Tab-separated plain text file that contains one list of peaks. Each peak is described for the chromosome, the starting and the ending position in BED format.

Example about the format on a file with peaks in BED format:

chr   pos1   pos2
chr   pos1   pos2
...

Tab-separated plain text file that contains one list of peaks. Each peak is described for the chromosome, the starting and the ending position in BED format.

Example about the format on a file with peaks in BED format:

chr   pos1   pos2
chr   pos1   pos2
...

Text labels that will be used to identify the peaks from each set when performing the comparison and building the final lists of overlapping and specific peaks. Spaces and special characters will be substituted for the symbol "_".

Minimum size in the overlap between two peaks that coincide to be considered as a successful match.

Definition of graphical parameters to customize the Venn diagram between both sets of elements.

- Background color is used to fill the circles inside.
- Circle line color is used for the line around each circle.

Colors must be defined in the R software as shown in the following table.

- Transparency degree: alpha channel value related to the opacity in overlapping areas.
- Extract the number: this option is useful when there is not enough space to put a number inside an area of the diagram.
- Distance of the set name to circle: this option is useful to increase the space between the label of the set and the corresponding circle.

Definition of graphical parameters to customize the Venn diagram global appearance.

- Font size of gene names is useful to change the size of labels outside the diagram.
- Font size of numbers is useful to change the size of numbers inside the diagram.
- Line width of circles can be used to adapt the thickness of the Venn diagram circles.
- Figure size (small/normal): this option adapts the margins of the page and generates smaller plots (if necessary).
- Extract the common number permits the user to extract the value in the intersection of the diagram.
- Distance of external numbers together with the previous option is able to change the distance of numbers to the diagram.
- Proportional sizes: this option allows the users to generate proportional sets in the final diagram according to their sizes.
- Font family (helvetica/times) defines the family of the font (sans-serif or serif).

List of ChIPseq experiments that are available in our web site. Samples are classified into several main groups:

- Mouse embryonic stem cells (serum)
- Mouse embryonic stem cells (2i+LIF)
- Mouse HPC7 cells (hematopoietic precursor)
- Human K562 cells (chronic myelogenous leukemia)
- Human DU145 cells (prostate cancer)
- Drosophila wing imaginal discs (L3)

Users will choose one sample of the list to plot the trend exhibit by the subsets of genes provided at the same time. Optionally, it is possible to select a control experiment from the second list (e.g. Input or IgG samples) to display the background level in the resulting image.

Number of genesets that will be employed in the final graphical representation. For each list of genes provided by the user, the application will generate the resulting profile using the same sequencing experiment and the whole collection of profiles will be gathered into the same picture.

Plain text file that contains a list of elements for further characterization. Only one element is stored at each line. The name of the elements is used to index another file of information in which the features for all elements have been previously uploaded as well. The lines of the full set of values that correspond to each key here will be graphically represented afterwards.

Example about the format of one file with the elements that form a subset.

element1
element2
element3
...

Text labels that will be used to characterize the resulting boxplot of ChIPseq levels. Spaces and special characters will be substituted for the symbol "_".

Definition of graphical parameters to customize the global appearance of the resulting boxplot of ChIPseq levels.

- Color palette is the combination of colors that is used for the boxes.
- Color style for boxes can be used to determine whether the boxes are filled on a solid style, using colors for lines or black and white.
- Log scale converts the dsitributions of values submitted by the user into log scale distributions.
- Violin plots or violin plots with boxplots inside can be included in the final image instead of canonical boxplots.
- Line width can be used to adapt the thickness of the boxes of the boxplot.
- Outliers of each distribution can be included into the final boxplot.
- Each individual observation can be plotted as a point (optional).
- The size of the individual observations can be customized (see above for observations).
- The value on the X axis and the Y axis for the labels can be changed depending on the final boxplot.

Tab-separated plain text file generated by MACS that contains one list of peaks. Each peak is described for its location plus a series of several attributes and quality scores.

Example about the format on a file with peaks in MACS format:

chr  start	end	length	summit	tags	-10*log10(pvalue)	fold_enrichment	FDR(%)
chr1 3669878	3672606	2729	1433	123	193.84			6.05		0.00
chr1 4489349	4498634	9286	2549	566	169.78			3.69		0.00
chr1 4570559	4572646	2088	1400	100	73.15			2.79		1.02
...

To match ChIPseq peaks or regions of another classes to genes, users must select the appropriate catalog of RefSeq transcripts. Into this current version of SeqCode^WEB, there are five available collections of genes:

- Mouse (mm10)
- Mouse (mm9)
- Human (hg38)
- Human (hg19)
- Drosophila (dm3)

Users can run the stand-alone version of SeqCode to perform the same operation on any RefSeq catalog of transcripts.

Text label to characterize the peaks when matching to genes into the output files. Spaces and special characters will be substituted for the symbol "_".

Tab-separated plain text file that contains one list of peaks. Each peak is described for the chromosome, the starting and the ending position in BED format.

