Difference between revisions of "Run MACS 1.4.0 on ChiP-Seq (analysis)"

Revision as of 17:02, 23 April 2013

Analysis title

Run MACS 1_4_0 on ChiP-Seq

Provider

Institute of Systems Biology

Description

This is an advanced version of MACS 1.3.7. In this version during the model building, MACS will pick out the enriched regions which are not too high and not too low to build the paired-peak model. Default the region is from fold 10 to fold 30. If MACS fails to build the model, by default it will use the nomodel settings, like shiftsize=100bps, to shift and extend each tags.

Parameters:

• Track – Filtering track
• Control track – Control track (can be omitted)
• Genome size – Effective genome size
• Tag size (0 = autodetect) (expert) – Length of the tag in bp. If 0, it will be calculated based on average read length over several first reads.
• Band width – Band width
• P-value – P-value cutoff for peak detection
• MFOLD lower – Lower boundary of high-confidence enrichment ratio
• MFOLD upper – Upper boundary of high-confidence enrichment ratio
• Use fixed lambda (expert) – Use fixed background lambda as local lambda for every peak region
• Small region for dynamic lambda – The small nearby region in basepairs to calculate dynamic lambda. This is used to capture the bias near the peak summit region. Invalid if there is no control data.
• Large region for dynamic lambda – The large nearby region in basepairs to calculate dynamic lambda. This is used to capture the bias near the peak summit region. Invalid if there is no control data.
• No auto pair process (expert) – Whether to turn off the auto pair model process. If true, then when MACS failed to build paired model, it will exit with error message. Otherwise it will use the nomodel settings
• No model (expert) – Do not build the shifting model. In this mode shift size parameter is used.
• Shift size (expert) – The arbitrary shift size in bp. Used in no-model mode.
• Keep duplicates (expert) – How many tags will be kept in the same location (auto, all or number). Auto means value will be calculated based on binomal distribution using 1e-5 as p-value cutoff
• Scale to small – Whether to scale larger dataset down to smaller one.
• Compute peak profile (expert) – Compute peak profile
• Output name – Output name

More about MACS: http://liulab.dfci.harvard.edu/MACS/

Reference: Zhang et al. Model-based Analysis of ChIP-Seq (MACS). Genome Biol (2008) vol. 9 (9) pp. R137