Each "motif probability curve" shows the (estimated) probability of the best match to a given motif occurring at a given position in the input sequences. This estimated probability is based only on sequences that contain at least one match with score greater than the minimum score defined for this motif, and is the maximum likelihood estimate of the conditional probability shown below.

Points (X,Y) on the plot are:
  Y = Pr(best match occurs at position X | sequence contains a match)

Note: The plots are smoothed according to the function selected from the "Smoothing" menu on the right. Setting the smoothing window size to 1 turns off smoothing.

If a negative dataset has been supplied then two lines are drawn for each motif representing both datasets. The normal dataset is plotted with a single unbroken line whereas the negative dataset is plotted with a dashed line.

This shows a listing of all motifs currently plotted on the graph.

The color used to plot a motif can be changed by clicking on the color swatch next to the motif you want to change, followed by clicking on the color swatch you wish to swap it with.

These are extra colors you may use for plotting motifs.

Click on the color swatch next to one of the above motifs, then click on one of these "unused color" swatches to change the color of the motif's plot.

These options change the display of the graph.

Smoothing:

Allows selection of the smoothing function applied to the graph.

The weighted moving average option uses weights shaped as an isosceles triangle where the central point (or points in an even sized window) get the maximum weight.

The moving average simply weights all points in the smoothing window equally.

Note: Setting the smoothing window size to 1 turns off smoothing.

Window

The window size used to smooth the graph. The larger the smoothing window size, the smoother the graph, at the cost of hiding detail.

Below a smoothing window size of 10, thinner lines are used on the graph to allow more detail to be visible.

Note: Remember to press "return" or "enter" after changing the number in the input box in order to see the effect of the new smoothing window size.

Legend

Choose to display/disable the on-graph legend. The legend can be moved by clicking on the graph.

Negative Sequences

Choose whether to plot the motif probability curve(s) for the negative sequences (if provided). The curve(s) are plotted as dashed lines, using the same color as the corresponding curve for the positive sequences.

Zoom

Drag a range on the graph to zoom into that section. Clicking "Undo Zoom" will return the view to the preiously displayed part of the graph and clicking "Center on 0" will move the view so 0 is in the center.

Download EPS

Download the graph that you are currently viewing as an encapsulated postscript (EPS) image. EPS images are scalable making them suitable for publication.

List only enriched motifs that meet the selected filter criteria below.

Selected motifs are always listed; deselect all motifs first by clicking on the "X" above the color swatches if you wish to filter all motifs.

To filter on "ID" or "Name", you can enter any Javascript regular expression pattern. See here for documentation on Javascript regular expression patterns.

Sorting is applied after filtering where possible (the exception being the "Top" filter) so the filters applied will affect the sort. You can choose the motif sorting feature using the "Motifs:" menu.

If CentriMo is searching for locally enriched regions (not just centrally enriched regions), then multiple regions may be found per motif, and the "Regions:" menu will also be displayed. In this case, CentriMo first sorts all regions using the feature shown in the "Regions:" menu, and then it sorts the highest-ranked region of each motif according to the feature shown in the "Motifs:" menu.

Unless you check the box next to the "Regions:" menu, it will automatically show the same feature as the "Motifs:" menu (or "E-value" if a motif-only feature is chosen in the "Motifs:" menu).

Note:The motif p-value shown in the plot legend will always be for the region with the lowest p-value, and therefore may not match the value shown in the table "p-value" column when the "Regions:" menu is not set to "p-value".

The name of the database (file name) that contains the motif.

An ID for the motif that is unique in the motif database file. If more than one motif has the same ID, CentriMo uses only the first such motif.

An alternate ID of the motif that may be provided in the motif database file.

A consensus sequence is constructed from each column in a motif's frequency matrix using the "50% rule" as follows.

1. The letter frequencies in the column are sorted in decreasing order.
2. Letters with frequency less 50% of the maximum are discarded.
3. The letter used in this position in the consensus sequence is determined by the first rule below that applies:
• If there is only one letter left, or if the remaining letters exactly match an ambiguous symbol in the alphabet, the letter or ambiguous symbol, respectively, is used.
• Otherwise, if the remaining set contains at least 50% of the core symbols in the alphabet, the alphabet's wildcard (e.g., "N" for DNA or RNA, and "X" for protein) is used.
• Otherwise, the letter with the maximum frequency is used.

The expected number motifs that would have least one region as comparatively enriched for best matches to the motif as the reported region in the positive sequences compared with the negative sequences.

The Fisher E-value is the (one-sided) p-value of the one-sided Fisher's exact test that at least as many best matches in the region in the positive sequences that contain at least one match, multiplied by the number of motifs in the input database(s). The Fisher's exact test p-value is corrected for the number of regions and score thresholds tested ("Multiple Tests").