Example about the format on a file with peaks in BED format:

chr   pos1   pos2
chr   pos1   pos2
...

To match ChIPseq peaks or regions of another classes to genes, users must select the appropriate catalog of RefSeq transcripts. Into this current version of SeqCode^WEB, there are five available collections of genes:

- Mouse (mm10)
- Mouse (mm9)
- Human (hg38)
- Human (hg19)
- Drosophila (dm3)

Users can run the stand-alone version of SeqCode to perform the same operation on any RefSeq catalog of transcripts.

Text label to characterize the peaks when matching to genes into the output files. Spaces and special characters will be substituted for the symbol "_".

Users can define the region of the RefSeq transcripts that is useful to calculate the overlap against the ChIPseq peaks. There are three classes of definitions:

- One place upstream of the TSS until the TSS (excluding the gene body) or the TES (including the gene body)
- From the TES (excluding the gene body) or from the TSS (including the gene body) until one place downstream of the TES
- One region around the TSS (indicating the amount of positions upstream and downstream of the TSS)

In all these cases, it is necessary to set the length of the region that will be scanned when searching for overlaps between peaks and transcripts.

Definition of graphical parameters to customize the global appearance of the resulting piecharts of genome annotations.

- High/low detail is useful to switch between two lists of genomic features to characterize the peaks:

(Detailed)
* Distal promoters: the region between 2.5 Kb and 0.5 Kb upstream of the TSS of genes
* Proximal promoters: the region between the TSS and 0.5 Kb upstream of the TSS of genes
* 5'UTR and 3'UTR: untranslated regions upstream/downstream of transcripts (UTR exons)
* CDS: protein coding sequence part of transcripts (coding exons)
* Introns: spliced part of the genes that is not included into the transcripts
* Intergenic regions: genomic regions that do not belong to any of the previous classes

(Simple)
* Promoter region: the region between 2.5 Kb upstream of the TSS and the TSS
* Intragenic: exons and introns of genes
* Intergenic: genomic regions that are not classified as promoters or intragenic


Depending on the size of peaks, those elements can overlap with more than one class of genomic region. Thus, the total number of peaks shown in the title of the piechart will reflect these cases (this value will be equal or higher than the actual number of peaks provided by the user).
The corresponding spie chart to represent how significant are the results on the particular genome will be generated only when the High detail option is active. The circular grid can be optionally hidden.

- The color to depict each class of genomic region in the pie charts can be selected by the user
Colors must be defined in the R software coloring scheme as shown in the following table.

List of ChIPseq experiments that are available in our web site. Samples are classified into several main groups:

- Mouse embryonic stem cells (serum)
- Mouse embryonic stem cells (2i+LIF)
- Mouse HPC7 cells (hematopoietic precursor)
- Human K562 cells (chronic myelogenous leukemia)
- Human DU145 cells (prostate cancer)
- Drosophila wing imaginal discs (L3)

Users will choose one sample of the list to plot the trend exhibit by the subsets of genes provided at the same time. Optionally, it is possible to select a control experiment from the second list (e.g. Input or IgG samples) to display the background level in the resulting image.

Number of genesets that will be employed in the final graphical representation. For each list of genes provided by the user, the application will generate the resulting profile using the same sequencing experiment and the whole collection of profiles will be gathered into the same picture.

Plain text file that contains a list of elements for further characterization. Only one element is stored at each line. The name of the elements is used to index another file of information in which the features for all elements have been previously uploaded as well. The lines of the full set of values that correspond to each key here will be graphically represented afterwards.

Example about the format of one file with the elements that form a subset.

element1
element2
element3
...

Definition of graphical parameters to customize the appearance of the multiple lists of genes into the resulting metaplot.

For each list of genes, users can define the following values:
- The color to represent the list of genes in the metaplot
- The style of the line: solid, dashed or dotted
- The width or thickness of the line: from 1 to 8
- The level of transparency when overlapping to other lines

Colors must be defined in the R software coloring scheme as shown in the following table.

Definition of graphical parameters to customize the global appearance of the resulting metaplot.

Users can change the values of following parameters:
- The background and foreground colors of the metaplot
- The size of the font legend
- The style of the line depicting the TSS/TES of genes
- The width of the line depicting the TSS/TES of genes
- The colour of the line depicting the TSS/TES of genes
- The minimum and maximum value of the Y axis to crop the image

Colors must be defined in the R software coloring scheme as shown in the following table.

Plain text file that contains a list of elements for further characterization. Only one element is stored at each line. The name of the elements is used to index another file of information in which the features for all elements have been previously uploaded as well. The lines of the full set of values that correspond to each key here will be graphically represented afterwards.

Example about the format of one file with the elements that form a subset.

element1
element2
element3
...

Number of ChIPseq experiments that will be employed in the final graphical representation. For each sample selected by the user, the application will generate the resulting heat map using the same set of genes provided before and the whole collection of maps will be gathered into the same picture.

