- Development and source code on github with issue tracker and documentation. Join the mailing list and find us on IRC (#genenetwork channel). + Development and source code on github with issue tracker and documentation. Join the mailing list and find us on IRC (#genenetwork channel). {% if version: %}
GeneNetwork {{ version }}
{% endif %} diff --git a/wqflask/wqflask/templates/index_page_orig.html b/wqflask/wqflask/templates/index_page_orig.html index 16caa30b..7f82b35c 100755 --- a/wqflask/wqflask/templates/index_page_orig.html +++ b/wqflask/wqflask/templates/index_page_orig.html @@ -193,7 +193,7 @@The entire procedure can be reapplied once the initial outlier data sets have been eliminated to detect any remaining outlier data sets. -
DataDesk was used to examine the statistical quality of the probe level (CEL) data after step 5 below. DataDesk allows the rapid detection of subsets of probes that are particularly sensitive to still unknown factors in array processing. Arrays can then be categorized at the probe level into "reaction classes." A reaction class is a group of arrays for which the expression of essentially all probes are colinear over the full range of log2 values. A single but large group of arrays (n = 32) processed in essentially the identical manner by a single operator can produce arrays belonging to as many as four different reaction classes. Reaction classes are NOT related to strain, age, sex, treatment, or any known biological parameter (technical replicates can belong to different reaction classes). We do not yet understand the technical origins of reaction classes. The number of probes that contribute to the definition of reaction classes is quite small (<10% of all probes). We have categorized all arrays in this data set into one of 5 reaction classes. These have then been treated as if they were separate batches. Probes in these data type "batches" have been aligned to a common mean as described below. +
DataDesk was used to examine the statistical quality of the probe level (CEL) data after step 5 below. DataDesk allows the rapid detection of subsets of probes that are particularly sensitive to still unknown factors in array processing. Arrays can then be categorized at the probe level into "reaction classes." A reaction class is a group of arrays for which the expression of essentially all probes are colinear over the full range of log2 values. A single but large group of arrays (n = 32) processed in essentially the identical manner by a single operator can produce arrays belonging to as many as four different reaction classes. Reaction classes are NOT related to strain, age, sex, treatment, or any known biological parameter (technical replicates can belong to different reaction classes). We do not yet understand the technical origins of reaction classes. The number of probes that contribute to the definition of reaction classes is quite small (<10% of all probes). We have categorized all arrays in this data set into one of 5 reaction classes. These have then been treated as if they were separate batches. Probes in these data type "batches" have been aligned to a common mean as described below. -
Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell. +
Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
Pooled RNA samples (usually one pool of male hippocampii and one pool of female hippocampii) were prepared using standard protocols. Samples were processed using a total of 206 Affymetrix GeneChip Mouse Expression 430 2.0 short oligomer arrays (MOE430 2.0 or M430v2; see GEO platform ID GPL1261), of which 201 passed quality control and error checking. This particular data set was processed using the PDNN protocol. To simplify comparisons among transforms, PDNN values of each array were adjusted to an average of 8 units and a standard deviation of 2 units. +
Pooled RNA samples (usually one pool of male hippocampii and one pool of female hippocampii) were prepared using standard protocols. Samples were processed using a total of 206 Affymetrix GeneChip Mouse Expression 430 2.0 short oligomer arrays (MOE430 2.0 or M430v2; see GEO platform ID GPL1261), of which 201 passed quality control and error checking. This particular data set was processed using the PDNN protocol. To simplify comparisons among transforms, PDNN values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
Pooled RNA samples (usually one pool of male hippocampii and one pool of female hippocampii) were prepared using standard protocols. Samples were processed using a total of 206 Affymetrix GeneChip Mouse Expression 430 2.0 short oligomer arrays (MOE430 2.0 or M430v2; see GEO platform ID GPL1261), of which 201 passed quality control and error checking. This particular data set was processed using the PDNN protocol. To simplify comparisons among transforms, PDNN values of each array were adjusted to an average of 8 units and a standard deviation of 2 units. +
Pooled RNA samples (usually one pool of male hippocampii and one pool of female hippocampii) were prepared using standard protocols. Samples were processed using a total of 206 Affymetrix GeneChip Mouse Expression 430 2.0 short oligomer arrays (MOE430 2.0 or M430v2; see GEO platform ID GPL1261), of which 201 passed quality control and error checking. This particular data set was processed using the PDNN protocol. To simplify comparisons among transforms, PDNN values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
Please cite: Overall RW, Kempermann G, Peirce J, Lu L, Goldowitz D, Gage FH, Goodwin S, Smit AB, Airey DC, Rosen GD, Schalkwyk LC, Sutter TR, Nowakowski RS, Whatley S, Williams RW (2009) Genetics of the hippocampal transcriptome in mice: a systematic survey and online neurogenomic resource. Front. Neurogen. 1:3 Full Text HTML doi:10.3389/neuro.15.003.2009 +
Please cite: Overall RW, Kempermann G, Peirce J, Lu L, Goldowitz D, Gage FH, Goodwin S, Smit AB, Airey DC, Rosen GD, Schalkwyk LC, Sutter TR, Nowakowski RS, Whatley S, Williams RW (2009) Genetics of the hippocampal transcriptome in mice: a systematic survey and online neurogenomic resource. Front. Neurogen. 1:3 Full Text HTML doi:10.3389/neuro.15.003.2009