IList <int> ToIndexList(INumberTable nTable, bool attributeMode, IList <string> itemList)
{
if (attributeMode)
{
return(nTable.IndexOfColumns(itemList));
}
else
{
return(nTable.IndexOfRows(itemList));
}
}
public List <string> Expression(List <string> selectedIds, double threshold)
{
const short maxExprIndex = 13; // number of expressed levels.
const short indexShift = 38;
double[][] M = (double[][])(NumTable.Matrix);
int cellNr = NumTable.Rows;
int geneNr = NumTable.Columns;
IList <int> selectedCells = NumTable.IndexOfRows(selectedIds);
IList <int> selectedGenes = NumTable.IndexOfColumns(selectedIds);
List <string> expressedId = new List <string>();
if (threshold == 0) // mark the genes/cells which have higher expression than the average of selected genes/cells.
{
if (GeneToCell) // Finding expressed cells for selected genes. Gene->Cell operation.
{
double[] expression = new double[cellNr]; // total expression of each cell.
MT.Loop(0, cellNr, row => {
foreach (int col in selectedGenes)
{
expression[row] += M[row][col];
}
});
double meanExp = expression.Sum() / cellNr;
double maxExp = expression.Max();
double step = (maxExp - meanExp) / maxExprIndex;
this.Genes = selectedGenes.Count;
this.Cells = 0;
for (int i = 0; i < cellNr; i++) // for each cells.
{
double delta = expression[i] - meanExp;
int bIdx = row2bodyIdx[i];
if (delta > 0)
{
short v = Math.Min(maxExprIndex, (short)(delta / step));
BodyList[bIdx].Type = (short)(indexShift + v);
this.Cells++;
expressedId.Add(BodyList[bIdx].Id);
}
else
{
BodyList[bIdx].Type = OrgBodies[bIdx].Type;
}
}
}
else
{
double[] expression = new double[geneNr]; // total expression of each gene.
MT.Loop(0, geneNr, col => {
foreach (int row in selectedCells)
{
expression[col] += M[row][col];
}
});
double meanExp = expression.Sum() / geneNr;
double maxExp = expression.Max();
double step = (maxExp - meanExp) / maxExprIndex;
// Finding expressed genes for selected cells. Cell->Gene operation.
this.Cells = selectedCells.Count;
this.Genes = 0;
for (int i = 0; i < geneNr; i++) // for each gene.
{
double delta = expression[i] - meanExp;
int bIdx = col2bodyIdx[i];
if (delta > 0)
{
int v = Math.Min(maxExprIndex, (int)(delta / step));
BodyList[bIdx].Type = (short)(indexShift + v);
this.Genes++;
expressedId.Add(BodyList[bIdx].Id);
}
else
{
BodyList[bIdx].Type = OrgBodies[bIdx].Type;
}
}
}
}
else // Mark all those cells/genes which have above global average expressions.
{
if (GeneToCell)
{
short[] expressed = new short[cellNr]; // count of expressed genes for each cell.
MT.Loop(0, cellNr, row => {
foreach (int col in selectedGenes)
{
if (M[row][col] > threshold)
{
expressed[row] += 1;
}
}
});
this.Genes = selectedGenes.Count;
this.Cells = expressed.Count(v => v > 0);
for (int i = 0; i < cellNr; i++)
{
short v = Math.Min(maxExprIndex, expressed[i]);
int bIdx = row2bodyIdx[i];
BodyList[bIdx].Type = (short)((v > 0) ? (indexShift + v) : OrgBodies[bIdx].Type);
if (v > 0)
{
expressedId.Add(BodyList[bIdx].Id);
}
}
}
else
{
short[] expressed = new short[geneNr]; // count of expressed cells for each gene.
MT.Loop(0, geneNr, col => {
foreach (int row in selectedCells)
{
if (M[row][col] > threshold)
{
expressed[col] += 1;
}
}
});
this.Cells = selectedCells.Count;
this.Genes = expressed.Count(v => v > 0);
for (int i = 0; i < geneNr; i++)
{
short v = Math.Min(maxExprIndex, expressed[i]);
int bIdx = col2bodyIdx[i];
BodyList[bIdx].Type = (short)((v > 0) ? (indexShift + v) : OrgBodies[bIdx].Type);
if (v > 0)
{
expressedId.Add(BodyList[bIdx].Id);
}
}
}
}
return(expressedId);
}