List of ChIPseq experiments that are available in our web site. Samples are classified into several main groups:

- Mouse embryonic stem cells (serum)
- Mouse embryonic stem cells (2i+LIF)
- Mouse HPC7 cells (hematopoietic precursor)
- Human K562 cells (chronic myelogenous leukemia)
- Human DU145 cells (prostate cancer)
- Drosophila wing imaginal discs (L3)

Users can choose up to five different samples of the list to plot the heat maps corresponding to the same set of genes provided at this moment. It is possible to select a control experiment from the same list (e.g. Input or IgG samples) to display the background level in the resulting heat map.

Text labels that will be used to characterize the resulting heatmap (title). Spaces and special characters will be substituted for the symbol "_".

Definition of graphical parameters to customize the appearance of the multiple heat maps into the resulting metaplot.

For each ChIPseq sample, users can define the following colors:
- Foreground color to represent the presence of signal at each gene
- Background color to represent the absence of signal at each gene

Colors must be defined in the R software coloring scheme as shown in the following table.

Definition of graphical parameters to customize the appearance of the image containing the full set of heat maps.

Users can change the values of following parameters:
- The background and foreground colors of the multiple heatmap
- To generate a uniform heat map in which the regions associated to each gene in the map display only presence (foreground color) or absence of signal (background color). In other words, it is generated a binary heat map as there is not a degree of colors proportional to the strength of the ChIP signal
- To normalize all the heat maps using the same value to favor the comparison among them

Colors must be defined in the R software coloring scheme as shown in the following table.

List of ChIPseq experiments that are available in our web site. Samples are classified into several main groups:

- Mouse embryonic stem cells (serum)
- Mouse embryonic stem cells (2i+LIF)
- Mouse HPC7 cells (hematopoietic precursor)
- Human K562 cells (chronic myelogenous leukemia)
- Human DU145 cells (prostate cancer)
- Drosophila wing imaginal discs (L3)

Users will choose one sample of the list to plot the trend exhibit by the subsets of genes provided at the same time. Optionally, it is possible to select a control experiment from the second list (e.g. Input or IgG samples) to display the background level in the resulting image.

Number of genesets that will be employed in the final graphical representation. For each list of genes provided by the user, the application will generate the resulting profile using the same sequencing experiment and the whole collection of profiles will be gathered into the same picture.

Plain text file that contains a list of elements for further characterization. Only one element is stored at each line. The name of the elements is used to index another file of information in which the features for all elements have been previously uploaded as well. The lines of the full set of values that correspond to each key here will be graphically represented afterwards.

Example about the format of one file with the elements that form a subset.

element1
element2
element3
...

Definition of graphical parameters to customize the appearance of the multiple lists of genes into the resulting metaplot.

For each list of genes, users can define the following values:
- The color to represent the list of genes in the metaplot
- The style of the line: solid, dashed or dotted
- The width or thickness of the line: from 1 to 8
- The level of transparency when overlapping to other lines

Colors must be defined in the R software coloring scheme as shown in the following table.

Definition of graphical parameters to customize the global appearance of the resulting metaplot.

Users can change the values of following parameters:
- The background and foreground colors of the metaplot
- The size of the font legend
- The style of the line depicting the TSS/TES of genes
- The width of the line depicting the TSS/TES of genes
- The colour of the line depicting the TSS/TES of genes
- The minimum and maximum value of the Y axis to crop the image

Colors must be defined in the R software coloring scheme as shown in the following table.

Users can generate barplots from a list of terms provided directly through the web form or by uploading an Enrichr file of results. Depending on the mode that is selected, users must provide the information in the specific box of parameters below: (1) Manual mode requires the user to input the name, score and percentage of genes belonging to such a class in comparison to the whole genome; (2) Enrichr file requires to upload the file of scores as provided by Enrichr for a particular ontology and gene set (Table option).

Number of terms of the ontology enrichment analysis to be included in the resulting barplot. For the Manual mode, the first N terms in the order generated by sorting all terms using the score provided by the user will be selected. For the Enrichr mode, all terms in the file will be ranked by the scoring attribute selected by the user and the TOP N in the current ranking will be selected for the barplot.

(Manual mode only) Users must provide for each term to be included in the output barplot, its name, a numerical natural score and a value of percentage. For scores, P values must be converted into natural numbers (e.g. -log P value) by the user prior to be provided here. Percentages correspond to the fraction of the genes of a particular class that belong to this term in comparison to the total number of genes of the same class annotated in the whole genome. Percentages must be provided without the % symbol.

For example, this a valid format for a term in this section:

MY TERM1   300   50
...

Users must upload the Enrichr file of analysys of a determined ontology over a given gene set. By clicking the "Export entries to table" function from Enrichr for a particular ontology term enrichment analysis, users can download this archive that comprises the full set of terms and scores as calculated by Enrichr.

