACS_wiggle/treat/' +EXPERIMENT_NAME+'treat_afterfiting_all.wig.gz' or 'treat_afterfiting_all.bdg.gz' for treatment data, and EXPERIMENT_NAME+'_MACS_wiggle'+'_MACS_wiggle/control/' +EXPERIMENT_NAME+'control_afterfiting_all.wig.gz' or 'control_afterfiting_all.bdg.gz' for control data.
By default, the resoluation for saving wiggle files is 10 bps,i.e., MACS will save the raw tag count every 10 bps. You can change it along with '--wig' option.
Note this option doesn't work if -B/--bdg is on.
If set, MACS will invoke Mali Salmon's PeakSplitter software through system call. If PeakSplitter can't be found, an instruction will be shown for downloading and installing the PeakSplitter package. The PeakSplitter can refine the MACS peaks and split the wide peaks into smaller subpeaks. For more information, please check the following URL:
Note this option doesn't work if -B/--bdg is on.
If you don't want to see any message during the running of MACS, set it to 0. But the CRITICAL messages will never be hidden. If you want to see rich information like how many peaks are called for every chromosome, you can set it to 3 or larger than 3.
A diagnosis report can be generated through this option. This report can help you get an assumption about the sequencing saturation. This funtion is only in beta stage.
--fe-min, --fe-max & --fe-step
For diagnostics, FEMIN and FEMAX are the minimum and maximum fold enrichment to consider, and FESTEP is the interval of fold enrichment. For example, "--fe-min 0 --fe-max 40 --fe-step 10" will let MACS choose the following fold enrichment ranges to consider: [0,10), [10,20), [20,30) and [30,40).
NAME_peaks.xls is a tabular file which contains information about called peaks. You can open it in excel and sort/filter using excel functions. Information include: chromosome name, start position of peak, end position of peak, length of peak region, peak summit position related to the start position of peak region, number of tags in peak region, -10*log10(pvalue) for the peak region (e.g. pvalue =1e-10, then this value should be 100), fold enrichment for this region against random Poisson distribution with local lambda, FDR in percentage. Coordinates in XLS is 1-based which is different with BED format.
NAME_peaks.bed is BED format file which contains the peak locations. You can load it to UCSC genome browser or Affymetrix IGB software. The 5th column in this file is the -10*log10pvalue of peak region.
NAME_summits.bed is in BED format, which contains the peak summits locations for every peaks. The 5th column in this file is the summit height of fragment pileup. If you want to find the motifs at the binding sites, this file is recommended.
NAME_negative_peaks.xls is a tabular file which contains information about negative peaks. Negative peaks are called by swapping the ChIP-seq and control channel.
NAME_model.r is an R script which you can use to produce a PDF image about the model based on your data. Load it to R by:
R --vanilla < NAME_model.r
Then a pdf file NAME_model.pdf will be generated in your current directory. Note, R is required to draw this figure.
NAME_treat/control_afterfiting.wig.gz files in NAME_MACS_wiggle directory are wiggle format files which can be imported to UCSC genome browser/GMOD/Affy IGB. The .bdg.gz files are in bedGraph format which can also be imported to UCSC genome browser or be converted into even smaller bigWig files.
NAME_diag.xls is the diagnosis report. First column is for various fold_enrichment ranges; the second column is number of peaks for that fc range; after 3rd columns are the percentage of peaks covered after sampling 90%, 80%, 70% ... and 20% of the total tags.
NAME_peaks.subpeaks.bed is a text file which IS NOT in BED format. This file is generated by PeakSplitter (<http://www.ebi.ac.uk/bertone/software/PeakSplitter_Cpp_usage.txt>) when --call-subpeaks option is set.
Other useful links
Cistrome web server for ChIP-chip/seq analysis: http://cistrome.org/ap/
bedTools -- a super useful toolkits for genome annotation files: http://code.google.com/p/bedtools/
UCSC toolkits: http://hgdownload.cse.ucsc.edu/admin/exe/