Fisher's exact test assumes that the probability that the best match (if any) falls into a given region is the same for all positive and negative sequences.

The probability that any tested region would be as enriched for best matches to this motif as the reported region is.

By default the p-value is calculated by using the one-tailed binomial test on the number of sequences with a match to the motif ("Total Matches") that have their best match in the reported region ("Region Matches"), corrected for the number of regions and score thresholds tested ("Multiple Tests"). The test assumes that the probability that the best match in a sequence falls in the region is the region width divided by the number of places a motif can align in the sequence (sequence length minus motif width plus 1).

When CentriMo is run in discriminative mode with a negative set of sequences, the p-value of a region is calculated using Fisher's exact test on the enrichment of best matches in the positive sequences ("Region Matches") relative to the negative sequences ("Negative Region Matches"), corrected for the number of regions and score thresholds tested ("Multiple Tests"). The test assumes that the probability that the best match (if any) falls into a given region is the same for all positive and negative sequences.

The expected number motifs that would have least one region as enriched for best matches to the motif as the reported region. The E-value is the p-value multiplied by the number of motifs in the input database(s).

The Matthew's Correlation Coefficient (MCC) gives a measure of the ability of the motif to discriminate the positive sequences from the negative sequences:

MCC = [TP*TN - FP*FN] / [(TP + FP) * (TP + FN) * (TN + FP) * (TN + FN)]

TP is the number of positive sequences with a best match in the reported region,

FP is the number of negative sequences with a best match in the reported region,

TN is the number of negative sequences without a best match in the reported region, and

FN is the number of positive sequences without a best match in the reported region.

MCC ranges from -1 to +1, where a +1 result indicates that the occurrence of the best match to the motif in the reported region perfectly discriminates positive sequences from negative sequences.

This is the score threshold (in bits) for determining if a sequence contains a match to this motif.

When score optimization is enabled, this column lists the score threshold that gives the best p-value. Otherwise it shows the smallest score found that was above the minimum score threshold specified to CentriMo.

The width (in sequence positions) of the most enriched region. A best match to the motif is counted as being in the region if the center of the motif falls in the region.

The number of (positive) sequences whose best match to the motif falls in the reported region.

Note: This number may be less than the number of (positive) sequences that have a best match in the region. The reason for this is that a sequence may have many matches that score equally best. If n matches have the best score in a sequence, 1/n is added to the appropriate bin for each match.

The number of negative sequences where the best match to the motif falls in the reported region. This value is rounded but the underlying value may contain fractional counts.

Note: This number may be less than the number of negative have a best match in the region. The reason for this is that a sequence may have many matches that score equally best. If n matches have the best score in a sequence, 1/n is added to the appropriate bin for each match.

The number of sequences containing a match to the motif above the score threshold ("Score Threshold").

The number of negative sequences containing a match to the motif above the minimum score threshold. When score optimization is enabled the score threshold may be raised higher than the minimum.

The probability that any tested region in the negative sequences would be as enriched for best matches to this motif according to the Binomial test.

Use the filter to display only motifs differentially enriched in both datasets (low p-value and high negative p-value).

The maximum probability that the best match occurs at any single sequence position. If the smoothing window size ("Window:", to right of graph) is set to "1", then this is value is the maximum value of the match-probability curve.

This is the number of multiple tests (n) done for this motif. It was used to correct the original p-value of a region for multiple tests using the formula

p' = 1 - (1-p)^n

where p is the uncorrected p-value. The number of multiple tests is the number of regions considered times the number of score thresholds considered. It depends on the motif length, sequence length, and the type of optimizations being done (central enrichment, local enrichement, score optimization).

Location of the center of the most enriched region.

The text box lists the sequence identifiers for sequences which have at least one of their best matches in the most significant region of all the selected motifs.

The "Intersection" subheading gives the number of identifiers in the text box and their percentage out of the total number of input sequences.

The "Union" subheading lists the number and percentage of sequences that have at least one of their best matches in the most significant region of any of the selected motifs and their percentage out of the total number of input sequences.

Note that the number of sequences with a match to a given motif in its best region may be larger than the value of "Region Matches". This is because a sequence may have multiple equally best matches and in that case a fractional match count is assigned to each of them when "Region Matches" is computed.

When more than one significant, non-overlapping region is found, they can be shown (and hidden again) by clicking the arrow.

By default the regions are sorted by E-value, but this can be changed by the menu on the right of the page.

Sequence position where the (unsmoothed) match-probability curve for this motif attains its maximum. Set the smoothing window size ("Window:", to right of graph) to "1" to see the unsmoothed match probability curve.