Users will choose the Enrichr scoring attribute that will be used to rank the whole set of terms from the input file. The TOP N terms according to this attribute will be extracted to be display in the final barplot. Three different scoring schemes are available: P value, adjusted P value and combined score (see Enrichr documentation for further details).

Text labels that will be used to characterize the resulting barplot (title, X and Y axis). Spaces and special characters will be substituted for the symbol "_".

Definition of graphical parameters to customize the global appearance of the resulting barplots.

- The color of bars in the barplot.
- The color of borders of the bars in the barplot.
- Showing the term names on the left or inside the bars (hidden is also possible).
- Showing the percentages of members of each class inside the bars or not.
- Drawing barplots or bubbleplots in which the size of the circles is proportional to the percentage of each term.
- A grid in grey or black and white style can be integrated as a background of the boxplot.
- Set the size of fonts from terms, axis, and title.
- Line width can be used to adapt the thickness of the boxes of the boxplot.
- The background and foreground colors of the barplot.

Tab-separated plain text file that contains the list of elements and features. Each line of the list contains the same number of columns: the key that identifies the current element is introduced at the column 1 while the attributes are stored from column 2 up to column N. Commas (if any) are internally susbtituted for floating points. Not available values (NA) are included in the treatment.

Example about the format on a file with elements characterized using two features:

element1   value1   value2
element2   value1   value2
element3   value1   value2
...

Plain text file that contains a list of elements for further characterization. Only one element is stored at each line. The name of the elements is used to index another file of information in which the features for all elements have been previously uploaded as well. The lines of the full set of values that correspond to each key here will be graphically represented afterwards.

Example about the format of one file with the elements that form a subset.

element1
element2
element3
...

Selection of the columns of the file of features uploaded before for the full set of elements. For those items included in the subset, a graphical representation will be generated from their characteristics. Users must label each column with a description that will be inserted in the picture. Spaces will be substituted for the symbol "_". One color defined in the R software must be assigned to each category as well.

Colors must be defined in the R software as shown in the following table.

Text labels that will be used to characterize the resulting boxplot (title and Y axis). Spaces and special characters will be substituted for the symbol "_".

Definition of graphical parameters to customize the global appearance of the resulting boxplots.

- Font family (helvetica/times) defines the family of the font (sans-serif or serif). - Font size of the title is useful to change the size of the title above the boxplot.
- Font size of the axis Y is useful to change the size of values on this axis of the boxplot.
- Font size of the labels is useful to change the size of labels of the boxplot.
- Angle of the labels can be used to rotate (0/45/90 degrees) the labels of sets in the boxplot.
- Position of the labels allows the user to set the location of the X axis labels on a defined position.
- Line width can be used to adapt the thickness of the boxes of the boxplot.
- Show outliers must be active to include the outliers of the distributions into the boxplot.
- Log scale converts the distributions of values submitted by the user into log scale distributions.

Definition of graphical parameters to customize the graphical appearance of the complementary histograms.

- Font size of the title is useful to change the size of the title above the boxplot.
- Font size of the axis is useful to change the size of values on the axes of the boxplot.
- Font family (helvetica/times) defines the family of the font (sans-serif or serif). - Line width can be used to adapt the thickness of the boxes of the boxplot.

Tab-separated plain text file that contains the list of elements and features. Each line of the list contains the same number of columns: the key that identifies the current element is introduced at the column 1 while the attributes are stored from column 2 up to column N. Commas (if any) are internally susbtituted for floating points. Not available values (NA) are included in the treatment.

Example about the format on a file with elements characterized using two features:

element1   value1   value2
element2   value1   value2
element3   value1   value2
...

The user will select in the next step which column must be used to generate the boxplot.

Selection of one column of the file of features uploaded in the first step for the full set of elements. For the subsets of genes that will be included in the the third step, a graphical representation will be generated from the value of this column.

Plain text file that contains a list of elements for further characterization. Only one element is stored at each line. The name of the elements is used to index another file of information in which the features for all elements have been previously uploaded as well. The lines of the full set of values that correspond to each key here will be graphically represented afterwards.

Example about the format of one file with the elements that form a subset.

element1
element2
element3
...

Up to five different subsets can be incorporated into the same boxplot.
Users will provide a name for each subset that will be used to characterize them in the resulting plot.

Text labels that will be used to characterize the resulting boxplot (title and Y axis). Spaces and special characters will be substituted for the symbol "_".

Definition of graphical parameters to customize the global appearance of the resulting boxplots.

- Font family (helvetica/times) defines the family of the font (sans-serif or serif). - Font size of the title is useful to change the size of the title above the boxplot.
- Font size of the axis Y is useful to change the size of values on this axis of the boxplot.
- Font size of the labels is useful to change the size of labels of the boxplot.
- Angle of the labels can be used to rotate (0/45/90 degrees) the labels of sets in the boxplot.
- Position of the labels allows the user to set the location of the X axis labels on a defined position.
- Line width can be used to adapt the thickness of the boxes of the boxplot.
- Show outliers must be active to include the outliers of the distributions into the boxplot.
- Log scale converts the distributions of values submitted by the user into log scale distributions.

One color will be assigned to each box representing a subset in the boxplot.
Colors must be defined in the R software as shown in the following table.

Definition of graphical parameters to customize the graphical appearance of the complementary histograms.

- Font size of the title is useful to change the size of the title above the boxplot.
- Font size of the axis is useful to change the size of values on the axes of the boxplot.
- Font family (helvetica/times) defines the family of the font (sans-serif or serif). - Line width can be used to adapt the thickness of the boxes of the boxplot.

Tab-separated plain text file that contains the list of elements and features. Each line of the list contains the same number of columns: the key that identifies the current element is introduced at the column 1 while the attributes are stored from column 2 up to column N. Commas (if any) are internally susbtituted for floating points. Not available values (NA) are included in the treatment.

Example about the format on a file with elements characterized using two features:

element1   value1   value2
element2   value1   value2
element3   value1   value2
...

Plain text file that contains a list of elements for further characterization. Only one element is stored at each line. The name of the elements is used to index another file of information in which the features for all elements have been previously uploaded as well. The lines of the full set of values that correspond to each key here will be graphically represented afterwards.

Example about the format of one file with the elements that form a subset.

element1
element2
element3
...

Selection of the columns of the file of features uploaded in the first step for the full set of elements. For those items included in the subset during the second step, a graphical representation will be generated from their characteristics. Users must label each column with a description that will be inserted in the picture. Spaces will be substituted for the symbol "_".

Text labels that will be used to characterize the resulting boxplot (title and both axes). Spaces and special characters will be substituted for the symbol "_".

Definition of graphical parameters to customize the global appearance of the resulting boxplots.

- Color palette is the combination of colors that is used for the boxes.
- Color style for boxes can be used to determine whether the boxes are filled on a solid style, using colors for lines or black and white.
- Log scale converts the distributions of values submitted by the user into log scale distributions.
. Pseudocount value is added to each value of the distributions to avoid the calcularion of log 0.
- Violin plots or violin plots with boxplots inside can be included in the final image instead of canonical boxplots.
- A grid in grey or black and white style can be integrated as a background of the boxplot.
- Line width can be used to adapt the thickness of the boxes of the boxplot.
- Outliers of each distribution can be included into the final boxplot.
- Each individual observation can be plotted as a point (optional).
- The size of the individual observations can be customized (see above for observations).
- The value on the X axis and the Y axis for the labels can be changed depending on the final boxplot.
- The color of lines in the line plot of each individual
- The graphical appearance of lines in the line plot of each individual

Tab-separated plain text file that contains the list of elements and features. Each line of the list contains the same number of columns: the key that identifies the current element is introduced at the column 1 while the attributes are stored from column 2 up to column N. Commas (if any) are internally susbtituted for floating points. Not available values (NA) are included in the treatment.

Example about the format on a file with elements characterized using two features:

element1   value1   value2
element2   value1   value2
element3   value1   value2
...

Number of values (starting from the second column) that will be graphically represented for each gene in the heat map.

Text labels that will be used to represent each condition in the gene heat map and to characterize the resulting image (main title and legend features). Spaces and special characters will be substituted for the symbol "_".

Definition of graphical parameters to customize the global appearance of the resulting gene heat map.

- Color palette is the combination of colors that is used for the boxes
- Log scale converts the distributions of values submitted by the user into log scale distributions
- Define a max value allows for a direct color normalization of the gene heat map
- It is possible to perform hierachical clustering on the genes and/or the conditions (dendograms are optional)
- A grid can be superimposed to the final image and the color is configurable
- It is possible to show or hide the names of genes and/or conditions (depending on the number of elements, it is recommended to hide)
- Optionally, the actual value assigned to each gene and condition can be also displayed inside each cell
- To show the legend is useful to include the distribution of values in the upper corner of the gene heat map

Tab-separated plain text file that contains the statistics of each gene. Each line of the list contains the same number of columns: the key that identifies the current element is introduced at the column 1 while the attributes are stored from column 2 up to column N. Commas (if any) are internally susbtituted for floating points. There is a mandatory header line (in which the gene descriptor is omitted), usually generated by the DESeq2 software. However, users can create their own tabular file containing this information as long as the field descriptors of the key columns coincide with the ones defined elsewehere in the web application.

Example about the output format of the DESeq2 analysis in R:

baseMean	log2FoldChange	lfcSE	stat	pvalue	padj
0610005C13Rik	6.70	-1.09	0.53	-2.05	0.03 0.11
...

Users can provide tabular files directly generated by the DESeq2 R library or independently created. In all cases, an input file must be tabular (tab separated) and include a header line with the information about the attributes to be used for the plot generation.

Number of genes for which the user intends to highlight their name using labels overlapping their points in the MA plot.

Names of the genes for which a label containing their name will be included in the plot. The number of genes from these boxes that will be effectively added depends on the previous parameter.

When providing their own custom tabular file, its header line must contain such field descriptors that will be employed to find the values to build the MA plot.

Text label that will be used as a title and axis labels in the resulting MA plot. Spaces and special characters will be substituted

Definition of graphical parameters to customize the graphical appearance of the resulting MA plot:

- FC cutoff to define areas in the volcano plot.
- FDR cutoff to define areas in the volcano plot.
- Size of the points (genes) shown in the plot.
- Alpha transparency coefficient for points. - Size of the labels (if any) for genes in the plot.
- Colors to each area of the three gene sets as defined by the FC and FDR.
Colors must be defined in the R software as shown in the following table.

- Label style (bold/italics/boxed) if any.
- Number of labels to be shown in the MA plot.

Tab-separated plain text file that contains the list of elements and features. Each line of the list contains the same number of columns: the key that identifies the current element is introduced at the column 1 while the attributes are stored from column 2 up to column N. Commas (if any) are internally susbtituted for floating points. Not available values (NA) are included in the treatment.

Example about the format on a file with elements characterized using two features:

element1   value1   value2
element2   value1   value2
element3   value1   value2
...

From the list of experiments (values) provided above, the user will select several ones (up to nine) in order to perform the PCA analysis.

Once one column (condition) is included, it is necessary to use a text label for the identification and indicate the group of this feature. The group is useful in the final PCA plot to show in the same color those features in the space belonging to the same class.

Text label that will be used as a title in the resulting PCA plot. Spaces and special characters will be substituted

Definition of graphical parameters to customize the graphical appearance of the resulting PCA plot:

-One label and its color will be assigned to each group of conditions to highlight them in the bidimensional space plot.
Colors must be defined in the R software as shown in the following table.

- Log scale converts the distributions of values submitted by the user into log scale distributions.
- ncRNAs can be filtered out from the initial list of elements to help to improve the PCA analysis

Tab-separated plain text file that contains the list of elements and features. Each line of the list contains the same number of columns: the key that identifies the current element is introduced at the column 1 while the attributes are stored from column 2 up to column N. Commas (if any) are internally susbtituted for floating points. Not available values (NA) are included in the treatment.

Example about the format on a file with elements characterized using two features:

element1   value1   value2
element2   value1   value2
element3   value1   value2
...

Tab-separated plain text file that contains a subset of the main list of elements including the values of features that contribute to their characterization. Each line of the list contains the same number of columns: the key that identifies the current element is introduced at the column 1 while the attributes are stored from column 2 up to column N. Commas (if any) are internally susbtituted for floating points. Not available values (NA) are included in the treatment.

Example about the format on a file with elements characterized using two features:

element1   value1   value2
element2   value1   value2
element3   value1   value2
...

These elements will be included into the final plot, being superimposed to the points generated from the whole list of values using a disctinct color for being highlghted. Up to two different subsets can be integrated into the scatterplot.

Tab-separated plain text file that contains a subset of the main list of elements including the values of features that contribute to their characterization. Each line of the list contains the same number of columns: the key that identifies the current element is introduced at the column 1 while the attributes are stored from column 2 up to column N. Commas (if any) are internally susbtituted for floating points. Not available values (NA) are included in the treatment.

Example about the format on a file with elements characterized using two features:

element1   value1   value2
element2   value1   value2
element3   value1   value2
...

These elements will be included into the final plot, being superimposed to the points generated from the whole list of values using a disctinct color for being highlghted. Up to two different subsets can be integrated into the scatterplot.

Text labels that will be used to provide the title and the names of the two conditions being compared in the final scatterplot. Spaces and special characters will be substituted for the symbol "_".

Definition of graphical parameters to customize the global appearance of the resulting scatterplot.

- Log scale converts the distributions of values submitted by the user into log scale distributions.
- Null lines that contain 0 in both conditions can be excluded from the scatterplot
- Color palette is the combination of colors that is used for the points and the background
- Both optional subsets of points can be customized with a distinct color
- It is able to include several classes of guidelines (diagonal y=x, lines to denote several fold-change conditions)
- The regression line can be integrated into the picture (optional), customizing the color and the thickness
- Show lowest density area points is useful to highlight the areas with less points (potential outliers)
- Binarization values are useful to play with the balance between image smoothness and size of the scatterplot
- It is possible to crop the image by defining particular values for X and Y

Colors must be defined in the R software as shown in the following table.

Tab-separated plain text file that contains the statistics of each gene. Each line of the list contains the same number of columns: the key that identifies the current element is introduced at the column 1 while the attributes are stored from column 2 up to column N. Commas (if any) are internally susbtituted for floating points. There is a mandatory header line (in which the gene descriptor is omitted), usually generated by the DESeq2 software. However, users can create their own tabular file containing this information as long as the field descriptors of the key columns coincide with the ones defined elsewehere in the web application.

Example about the output format of the DESeq2 analysis in R:

baseMean	log2FoldChange	lfcSE	stat	pvalue	padj
0610005C13Rik	6.70	-1.09	0.53	-2.05	0.03 0.11
...

Users can provide tabular files directly generated by the DESeq2 R library or independently created. In all cases, an input file must be tabular (tab separated) and include a header line with the information about the attributes to be used for the plot generation.

Number of genes for which the user intends to highlight their name using labels overlapping their points in the volcano plot.

Names of the genes for which a label containing their name will be included in the plot. The number of genes from these boxes that will be effectively added depends on the previous parameter.

When providing their own tabular files, those values should be found in the header line that describes the content of the archive. Both values will be used to generate the custom volcano plot.x

Text that will be used as a title, subtitles and axis labels in the resulting volcano plot. Spaces and special characters will be substituted

Definition of graphical parameters to customize the graphical appearance of the resulting Volcano plot:

- FC cutoff to define areas in the volcano plot.
- P value cutoff to define areas in the volcano plot.
- Size of the points (genes) shown in the plot.
- Size of the labels (if any) for genes in the plot.
- Colors to each area of the four ones as defined by the FC and P value.
Colors must be defined in the R software as shown in the following table.

- Label style (bold/italics/boxed) if any.
- Legend position and size (for the four areas/classes of points of the plot).
- Show connectors or not for gene labels (if any).
- Horizontal volcano plot (X and Y axis are switched, respectively).

Tab-separated plain text file that contains one list of genes. Each gene is described for the membership to a user-defined category.

Genes belonging to gene sets provided by the user will be annotated and classified following both type of information.

Example about the format on a file with genes and classes:

gene1   classx
gene2   classy
...

Number of input sets of elements to be represented as columns in the alluvial diagram. According to this number, the same amount of columns will appear in the same order in the final plot.

Plain text files that contain a list of elements for further characterization. Only one element is stored at each line. The name of the elements is used to be compared against the rest of files in order to identify the elements in common and those that are specific of each particular combination of lists.

Example about the format of one file with the elements that form a set.

element1
element2
element3
...

Text labels that will be used to identify each set in the resulting Venn diagram. Spaces and special characters will be substituted for the symbol "_".

Definition of graphical parameters to customize the Alluvial diagram of elements.

Each class as defined by the user in the membership file will be assigned a color in the same order.

Colors must be defined in the R software as shown in the following table.

Plain text file that contains a list of elements for further characterization. Only one element is stored at each line. The name of the elements is used to be compared against another file in order to identify the elements in common and those that are specific of each list.

Example about the format of one file with the elements that form a set.

element1
element2
element3
...

Plain text file that contains a list of elements for further characterization. Only one element is stored at each line. The name of the elements is used to be compared against another file in order to identify the elements in common and those that are specific of each list.

Example about the format of one file with the elements that form a set.

element1
element2
element3
...

Text labels that will be used to identify each set in the resulting Venn diagram. Spaces and special characters will be substituted for the symbol "_".

Definition of graphical parameters to customize the Venn diagram between both sets of elements.

- Background color is used to fill the circles inside.
- Circle line color is used for the line around each circle.

Colors must be defined in the R software as shown in the following table.

- Transparency degree: alpha channel value related to the opacity in overlapping areas.
- Extract the number: this option is useful when there is not enough space to put a number inside an area of the diagram.
- Distance of the set name to circle: this option is useful to increase the space between the label of the set and the corresponding circle.

Definition of graphical parameters to customize the Venn diagram global appearance.

- Font size of gene names is useful to change the size of labels outside the diagram.
- Font size of numbers is useful to change the size of numbers inside the diagram.
- Line width of circles can be used to adapt the thickness of the Venn diagram circles.
- Figure size (small/normal): this option adapts the margins of the page and generates smaller plots (if necessary).
- Extract the common number permits the user to extract the value in the intersection of the diagram.
- Distance of external numbers together with the previous option is able to change the distance of numbers to the diagram.
- Proportional sizes: this option allows the users to generate proportional sets in the final diagram according to their sizes.
- Font family (helvetica/times) defines the family of the font (sans-serif or serif).

Total number of genes in the genome to compute the significance of the overlap between both sets.

Number of input sets of elements to be compared (between 2 and 10). According to this number, the same number of files in the section below will be processed in the same order.

Plain text files that contain a list of elements for further characterization. Only one element is stored at each line. The name of the elements is used to be compared against the rest of files in order to identify the elements in common and those that are specific of each particular combination of lists.

Example about the format of one file with the elements that form a set.

element1
element2
element3
...

This option indicates the species, to be used when generating the table with the comparison codes.

Text labels that will be used to identify each set in the resulting plot. Spaces and special characters will be substituted for the symbol "_".

Definition of graphical parameters to customize the global appearance of the resulting UpSet diagram.

- Font size of the title is useful to change the size of the title above the plot
- Point size is useful to change the size of the points denoting presence of an element in a particular combination
- Font size of the top and bottom axis is useful to change the size of values on both parts of the plot
- Intersections can be ranked by the number of elements that belong to each class in the dataset. Alternatively,
this can be done using a fixed ranking based on the class of combinations irrespectively of the example
- Font size of the number of intersections is useful to change the size of these values in the plot
- Highlight the perfect combination is useful to paint in a different color the option that contains elements of every class
- Bar color is useful to change the color of the bars that denote the size of each list of elements

Colors must be defined in the R software as shown in the following table.

Number of input sets of elements to be compared (between 2 and 5). According to this number, the same number of files in the section below will be processed in the same order.

Plain text files that contain a list of elements for further characterization. Only one element is stored at each line. The name of the elements is used to be compared against the rest of files in order to identify the elements in common and those that are specific of each particular combination of lists.

Example about the format of one file with the elements that form a set.

element1
element2
element3
...

Text labels that will be used to identify each set in the resulting Venn diagram. Spaces and special characters will be substituted for the symbol "_".

Definition of graphical parameters to customize the Venn diagram among multiple sets of elements.

- Background color is used to fill the circles inside.
- Circle line color is used for the line around each circle.
(colors must defined in the R software as shown in the following table)

Definition of graphical parameters to customize the Venn diagram global appearance.

- Font size of gene names is useful to change the size of labels outside the diagram.
- Font size of numbers is useful to change the size of numbers inside the diagram.
- Figure size (small/normal): this option adapts the margins of the page and generates smaller plots (if necessary).
- Transparency degree: alpha channel value related to the opacity in overlapping areas.
- Show percentages: this option shows the percentages instead of the totals in the venn pies labels.

Select a FASTA file to be processed by MatScan. FASTA format consists on a header line (labeled by the symbol ">" and a genomic sequence divided into lines of the same length.

From the Jaspar database of predictive models for vertebrates, user can choose up to 5 models.

If the location of the sequence to be scan for TF binding sites is known over a particular chromosome, this information can be provided here to get a screenshot of the putative sites in the genome using the UCSC genome browser.

Text label that will be used to characterize the resulting list of values. Spaces and special characters will be substituted for the symbol "_".

Definition of graphical parameters to customize the Matscan maps of binding sites.

- Palette of colors (list of viridis palettes).
- A grid in grey or black and white style can be integrated as a background of the boxplot.
- Point size of TF binding sites in the map of predictions can be customized.
- Point shape of TF binding sites in the map of predictions can be customized.
- The position of each hit in the map of TF sites can be included or hidden.
- Show title: this option shows the main title above in the top of the map plot.
- Background color is used in the background of the map plot.
- Foreground color is used in the foreground elements of the map plot.

Tab-separated plain text file that contains the list of elements and features. Each line of the list contains the same number of columns: the key that identifies the current element is introduced at the column 1 while the attributes are stored from column 2 up to column N. Commas (if any) are internally susbtituted for floating points. Not available values (NA) are included in the treatment.

Example about the format on a file with elements characterized using two features:

element1   value1   value2
element2   value1   value2
element3   value1   value2
...

Selection of two columns of the file of features uploaded in the first step for the full set of elements. The ratio between both values will be used to establish the fold-change

Text label that will be used to characterize the resulting list of values. Spaces and special characters will be substituted for the symbol "_".

Users can apply to filters on the ratio calculated between both selected values:

- Fold-change: the ratio must be higher/lower than this proportion (up or down elements)
- Minimum value: useful to dismiss the elements under this minimum threshold before calculating the ratio

Tab-separated plain text file that contains the list of elements and features. Each line of the list contains the same number of columns: the key that identifies the current element is introduced at the column 1 while the attributes are stored from column 2 up to column N. Commas (if any) are internally susbtituted for floating points. Not available values (NA) are included in the treatment.

Example about the format on a file with elements characterized using two features:

element1   value1   value2
element2   value1   value2
element3   value1   value2
...

To filter those lines that do not match certain rules, users on up to three fileds are able to check whether the corresponding attributes are lower/higher/equal than particular values.

Text label that will be used to characterize the resulting list of values. Spaces and special characters will be substituted for the symbol "_".

Plain text file that contains a list of elements and values for further comparison. Only one element is stored at each line (together with its set of features). One particular column defined arbitrarily by the user (the index or key) is used to be compared against another file in order to identify the elements in common and those that are specific of each list.

Example about the format of one file with the elements that form a set.

value11 ... value1N
value21 ... value2N
value31 ... value3N
...

Plain text file that contains a list of elements and values for further comparison. Only one element is stored at each line (together with its set of features). One particular column defined arbitrarily by the user (the index or key) is used to be compared against another file in order to identify the elements in common and those that are specific of each list.

Example about the format of one file with the elements that form a set.

value11 ... value1N
value21 ... value2N
value31 ... value3N
...

Text label that will be used to characterize the elements of each list in the comparison. Spaces and special characters will be substituted for the symbol "_".

Users must indicate which column/field of each file will be used as the key or index for the comparison.